Research on Assessment Methods for Urban Public Transport Development in China

PubMed Central

Zou, Linghong; Guo, Hongwei

2014-01-01

In recent years, with the rapid increase in urban population, the urban travel demands in Chinese cities have been increasing dramatically. As a result, developing comprehensive urban transport systems becomes an inevitable choice to meet the growing urban travel demands. In urban transport systems, public transport plays the leading role to promote sustainable urban development. This paper aims to establish an assessment index system for the development level of urban public transport consisting of a target layer, a criterion layer, and an index layer. Review on existing literature shows that methods used in evaluating urban public transport structure are dominantly qualitative. To overcome this shortcoming, fuzzy mathematics method is used for describing qualitative issues quantitatively, and AHP (analytic hierarchy process) is used to quantify expert's subjective judgment. The assessment model is established based on the fuzzy AHP. The weight of each index is determined through the AHP and the degree of membership of each index through the fuzzy assessment method to obtain the fuzzy synthetic assessment matrix. Finally, a case study is conducted to verify the rationality and practicability of the assessment system and the proposed assessment method. PMID:25530756

Assessing coastal reclamation suitability based on a fuzzy-AHP comprehensive evaluation framework: A case study of Lianyungang, China.

PubMed

Feng, Lan; Zhu, Xiaodong; Sun, Xiang

2014-12-15

Coastal reclamation suitability evaluation (CRSE) is a difficult, complex and protracted process requiring the evaluation of many different criteria. In this paper, an integrated framework employing a fuzzy comprehensive evaluation method and analytic hierarchy process (AHP) was applied to the suitability evaluation for coastal reclamation for future sustainable development in the coastal area of Lianyungang, China. The evaluation results classified 6.63%, 22.99%, 31.59% and 38.79% of the coastline as suitable, weakly suitable, unsuitable and forbidden, respectively. The evaluation results were verified by the marine pollution data and highly consistent with the water quality status. The fuzzy-AHP comprehensive evaluation method (FACEM) was found to be suitable for the CRSE. This CRSE can also be applied to other coastal areas in China and thereby be used for the better management of coastal reclamation and coastline protection projects. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation and selection of 3PL provider using fuzzy AHP and grey TOPSIS in group decision making

NASA Astrophysics Data System (ADS)

Garside, Annisa Kesy; Saputro, Thomy Eko

2017-11-01

Selection of a 3PL provider is a problem of multi criteria decision making, where the decision maker has to select several 3PL provider alternatives based on several evaluation criteria. A decision maker will have difficulty to express judgments in exact numerical values due to the fact that information is often incomplete and the decision environment is uncertain. This paper presents an integrated fuzzy AHP and Grey TOPSIS for the evaluation and selection of 3PL provider method. Fuzzy AHP is used to determine the importance weight of evaluation criteria. For final selection, grey TOPSIS is used to evaluate the alternatives and obtain the overall performance which is measured as closeness coefficient. This method is applied to solve the selection of 3PL provider at PT. X. Five criterias and twelve sub-criterias were determined and then the best alternative among four 3PL providers was selected by proposed method.

Fuzzy Decision Analysis for Integrated Environmental Vulnerability Assessment of the Mid-Atlantic Region

Treesearch

Liem T. Tran; C. Gregory Knight; Robert V. O' Neill; Elizabeth R. Smith; Kurt H. Riitters; James D. Wickham

2002-01-01

A fuzzy decision analysis method for integrating ecological indicators was developed. This was a combination of a fuzzy ranking method and the analytic hierarchy process (AHP). The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams,...

Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia

NASA Astrophysics Data System (ADS)

Abdullah, Lazim; Najib, Liana

2016-04-01

Energy consumption for developing countries is sharply increasing due to the higher economic growth due to industrialisation along with population growth and urbanisation. The increasing demand of energy leads to global energy crisis. Selecting the best energy technology and conservation requires both quantitative and qualitative evaluation criteria. The fuzzy set-based approach is one of the well-known theories to handle fuzziness, uncertainty in decision-making and vagueness of information. This paper proposes a new method of intuitionistic fuzzy analytic hierarchy process (IF-AHP) to deal with the uncertainty in decision-making. The new IF-AHP is applied to establish a preference in the sustainable energy planning decision-making problem. Three decision-makers attached with Malaysian government agencies were interviewed to provide linguistic judgement prior to analysing with the new IF-AHP. Nuclear energy has been decided as the best alternative in energy planning which provides the highest weight among all the seven alternatives.

Comparative Analysis of AHP-TOPSIS and Fuzzy AHP Models in Selecting Appropriate Nanocomposites for Environmental Noise Barrier Applications

NASA Astrophysics Data System (ADS)

Naderzadeh, Mahdiyeh; Arabalibeik, Hossein; Monazzam, Mohammad Reza; Ghasemi, Ismaeil

Choosing the right material in the design of environmental noise barriers has always been a challenging issue in acoustics. In less-developed countries, the material selection is affected by many factors from various aspects, which makes the decision-making very complicated. This study attempts to compare and assign weights to the most important indices affecting the choice of appropriate noise barrier material. These criteria include absorption coefficient, transparency, tensile modulus, strength at yield, elongation at break, impact strength, flexural modulus, hardness, and cost. For this purpose, experts' opinions was gathered through a total of 13 questionnaires and used for assigning weights by Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy process (FAHP) techniques. According to the AHP results, impact strength, with only a minor difference of 0.093 compared to the AHP, was recognized as the most important criterion. Finally, the optimal composite material was selected using two different methods; first by Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS) based on the weights obtained from AHP, and next by directly applying the obtained weights from FAHP to the true measured values of parameters. As the results show, in both abovementioned methods, Polycarbonate-SiO2 0.3% with roughened surface (PCSI3-R) received the highest score and was selected as the preferred composite material. Given the close similarity of the results, to determine the superiority of one method over the other, some noise was added to the original data set from the mechanical and acoustic tests and then the variance of the changes in the final orders of preferences was calculated. This indicates the robustness of the method against the measurement errors and noise. The results shows that under the same circumstances, the overall order shift variance in the classic TOPSIS is six times higher than that of the fuzzy AHP method.

Modeling Choice Under Uncertainty in Military Systems Analysis

DTIC Science & Technology

1991-11-01

operators rather than fuzzy operators. This is suggested for further research. 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) In AHP , objectives, functions and...14 4.1 IMPRECISELY SPECIFIED MULTIPLE A’ITRIBUTE UTILITY THEORY... 14 4.2 FUZZY DECISION ANALYSIS...14 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) ................................... 14 4.4 SUBJECTIVE TRANSFER FUNCTION APPROACH

Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment.

PubMed

Onüt, Semih; Soner, Selin

2008-01-01

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker to describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.

Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

PubMed

Zhou, Ronggang; Chan, Alan H S

2017-01-01

In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process.

a New Multimodal Multi-Criteria Route Planning Model by Integrating a Fuzzy-Ahp Weighting Method and a Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Ghaderi, F.; Pahlavani, P.

2015-12-01

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user's bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.

Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework

PubMed Central

Zhou, Ronggang; Chan, Alan H. S.

2016-01-01

BACKGROUND: In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. OBJECTIVE: This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. METHODS: With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. RESULTS AND CONCLUSIONS: Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process. PMID:28035943

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

DTIC Science & Technology

2002-03-01

such as weighted sum method, weighted 5 product method, and the Analytic Hierarchy Process ( AHP ). This research focuses on only weighted sum...different groups. They can be termed as deterministic, stochastic, or fuzzy multi-objective decision methods if they are classified according to the...weighted product model (WPM), and analytic hierarchy process ( AHP ). His method attempts to identify the most important criteria weight and the most

An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness.

PubMed

Nguyen, Huu-Tho; Dawal, Siti Zawiah Md; Nukman, Yusoff; Rifai, Achmad P; Aoyama, Hideki

2016-01-01

The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts' uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; P. Rifai, Achmad; Aoyama, Hideki

2016-01-01

The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts’ uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs. PMID:27070543

Artificial Intelligence Methods in Pursuit Evasion Differential Games

DTIC Science & Technology

1990-07-30

objectives, sometimes with fuzzy ones. Classical optimization, control or game theoretic methods are insufficient for their resolution. I Solution...OVERALL SATISFACTION WITH SCHOOL 120 FIGURE 5.13 EXAMPLE AHP HIERARCHY FOR CHOOSING MOST APPROPRIATE DIFFERENTIAL GAME AND PARAMETRIZATION 125 FIGURE 5.14...the Analytical Hierarchy Process originated by T.L. Saaty of the Wharton School. The Analytic Hierarchy Process ( AHP ) is a general theory of

Application of multiattribute decision-making methods for the determination of relative significance factor of impact categories.

PubMed

Noh, Jaesung; Lee, Kun Mo

2003-05-01

A relative significance factor (f(i)) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f(i). Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f(i). Thus, all three methods can be applied to the determination of f(i). The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f(i) because it is easier and simpler to use compared to the AHP and the fuzzy method.

Using fuzzy logic analysis for siting decisions of infiltration trenches for highway runoff control.

PubMed

Ki, Seo Jin; Ray, Chittaranjan

2014-09-15

Determining optimal locations for best management practices (BMPs), including their field considerations and limitations, plays an important role for effective stormwater management. However, these issues have been often overlooked in modeling studies that focused on downstream water quality benefits. This study illustrates the methodology of locating infiltration trenches at suitable locations from spatial overlay analyses which combine multiple layers that address different aspects of field application into a composite map. Using seven thematic layers for each analysis, fuzzy logic was employed to develop a site suitability map for infiltration trenches, whereas the DRASTIC method was used to produce a groundwater vulnerability map on the island of Oahu, Hawaii, USA. In addition, the analytic hierarchy process (AHP), one of the most popular overlay analyses, was used for comparison to fuzzy logic. The results showed that the AHP and fuzzy logic methods developed significantly different index maps in terms of best locations and suitability scores. Specifically, the AHP method provided a maximum level of site suitability due to its inherent aggregation approach of all input layers in a linear equation. The most eligible areas in locating infiltration trenches were determined from the superposition of the site suitability and groundwater vulnerability maps using the fuzzy AND operator. The resulting map successfully balanced qualification criteria for a low risk of groundwater contamination and the best BMP site selection. The results of the sensitivity analysis showed that the suitability scores were strongly affected by the algorithms embedded in fuzzy logic; therefore, caution is recommended with their use in overlay analysis. Accordingly, this study demonstrates that the fuzzy logic analysis can not only be used to improve spatial decision quality along with other overlay approaches, but also is combined with general water quality models for initial and refined searches for the best locations of BMPs at the sub-basin level. Copyright © 2014. Published by Elsevier B.V.

Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS

NASA Astrophysics Data System (ADS)

Boroushaki, Soheil; Malczewski, Jacek

2008-04-01

This paper focuses on the integration of GIS and an extension of the analytical hierarchy process (AHP) using quantifier-guided ordered weighted averaging (OWA) procedure. AHP_OWA is a multicriteria combination operator. The nature of the AHP_OWA depends on some parameters, which are expressed by means of fuzzy linguistic quantifiers. By changing the linguistic terms, AHP_OWA can generate a wide range of decision strategies. We propose a GIS-multicriteria evaluation (MCE) system through implementation of AHP_OWA within ArcGIS, capable of integrating linguistic labels within conventional AHP for spatial decision making. We suggest that the proposed GIS-MCE would simplify the definition of decision strategies and facilitate an exploratory analysis of multiple criteria by incorporating qualitative information within the analysis.

Risk evaluation of highway engineering project based on the fuzzy-AHP

NASA Astrophysics Data System (ADS)

Yang, Qian; Wei, Yajun

2011-10-01

Engineering projects are social activities, which integrate with technology, economy, management and organization. There are uncertainties in each respect of engineering projects, and it needs to strengthen risk management urgently. Based on the analysis of the characteristics of highway engineering, and the study of the basic theory on risk evaluation, the paper built an index system of highway project risk evaluation. Besides based on fuzzy mathematics principle, analytical hierarchy process was used and as a result, the model of the comprehensive appraisal method of fuzzy and AHP was set up for the risk evaluation of express way concessionary project. The validity and the practicability of the risk evaluation of expressway concessionary project were verified after the model was applied to the practice of a project.

Highlights from the 17th International Conference on Multi-Criteria Decision Making, Whistler, BC, August 6-11, 2004

DTIC Science & Technology

2005-04-01

related to one of the following areas: 1. Group Decision Support Methods; 2. Decision Support Methods; 3. AHP applications; 4. Multi...Objective Linear Programming (MOLP) algorithms; 5. Industrial engineering applications; 6. Behavioural considerations, and 7. Fuzzy MCDM. 3...making. This is especially important when using software like AHP or when constructing questionnaires for SME’s ( see [10] for many examples

Aggregating Individual Preferences in the Analytic Hierarchy Process Applied to the 1983 Battelle TAV Study.

DTIC Science & Technology

1985-03-15

elicitation - rankings, ratings, and pairwise comparisons, 2) Value Theory: includes an explanation of the AHP and fuzzy set theory, and 3) Group... AHP are better tools for these " fuzzy " applications. These results apply directly to this thesis. The original Battelle survey used direct ratings to...iridepeindent uf three arggretation toctiiIque5: geometric mean input, arithmetic me;n voctor output, and Majority rle,, output. The AHP consi:3tcncy index was

Wastewater treatment evaluation for enterprises based on fuzzy-AHP comprehensive evaluation: a case study in industrial park in Taihu Basin, China.

PubMed

Hu, Wei; Liu, Guangbing; Tu, Yong

2016-01-01

This paper applied the fuzzy comprehensive evaluation (FCE) technique and analytic hierarchy process (AHP) procedure to evaluate the wastewater treatment for enterprises. Based on the characteristics of wastewater treatment for enterprises in Taihu basin, an evaluating index system was established for enterprise and analysis hierarchy process method was applied to determine index weight. Then the AHP and FCE methods were combined to validate the wastewater treatment level of 3 representative enterprises. The results show that the evaluation grade of enterprise 1, enterprise 2 and enterprise 3 was middle, good and excellent, respectively. Finally, the scores of 3 enterprises were calculated according to the hundred-mark system, and enterprise 3 has the highest wastewater treatment level, followed by enterprise 2 and enterprises 1. The application of this work can make the evaluation results more scientific and accurate. It is expected that this work may serve as an assistance tool for managers of enterprise in improving the wastewater treatment level.

Comparison of Customer Preference for Bulk Material Handling Equipment through Fuzzy-AHP Approach

NASA Astrophysics Data System (ADS)

Sen, Kingshuk; Ghosh, Surojit; Sarkar, Bijan

2017-06-01

In the present study, customer's perception has played one of the important roles for selection of the exact equipment out of available alternatives. The present study is dealt with the method of optimization of selection criteria of a material handling equipment, based on the technical specifications considered to be available at the user end. In this work, the needs of customers have been identified and prioritized, that lead to the selection of number of criteria, which have direct effect upon the performance of the equipment. To check the consistency of selection criteria, first of all an AHP based methodology is adopted with the identified criteria and available product categories, based upon which, the judgments of the users are defined to derive the priority scales. Such judgments expressed the relative strength or intensity of the impact of the elements of the hierarchy. Subsequently, all the alternatives have ranked for each identified criteria with subsequent constitution of weighted matrices. The same has been compared with the normalized values of approximate selling prices of the equipments to determine individual cost-benefit ratio. Based on the cost-benefit ratio, the equipment is ranked. With same conditions, the study is obtained again with a Fuzzy AHP concept, where a fuzzy linguistic approach has reduced the amount of uncertainty in decision making, caused by conventional AHP due to lack of deterministic approach. The priority vectors of category and criteria are determined separately and multiplied to obtain composite score. Subsequently, the average of fuzzy weights was determined and the preferences of equipment are ranked.

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

Group Decision Support System to Aid the Process of Design and Maintenance of Large Scale Systems

DTIC Science & Technology

1992-03-23

from a fuzzy set of user requirements. The overall objective of the project is to develop a system combining the characteristics of a compact computer... AHP ) for hierarchical prioritization. 4) Individual Evaluation and Selection of Alternatives - Allows the decision maker to individually evaluate...its concept of outranking relations. The AHP method supports complex decision problems by successively decomposing and synthesizing various elements

A Model for the Development of Hospital Beds Using Fuzzy Analytical Hierarchy Process (Fuzzy AHP)

PubMed Central

RAVANGARD, Ramin; BAHADORI, Mohammadkarim; RAADABADI, Mehdi; TEYMOURZADEH, Ehsan; ALIMOMOHAMMADZADEH, Khalil; MEHRABIAN, Fardin

2017-01-01

Background: This study aimed to identify and prioritize factors affecting the development of military hospital beds and provide a model using fuzzy analytical hierarchy process (Fuzzy AHP). Methods: This applied study was conducted in 2016 in Iran using a mixed method. The sample included experts in the field of military health care system. The MAXQDA 10.0 and Expert Choice 10.0 software were used for analyzing the collected data. Results: Geographic situation, demographic status, economic status, health status, health care centers and organizations, financial and human resources, laws and regulations and by-laws, and the military nature of service recipients had effects on the development of military hospital beds. The military nature of service recipients (S=0.249) and economic status (S=0.040) received the highest and lowest priorities, respectively. Conclusion: Providing direct health care services to the military forces in order to maintain their dignity, and according to its effects in the crisis, as well as the necessity for maintaining the security of the armed forces, and the hospital beds per capita based on the existing laws, regulations and bylaws are of utmost importance. PMID:29167775

The use of multi-criteria decision making models in evaluating anesthesia method options in circumcision surgery.

PubMed

Hancerliogullari, Gulsah; Hancerliogullari, Kadir Oymen; Koksalmis, Emrah

2017-01-23

Determining the most suitable anesthesia method for circumcision surgery plays a fundamental role in pediatric surgery. This study is aimed to present pediatric surgeons' perspective on the relative importance of the criteria for selecting anesthesia method for circumcision surgery by utilizing the multi-criteria decision making methods. Fuzzy set theory offers a useful tool for transforming linguistic terms into numerical assessments. Since the evaluation of anesthesia methods requires linguistic terms, we utilize the fuzzy Analytic Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Both mathematical decision-making methods are originated from individual judgements for qualitative factors utilizing the pair-wise comparison matrix. Our model uses four main criteria, eight sub-criteria as well as three alternatives. To assess the relative priorities, an online questionnaire was completed by three experts, pediatric surgeons, who had experience with circumcision surgery. Discussion of the results with the experts indicates that time-related factors are the most important criteria, followed by psychology, convenience and duration. Moreover, general anesthesia with penile block for circumcision surgery is the preferred choice of anesthesia compared to general anesthesia without penile block, which has a greater priority compared to local anesthesia under the discussed main-criteria and sub-criteria. The results presented in this study highlight the need to integrate surgeons' criteria into the decision making process for selecting anesthesia methods. This is the first study in which multi-criteria decision making tools, specifically fuzzy AHP and fuzzy TOPSIS, are used to evaluate anesthesia methods for a pediatric surgical procedure.

Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

NASA Astrophysics Data System (ADS)

Tazik, E.; Jahantab, Z.; Bakhtiari, M.; Rezaei, A.; Kazem Alavipanah, S.

2014-10-01

Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

A Model for the Development of Hospital Beds Using Fuzzy Analytical Hierarchy Process (Fuzzy AHP).

PubMed

Ravangard, Ramin; Bahadori, Mohammadkarim; Raadabadi, Mehdi; Teymourzadeh, Ehsan; Alimomohammadzadeh, Khalil; Mehrabian, Fardin

2017-11-01

This study aimed to identify and prioritize factors affecting the development of military hospital beds and provide a model using fuzzy analytical hierarchy process (Fuzzy AHP). This applied study was conducted in 2016 in Iran using a mixed method. The sample included experts in the field of military health care system. The MAXQDA 10.0 and Expert Choice 10.0 software were used for analyzing the collected data. Geographic situation, demographic status, economic status, health status, health care centers and organizations, financial and human resources, laws and regulations and by-laws, and the military nature of service recipients had effects on the development of military hospital beds. The military nature of service recipients (S=0.249) and economic status (S=0.040) received the highest and lowest priorities, respectively. Providing direct health care services to the military forces in order to maintain their dignity, and according to its effects in the crisis, as well as the necessity for maintaining the security of the armed forces, and the hospital beds per capita based on the existing laws, regulations and bylaws are of utmost importance.

Constructing the Indicators of Assessing Human Vulnerability to Industrial Chemical Accidents: A Consensus-based Fuzzy Delphi and Fuzzy AHP Approach

PubMed Central

Fatemi, Farin; Ardalan, Ali; Aguirre, Benigno; Mansouri, Nabiollah; Mohammadfam, Iraj

2017-01-01

Introduction: Industrial chemical accidents have been increased in developing countries. Assessing the human vulnerability in the residents of industrial areas is necessary for reducing the injuries and causalities of chemical hazards. The aim of this study was to explore the key indicators for the assessment of human vulnerability in the residents living near chemical installations. Methods: The indicators were established in the present study based on the Fuzzy Delphi method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP). The reliability of FDM and FAHP was calculated. The indicators of human vulnerability were explored in two sets of social and physical domains. Thirty-five relevant experts participated in this study during March-July 2015. Results: According to experts, the top three indicators of human vulnerability according to the FDM and FAHP were vulnerable groups, population density, and awareness. Detailed sub-vulnerable groups and awareness were developed based on age, chronic or severe diseases, disability, first responders, and residents, respectively. Each indicator and sub-indicator was weighted and ranked and had an acceptable consistency ratio. Conclusions: The importance of social vulnerability indicators are about 7 times more than physical vulnerability indicators. Among the extracted indicators, vulnerable groups had the highest weight and the greatest impact on human vulnerability. however, further research is needed to investigate the applicability of established indicators and generalizability of the results to other studies. Key words: Fuzzy Delphi; Fuzzy AHP; Human vulnerability; Chemical hazards PMID:28480124

Non-Cooperative Group Decision Support Systems: Problems and Some Solutions.

DTIC Science & Technology

1986-09-01

appears that in these situations the 46 content of the problem and the structure of the problem is " fuzzy ." It requires an active cooperation between the...some unstructured parts will remain. This partial ’unstructurability’ is due to uncertainty, fuzziness , ignorance, and an inability to...according to the Analytic Hierarchy Process ( AHP ) technique (Gui, 1985). The AHP algorithm consists of the following steps; (i) Perform a pairwise comparison

A new web-based framework development for fuzzy multi-criteria group decision-making.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

Gis-Based Site Selection for Underground Natural Resources Using Fuzzy Ahp-Owa

NASA Astrophysics Data System (ADS)

Sabzevari, A. R.; Delavar, M. R.

2017-09-01

Fuel consumption has significantly increased due to the growth of the population. A solution to address this problem is the underground storage of natural gas. The first step to reach this goal is to select suitable places for the storage. In this study, site selection for the underground natural gas reservoirs has been performed using a multi-criteria decision-making in a GIS environment. The "Ordered Weighted Average" (OWA) operator is one of the multi-criteria decision-making methods for ranking the criteria and consideration of uncertainty in the interaction among the criteria. In this paper, Fuzzy AHP_OWA (FAHP_OWA) is used to determine optimal sites for the underground natural gas reservoirs. Fuzzy AHP_OWA considers the decision maker's risk taking and risk aversion during the decision-making process. Gas consumption rate, temperature, distance from main transportation network, distance from gas production centers, population density and distance from gas distribution networks are the criteria used in this research. Results show that the northeast and west of Iran and the areas around Tehran (Tehran and Alborz Provinces) have a higher attraction for constructing a natural gas reservoir. The performance of the used method was also evaluated. This evaluation was performed using the location of the existing natural gas reservoirs in the country and the site selection maps for each of the quantifiers. It is verified that the method used in this study is capable of modeling different decision-making strategies used by the decision maker with about 88 percent of agreement between the modeling and test data.

Hierarchical semi-numeric method for pairwise fuzzy group decision making.

PubMed

Marimin, M; Umano, M; Hatono, I; Tamura, H

2002-01-01

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.

Dynamic fuzzy hierarchy analysis for evaluation of professionalization degree

NASA Astrophysics Data System (ADS)

Jin, Lin; Min, Luo; Ma, Jingxi

2016-06-01

This paper presents the model of dynamic fuzzy hierarchy analysis for evaluation of professionalization degree, as a combination of the dynamic fuzzy theory and the AHP, which can show the changes and trends of the value of each index of professionalization.

Selecting the best rayon in customer’s perspective using fuzzy analytic hierarchy process

NASA Astrophysics Data System (ADS)

Sonjaya, E. G.; Paulus, E.; Hidayat, A.

2018-03-01

Annually, the best Rayon selection is conducted by the assessment team of PT.PLN (Persero) Cirebon with the goal to increase the spirit of company members in providing an improved service for customers. However, there is a problem in multiple criteria decision making in this case, which is the importance intensity of each criterion in the selection are often assessed subjectively. To solve this problem, Fuzzy Analytical Hierarchy Process are used to cover AHP scale deficiency in the form of ‘crisp’ numbers. So, it should be considered to use Fuzzy logic approach to handle uncertainty. Fuzzy approach, especially triangular fuzzy number towards AHP scale, are expected to minimize the handling of subjective input, which then will make a more objective result. Thus, this research was conducted to help the management or assessment team in the selection of the best Rayon with a more objective selection in according to the company criteria.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Onuet, Semih; Soner, Selin

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker tomore » describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.« less

Constructing the Indicators of Assessing Human Vulnerability to Industrial Chemical Accidents: A Consensus-based Fuzzy Delphi and Fuzzy AHP Approach.

PubMed

Fatemi, Farin; Ardalan, Ali; Aguirre, Benigno; Mansouri, Nabiollah; Mohammadfam, Iraj

2017-04-10

Industrial chemical accidents have been increased in developing countries. Assessing the human vulnerability in the residents of industrial areas is necessary for reducing the injuries and causalities of chemical hazards. The aim of this study was to explore the key indicators for the assessment of human vulnerability in the residents living near chemical installations. The indicators were established in the present study based on the Fuzzy Delphi method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP). The reliability of FDM and FAHP was calculated. The indicators of human vulnerability were explored in two sets of social and physical domains. Thirty-five relevant experts participated in this study during March-July 2015. According to experts, the top three indicators of human vulnerability according to the FDM and FAHP were vulnerable groups, population density, and awareness. Detailed sub-vulnerable groups and awareness were developed based on age, chronic or severe diseases, disability, first responders, and residents, respectively. Each indicator and sub-indicator was weighted and ranked and had an acceptable consistency ratio. The importance of social vulnerability indicators are about 7 times more than physical vulnerability indicators. Among the extracted indicators, vulnerable groups had the highest weight and the greatest impact on human vulnerability. however, further research is needed to investigate the applicability of established indicators and generalizability of the results to other studies. Fuzzy Delphi; Fuzzy AHP; Human vulnerability; Chemical hazards.

Research on Logistics Service Providers Selection Based on AHP and VIKOR

NASA Astrophysics Data System (ADS)

Shan, Lu

The logistics service providers supply a kind of service which is a service product, thus there is a plenty of uncertainty and fuzzy in selecting logistics service providers. AHP is first used to calculate the weights of logistics services providers evaluations and then VIKOR method developed for multi-criteria optimization determining a compromise solution is applied to select the logistics services providers. The latter method provides a maximum "group utility" for the "majority" and minimum of an individual regret for the "opponent". This decision making process of logistics services providers selection is verified to be scientific and feasible through the empirical research.

Integrating GIS with AHP and Fuzzy Logic to generate hand, foot and mouth disease hazard zonation (HFMD-HZ) model in Thailand

NASA Astrophysics Data System (ADS)

Samphutthanon, R.; Tripathi, N. K.; Ninsawat, S.; Duboz, R.

2014-12-01

The main objective of this research was the development of an HFMD hazard zonation (HFMD-HZ) model by applying AHP and Fuzzy Logic AHP methodologies for weighting each spatial factor such as disease incidence, socio-economic and physical factors. The outputs of AHP and FAHP were input into a Geographic Information Systems (GIS) process for spatial analysis. 14 criteria were selected for analysis as important factors: disease incidence over 10 years from 2003 to 2012, population density, road density, land use and physical features. The results showed a consistency ratio (CR) value for these main criteria of 0.075427 for AHP, the CR for FAHP results was 0.092436. As both remained below the threshold of 0.1, the CR value were acceptable. After linking to actual geospatial data (disease incidence 2013) through spatial analysis by GIS for validation, the results of the FAHP approach were found to match more accurately than those of the AHP approach. The zones with the highest hazard of HFMD outbreaks were located in two main areas in central Muang Chiang Mai district including suburbs and Muang Chiang Rai district including the vicinity. The produced hazardous maps may be useful for organizing HFMD protection plans.

Assessment of land suitability for olive mill wastewater disposal site selection by integrating fuzzy logic, AHP, and WLC in a GIS.

PubMed

Aydi, Abdelwaheb; Abichou, Tarek; Nasr, Imen Hamdi; Louati, Mourad; Zairi, Moncef

2016-01-01

This paper presents a geographic information system-based multi-criteria site selection tool of an olive mill wastewater (OMW) disposal site in Sidi Bouzid Region, Tunisia. The multi-criteria decision framework integrates ten constraints and six factors that relate to environmental and economic concerns, and builds a hierarchy model for OMW disposal site suitability. The methodology is used for preliminary assessment of the most suitable OMW disposal sites by combining fuzzy set theory and analytic hierarchy process (AHP). The fuzzy set theory is used to standardize factors using different fuzzy membership functions while the AHP is used to establish the relative importance of the criteria. The AHP makes pairwise comparisons of relative importance between hierarchy elements grouped by both environmental and economic decision criteria. The OMW disposal site suitability is achieved by applying a weighted linear combination that uses a comparison matrix to aggregate different importance scenarios associated with environmental and economic objectives. Three different scenarios generated by different weights applied to the two objectives. The scenario (a) assigns a weight of 0.75 to the environmental and 0.25 to the economic objective, scenario (b) has equal weights, and scenario (c) features weights of 0.25 and 0.75 for environmental and economic objectives, respectively. The results from this study assign the least suitable OMW disposal site of 2.5 % when environmental and economic objectives are rated equally, while a more suitable OMW disposal site of 1.0 % is generated when the economic objective is rated higher.

Application of Fuzzy Analytic Hierarchy Process to Building Research Teams

NASA Astrophysics Data System (ADS)

Dąbrowski, Karol; Skrzypek, Katarzyna

2016-03-01

Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process) and ANFIS (Adaptive Neuro Fuzzy Inference System) methods in working groups building for R&D projects on the basis of employees skills.

Susceptibility mapping of visceral leishmaniasis based on fuzzy modelling and group decision-making methods.

PubMed

Rajabi, Mohamadreza; Mansourian, Ali; Bazmani, Ahad

2012-11-01

Visceral leishmaniasis (VL) is a vector-borne disease, highly influenced by environmental factors, which is an increasing public health problem in Iran, especially in the north-western part of the country. A geographical information system was used to extract data and map environmental variables for all villages in the districts of Kalaybar and Ahar in the province of East Azerbaijan. An attempt to predict VL prevalence based on an analytical hierarchy process (AHP) module combined with ordered weighted averaging (OWA) with fuzzy quantifiers indicated that the south-eastern part of Ahar is particularly prone to high VL prevalence. With the main objective to locate the villages most at risk, the opinions of experts and specialists were generalised into a group decision-making process by means of fuzzy weighting methods and induced OWA. The prediction model was applied throughout the entire study area (even where the disease is prevalent and where data already exist). The predicted data were compared with registered VL incidence records in each area. The results suggest that linguistic fuzzy quantifiers, guided by an AHP-OWA model, are capable of predicting susceptive locations for VL prevalence with an accuracy exceeding 80%. The group decision-making process demonstrated that people in 15 villages live under particularly high risk for VL contagion, i.e. villages where the disease is highly prevalent. The findings of this study are relevant for the planning of effective control strategies for VL in northwest Iran.

Using a fuzzy comprehensive evaluation method to determine product usability: A test case

PubMed Central

Zhou, Ronggang; Chan, Alan H. S.

2016-01-01

BACKGROUND: In order to take into account the inherent uncertainties during product usability evaluation, Zhou and Chan [1] proposed a comprehensive method of usability evaluation for products by combining the analytic hierarchy process (AHP) and fuzzy evaluation methods for synthesizing performance data and subjective response data. This method was designed to provide an integrated framework combining the inevitable vague judgments from the multiple stages of the product evaluation process. OBJECTIVE AND METHODS: In order to illustrate the effectiveness of the model, this study used a summative usability test case to assess the application and strength of the general fuzzy usability framework. To test the proposed fuzzy usability evaluation framework [1], a standard summative usability test was conducted to benchmark the overall usability of a specific network management software. Based on the test data, the fuzzy method was applied to incorporate both the usability scores and uncertainties involved in the multiple components of the evaluation. Then, with Monte Carlo simulation procedures, confidence intervals were used to compare the reliabilities among the fuzzy approach and two typical conventional methods combining metrics based on percentages. RESULTS AND CONCLUSIONS: This case study showed that the fuzzy evaluation technique can be applied successfully for combining summative usability testing data to achieve an overall usability quality for the network software evaluated. Greater differences of confidence interval widths between the method of averaging equally percentage and weighted evaluation method, including the method of weighted percentage averages, verified the strength of the fuzzy method. PMID:28035942

Using a fuzzy comprehensive evaluation method to determine product usability: A test case.

PubMed

Zhou, Ronggang; Chan, Alan H S

2017-01-01

In order to take into account the inherent uncertainties during product usability evaluation, Zhou and Chan [1] proposed a comprehensive method of usability evaluation for products by combining the analytic hierarchy process (AHP) and fuzzy evaluation methods for synthesizing performance data and subjective response data. This method was designed to provide an integrated framework combining the inevitable vague judgments from the multiple stages of the product evaluation process. In order to illustrate the effectiveness of the model, this study used a summative usability test case to assess the application and strength of the general fuzzy usability framework. To test the proposed fuzzy usability evaluation framework [1], a standard summative usability test was conducted to benchmark the overall usability of a specific network management software. Based on the test data, the fuzzy method was applied to incorporate both the usability scores and uncertainties involved in the multiple components of the evaluation. Then, with Monte Carlo simulation procedures, confidence intervals were used to compare the reliabilities among the fuzzy approach and two typical conventional methods combining metrics based on percentages. This case study showed that the fuzzy evaluation technique can be applied successfully for combining summative usability testing data to achieve an overall usability quality for the network software evaluated. Greater differences of confidence interval widths between the method of averaging equally percentage and weighted evaluation method, including the method of weighted percentage averages, verified the strength of the fuzzy method.

[Study on building index system of risk assessment of post-marketing Chinese patent medicine based on AHP-fuzzy neural network].

PubMed

Li, Yuanyuan; Xie, Yanming; Fu, Yingkun

2011-10-01

Currently massive researches have been launched about the safety, efficiency and economy of post-marketing Chinese patent medicine (CPM) proprietary Chinese medicine, but it was lack of a comprehensive interpretation. Establishing the risk evaluation index system and risk assessment model of CPM is the key to solve drug safety problems and protect people's health. The clinical risk factors of CPM exist similarities with the Western medicine, can draw lessons from foreign experience, but also have itself multi-factor multivariate multi-level complex features. Drug safety risk assessment for the uncertainty and complexity, using analytic hierarchy process (AHP) to empower the index weights, AHP-based fuzzy neural network to build post-marketing CPM risk evaluation index system and risk assessment model and constantly improving the application of traditional Chinese medicine characteristic is accord with the road and feasible beneficial exploration.

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

PubMed

Li, Maozhong; Du, Yunai; Wang, Qiyue; Sun, Chunmeng; Ling, Xiang; Yu, Boyang; Tu, Jiasheng; Xiong, Yerong

2016-01-01

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

PubMed

Li, Maozhong; Du, Yunai; Wang, Qiyue; Sun, Chunmeng; Ling, Xiang; Yu, Boyang; Tu, Jiasheng; Xiong, Yerong

2016-04-01

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.

Multi-criteria analysis of potential recovery facilities in a reverse supply chain

NASA Astrophysics Data System (ADS)

Nukala, Satish; Gupta, Surendra M.

2005-11-01

Analytic Hierarchy Process (AHP) has been employed by researchers for solving multi-criteria analysis problems. However, AHP is often criticized for its unbalanced scale of judgments and failure to precisely handle the inherent uncertainty and vagueness in carrying out the pair-wise comparisons. With an objective to address these drawbacks, in this paper, we employ a fuzzy approach in selecting potential recovery facilities in the strategic planning of a reverse supply chain network that addresses the decision maker's level of confidence in the fuzzy assessments and his/her attitude towards risk. A numerical example is considered to illustrate the methodology.

An Application of Fuzzy AHP for Evaluating Course Website Quality

ERIC Educational Resources Information Center

Lin, Hsiu-Fen

2010-01-01

Although previous studies have identified various influences on course website effectiveness, the evaluation of the relative importance of these factors across different online learning experience groups has not been empirically determined. This study develops an evolution model that integrates triangular fuzzy numbers and analytic hierarchy…

MFAHP: A novel method on the performance evaluation of the industrial wireless networked control system

NASA Astrophysics Data System (ADS)

Wu, Linqin; Xu, Sheng; Jiang, Dezhi

2015-12-01

Industrial wireless networked control system has been widely used, and how to evaluate the performance of the wireless network is of great significance. In this paper, considering the shortcoming of the existing performance evaluation methods, a comprehensive performance evaluation method of networks multi-indexes fuzzy analytic hierarchy process (MFAHP) combined with the fuzzy mathematics and the traditional analytic hierarchy process (AHP) is presented. The method can overcome that the performance evaluation is not comprehensive and subjective. Experiments show that the method can reflect the network performance of real condition. It has direct guiding role on protocol selection, network cabling, and node setting, and can meet the requirements of different occasions by modifying the underlying parameters.

Project Delivery System Mode Decision Based on Uncertain AHP and Fuzzy Sets

NASA Astrophysics Data System (ADS)

Kaishan, Liu; Huimin, Li

2017-12-01

The project delivery system mode determines the contract pricing type, project management mode and the risk allocation among all participants. Different project delivery system modes have different characteristics and applicable scope. For the owners, the selection of the delivery mode is the key point to decide whether the project can achieve the expected benefits, it relates to the success or failure of project construction. Under the precondition of comprehensively considering the influence factors of the delivery mode, the model of project delivery system mode decision was set up on the basis of uncertain AHP and fuzzy sets, which can well consider the uncertainty and fuzziness when conducting the index evaluation and weight confirmation, so as to rapidly and effectively identify the most suitable delivery mode according to project characteristics. The effectiveness of the model has been verified via the actual case analysis in order to provide reference for the construction project delivery system mode.

Evaluation and Prediction of Water Resources Based on AHP

NASA Astrophysics Data System (ADS)

Li, Shuai; Sun, Anqi

2017-01-01

Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm. After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

Improving the Method of Roof Fall Susceptibility Assessment based on Fuzzy Approach

NASA Astrophysics Data System (ADS)

Ghasemi, Ebrahim; Ataei, Mohammad; Shahriar, Kourosh

2017-03-01

Retreat mining is always accompanied by a great amount of accidents and most of them are due to roof fall. Therefore, development of methodologies to evaluate the roof fall susceptibility (RFS) seems essential. Ghasemi et al. (2012) proposed a systematic methodology to assess the roof fall risk during retreat mining based on risk assessment classic approach. The main defect of this method is ignorance of subjective uncertainties due to linguistic input value of some factors, low resolution, fixed weighting, sharp class boundaries, etc. To remove this defection and improve the mentioned method, in this paper, a novel methodology is presented to assess the RFS using fuzzy approach. The application of fuzzy approach provides an effective tool to handle the subjective uncertainties. Furthermore, fuzzy analytical hierarchy process (AHP) is used to structure and prioritize various risk factors and sub-factors during development of this method. This methodology is applied to identify the susceptibility of roof fall occurrence in main panel of Tabas Central Mine (TCM), Iran. The results indicate that this methodology is effective and efficient in assessing RFS.

Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model

PubMed Central

Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

2015-01-01

Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results. PMID:25689998

Dynamic assessment of water quality based on a variable fuzzy pattern recognition model.

PubMed

Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

2015-02-16

Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.

a New Multi-Criteria Evaluation Model Based on the Combination of Non-Additive Fuzzy Ahp, Choquet Integral and Sugeno λ-MEASURE

NASA Astrophysics Data System (ADS)

Nadi, S.; Samiei, M.; Salari, H. R.; Karami, N.

2017-09-01

This paper proposes a new model for multi-criteria evaluation under uncertain condition. In this model we consider the interaction between criteria as one of the most challenging issues especially in the presence of uncertainty. In this case usual pairwise comparisons and weighted sum cannot be used to calculate the importance of criteria and to aggregate them. Our model is based on the combination of non-additive fuzzy linguistic preference relation AHP (FLPRAHP), Choquet integral and Sugeno λ-measure. The proposed model capture fuzzy preferences of users and fuzzy values of criteria and uses Sugeno λ -measure to determine the importance of criteria and their interaction. Then, integrating Choquet integral and FLPRAHP, all the interaction between criteria are taken in to account with least number of comparison and the final score for each alternative is determined. So we would model a comprehensive set of interactions between criteria that can lead us to more reliable result. An illustrative example presents the effectiveness and capability of the proposed model to evaluate different alternatives in a multi-criteria decision problem.

Operator performance evaluation using multi criteria decision making methods

NASA Astrophysics Data System (ADS)

Rani, Ruzanita Mat; Ismail, Wan Rosmanira; Razali, Siti Fatihah

2014-06-01

Operator performance evaluation is a very important operation in labor-intensive manufacturing industry because the company's productivity depends on the performance of its operators. The aims of operator performance evaluation are to give feedback to operators on their performance, to increase company's productivity and to identify strengths and weaknesses of each operator. In this paper, six multi criteria decision making methods; Analytical Hierarchy Process (AHP), fuzzy AHP (FAHP), ELECTRE, PROMETHEE II, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) are used to evaluate the operators' performance and to rank the operators. The performance evaluation is based on six main criteria; competency, experience and skill, teamwork and time punctuality, personal characteristics, capability and outcome. The study was conducted at one of the SME food manufacturing companies in Selangor. From the study, it is found that AHP and FAHP yielded the "outcome" criteria as the most important criteria. The results of operator performance evaluation showed that the same operator is ranked the first using all six methods.

Fuzzy fault tree assessment based on improved AHP for fire and explosion accidents for steel oil storage tanks.

PubMed

Shi, Lei; Shuai, Jian; Xu, Kui

2014-08-15

Fire and explosion accidents of steel oil storage tanks (FEASOST) occur occasionally during the petroleum and chemical industry production and storage processes and often have devastating impact on lives, the environment and property. To contribute towards the development of a quantitative approach for assessing the occurrence probability of FEASOST, a fault tree of FEASOST is constructed that identifies various potential causes. Traditional fault tree analysis (FTA) can achieve quantitative evaluation if the failure data of all of the basic events (BEs) are available, which is almost impossible due to the lack of detailed data, as well as other uncertainties. This paper makes an attempt to perform FTA of FEASOST by a hybrid application between an expert elicitation based improved analysis hierarchy process (AHP) and fuzzy set theory, and the occurrence possibility of FEASOST is estimated for an oil depot in China. A comparison between statistical data and calculated data using fuzzy fault tree analysis (FFTA) based on traditional and improved AHP is also made. Sensitivity and importance analysis has been performed to identify the most crucial BEs leading to FEASOST that will provide insights into how managers should focus effective mitigation. Copyright © 2014 Elsevier B.V. All rights reserved.

Challenging Aerospace Problems for Intelligent Systems

DTIC Science & Technology

2003-06-01

importance of each rule. Techniques such as logarithmic regression or Saaty’s AHP may be employed to apply the weights on to the fuzzy rules. 15-9 Given u...at which designs could be evaluated. This implies that modeling techniques such as neural networks, fuzzy systems and so on can play an important role...failure conditions [4-6]. These approaches apply techniques, such as neural networks, fuzzy logic, and parameter identification, to improve aircraft

Landslide potential zonation in Baleghlu watershed (NW Iran) using AHP Fuzzy method

NASA Astrophysics Data System (ADS)

Jananeh, Keristineh; Roostai, Shahram

2017-04-01

Landslides and slope instabilities are among the important natural hazards, which cause human and financial casualties and loss of economic resources every year. These hazards mostly occur in natural slopes or those manipulated by human. Zonation of areas with regard to landslide potential is one of the means to identify areas prone to produce landslide and so, to conduct plannings and management based on the prepared zonation maps in order to reduce the casualties. This contribution investigates on the landslide potential zonation within the Baleghlu watershed. This watershed is located in the southeast of Sabalan volcano (NW Iran) within the longitudes of 47° 48` and 48° 12` E and northern latitudes of 37° 51` and 38° 16` N. Its main river is Baleghlu, which is later connected to the Arax river through the Qarasu and Dareh Roud rivers, and is finally terminated to the Caspian sea. The method of investigation is Fuzzy AHP in the GIS environment. First, the main factors including the slope and its direction, geology, soil, climate, distance from the road and river and land usage were investigated and then, after preparing data layers based on the above-mentioned parameters and giving weights to them in the GIS environment, the landslide potential map was prepared by Fuzzy AHP method. It was revealed that the slope factor with the value of 0.3882 has the highest weight, while the land usage factor with the value of 0.0287 has the lowest weight. According to the final zonation map of the landslide potential, the watershed was divided into 5 classes, ranging from very high potential class to the very low potential. The obtained results showed that the largest part of the watershed (32.21%) has low landslide potential, while about 13.5% of it has very high potential. Areas with very high and high landslide potential (327.39 km2 area) are mainly located in the northwest of the watershed, with some small areas distributed in the south and east, while areas with very low and low potential (504.06 km2) are mainly found in the central to northwestern and southern parts of the watershed.

A new state evaluation method of oil pump unit based on AHP and FCE

NASA Astrophysics Data System (ADS)

Lin, Yang; Liang, Wei; Qiu, Zeyang; Zhang, Meng; Lu, Wenqing

2017-05-01

In order to make an accurate state evaluation of oil pump unit, a comprehensive evaluation index should be established. A multi-parameters state evaluation method of oil pump unit is proposed in this paper. The oil pump unit is analyzed by Failure Mode and Effect Analysis (FMEA), so evaluation index can be obtained based on FMEA conclusions. The weights of different parameters in evaluation index are discussed using Analytic Hierarchy Process (AHP) with expert experience. According to the evaluation index and the weight of each parameter, the state evaluation is carried out by Fuzzy Comprehensive Evaluation (FCE) and the state is divided into five levels depending on status value, which is inspired by human body health. In order to verify the effectiveness and feasibility of the proposed method, a state evaluation of oil pump used in a pump station is taken as an example.

A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

NASA Astrophysics Data System (ADS)

Osezua Aikhuele, Daniel; Mohd Turan, Faiz

2016-02-01

In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

Army Program Value Added Analysis 90-97 (VAA 90-97)

DTIC Science & Technology

1991-08-01

affordability or duplication of capability. The AHP process appears to hold the greatest possibilities in this regard. 1-11. OTHER KEY FINDINGS a. The...to provide the logical skeleton in which to build an alternative’s effectiveness value. The analytical hierarchy process ( AHP ) is particularly...likely to be, at first cut, very fuzzy . Thus, the issue clarification step is inherently iterative. As the analyst gathers more and more information in

An innovative approach for determination of air quality health index.

PubMed

Gorai, Amit Kumar; Kanchan; Upadhyay, Abhishek; Tuluri, Francis; Goyal, Pramila; Tchounwou, Paul B

2015-11-15

Fuzzy-analytical hierarchical process (F-AHP) can be extended to determine fuzzy air quality health index (FAQHI) for deducing health risk associated with local air pollution levels, and subjective parameters. The present work aims at determining FAQHI by considering five air pollutant parameters (SO2, NO2, O3, CO, and PM10) and three subjective parameters (population sensitivity, population density and location sensitivity). Each of the individual pollutants has varying impacts. Hence the combined health effects associated with the pollutants were estimated by aggregating the pollutants with different weights. Global weights for each evaluation alternatives were determined using fuzzy-AHP method. The developed model was applied to determine FAQHI in Howrah City, India from daily-observed concentrations of air pollutants over the three-year period between 2009 and 2011. The FAQHI values obtained through this method in Howrah City range from 1 to 3. Since the permissible value of FAQHI (as calculated for NAAQS) for residential areas is 1.78, higher index values are of public health concern to the exposed individuals. During the period of study, the observed FAQHI values were found to be higher than 1.78 in most of the day in the months of January to March, and October to December. However, the index values were below the recommended limit during rest of the months. In conclusion, FAQHI in Howrah city was above permissible limit in winter months and within acceptable values in summer and rainy months. Diurnal variations of FAQHI showed a similar trend during the three-year period of assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

Performance evaluation method of electric energy data acquire system based on combination of subjective and objective weights

NASA Astrophysics Data System (ADS)

Gao, Chen; Ding, Zhongan; Deng, Bofa; Yan, Shengteng

2017-10-01

According to the characteristics of electric energy data acquire system (EEDAS), considering the availability of each index data and the connection between the index integrity, establishing the performance evaluation index system of electric energy data acquire system from three aspects as master station system, communication channel, terminal equipment. To determine the comprehensive weight of each index based on triangular fuzzy number analytic hierarchy process with entropy weight method, and both subjective preference and objective attribute are taken into consideration, thus realize the performance comprehensive evaluation more reasonable and reliable. Example analysis shows that, by combination with analytic hierarchy process (AHP) and triangle fuzzy numbers (TFN) to establish comprehensive index evaluation system based on entropy method, the evaluation results not only convenient and practical, but also more objective and accurate.

RFM-based eco-efficiency analysis using Takagi-Sugeno fuzzy and AHP approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen Ruiyang

2009-04-15

Eco-design is crucial to take environmental aspects into account in the phases of design. Few literature review that green product must meet market value. The development of models to predict market value is thus very useful because it can provide early eco-efficiency to the eco-design. For the eco-design engineer, when he tries to solve a customer feedback problem, he usually faces the eco-efficiency. There are, however, often other types of fuzziness uncertainty present, which are related to the quantity of eco-design conditions. In this paper, it is derived that analysis of eco-efficiency can be identified by using the RFM valuemore » for quantifying eco-design with Takagi-Sugeno fuzzy system on customer feedback problem. It clusters eco-efficiency into segments according to green product usages value expressed in terms of weighted RFM. This experiment examined the weighted RFM effect of overall average normalized, AHP and non-weighted for F1 metric. The experimental results show that the proposed methodology indeed can yield identification of higher quality.« less

Sensory evaluation based fuzzy AHP approach for material selection in customized garment design and development process

NASA Astrophysics Data System (ADS)

Hong, Y.; Curteza, A.; Zeng, X.; Bruniaux, P.; Chen, Y.

2016-06-01

Material selection is the most difficult section in the customized garment product design and development process. This study aims to create a hierarchical framework for material selection. The analytic hierarchy process and fuzzy sets theories have been applied to mindshare the diverse requirements from the customer and inherent interaction/interdependencies among these requirements. Sensory evaluation ensures a quick and effective selection without complex laboratory test such as KES and FAST, using the professional knowledge of the designers. A real empirical application for the physically disabled people is carried out to demonstrate the proposed method. Both the theoretical and practical background of this paper have indicated the fuzzy analytical network process can capture expert's knowledge existing in the form of incomplete, ambiguous and vague information for the mutual influence on attribute and criteria of the material selection.

Combining geographic information system, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Tsihrintzis, Vassilios A.; Voudrias, Evangelos; Petalas, Christos; Stravodimos, George

2007-01-01

This study presents a methodology for siting municipal solid waste landfills, coupling geographic information systems (GIS), fuzzy logic, and multicriteria evaluation techniques. Both exclusionary and non-exclusionary criteria are used. Factors, i.e., non-exclusionary criteria, are divided in two distinct groups which do not have the same level of trade off. The first group comprises factors related to the physical environment, which cannot be expressed in terms of monetary cost and, therefore, they do not easily trade off. The second group includes those factors related to human activities, i.e., socioeconomic factors, which can be expressed as financial cost, thus showing a high level of trade off. GIS are used for geographic data acquisition and processing. The analytical hierarchy process (AHP) is the multicriteria evaluation technique used, enhanced with fuzzy factor standardization. Besides assigning weights to factors through the AHP, control over the level of risk and trade off in the siting process is achieved through a second set of weights, i.e., order weights, applied to factors in each factor group, on a pixel-by-pixel basis, thus taking into account the local site characteristics. The method has been applied to Evros prefecture (NE Greece), an area of approximately 4,000 km2. The siting methodology results in two intermediate suitability maps, one related to environmental and the other to socioeconomic criteria. Combination of the two intermediate maps results in the final composite suitability map for landfill siting.

An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

PubMed Central

Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches. PMID:25574490

An adaptive handover prediction scheme for seamless mobility based wireless networks.

PubMed

Sadiq, Ali Safa; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.

[Assessment on ecological security spatial differences of west areas of Liaohe River based on GIS].

PubMed

Wang, Geng; Wu, Wei

2005-09-01

Ecological security assessment and early warning research have spatiality; non-linearity; randomicity, it is needed to deal with much spatial information. Spatial analysis and data management are advantages of GIS, it can define distribution trend and spatial relations of environmental factors, and show ecological security pattern graphically. The paper discusses the method of ecological security spatial differences of west areas of Liaohe River based on GIS and ecosystem non-health. First, studying on pressure-state-response (P-S-R) assessment indicators system, investigating in person and gathering information; Second, digitizing the river, applying fuzzy AHP to put weight, quantizing and calculating by fuzzy comparing; Last, establishing grid data-base; expounding spatial differences of ecological security by GIS Interpolate and Assembly.

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

NASA Astrophysics Data System (ADS)

Zaiwani, B. E.; Zarlis, M.; Efendi, S.

2018-03-01

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

Study on quantitative risk assessment model of the third party damage for natural gas pipelines based on fuzzy comprehensive assessment

NASA Astrophysics Data System (ADS)

Qiu, Zeyang; Liang, Wei; Wang, Xue; Lin, Yang; Zhang, Meng

2017-05-01

As an important part of national energy supply system, transmission pipelines for natural gas are possible to cause serious environmental pollution, life and property loss in case of accident. The third party damage is one of the most significant causes for natural gas pipeline system accidents, and it is very important to establish an effective quantitative risk assessment model of the third party damage for reducing the number of gas pipelines operation accidents. Against the third party damage accident has the characteristics such as diversity, complexity and uncertainty, this paper establishes a quantitative risk assessment model of the third party damage based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE). Firstly, risk sources of third party damage should be identified exactly, and the weight of factors could be determined via improved AHP, finally the importance of each factor is calculated by fuzzy comprehensive evaluation model. The results show that the quantitative risk assessment model is suitable for the third party damage of natural gas pipelines and improvement measures could be put forward to avoid accidents based on the importance of each factor.

Health Information Security: A Case Study of Three Selected Medical Centers in Iran

PubMed Central

Hajrahimi, Nafiseh; Dehaghani, Sayed Mehdi Hejazi; Sheikhtaheri, Abbas

2013-01-01

Health Information System (HIS) is considered a unique factor in improving the quality of health care activities and cost reduction, but today with the development of information technology and use of internet and computer networks, patients’ electronic records and health information systems have become a source for hackers. Methods This study aims at checking health information security of three selected medical centers in Iran using AHP fuzzy and TOPSIS compound model. To achieve that security measures were identified, based on the research literature and decision making matrix using experts’ points of view. Results and discussion Among the 27 indicators, seven indicators were selected as effective indicators and Fuzzy AHP technique was used to determine the importance of security indicators. Based on the comparisons made between the three selected medical centers to assess the security of health information, it is concluded that Chamran hospital has the most acceptable level of security and attention in three indicators of “verification and system design, user access management, access control system”, Al Zahra Hospital in two indicators of “access management and network access control” and Amin Hospital in “equipment safety and system design”. In terms of information security, Chamran Hospital ranked first, Al-Zahra Hospital ranked second and Al- Zahra hospital has the third place. PMID:23572861

Fuzzy multicriteria disposal method and site selection for municipal solid waste.

PubMed

Ekmekçioğlu, Mehmet; Kaya, Tolga; Kahraman, Cengiz

2010-01-01

The use of fuzzy multiple criteria analysis (MCA) in solid waste management has the advantage of rendering subjective and implicit decision making more objective and analytical, with its ability to accommodate both quantitative and qualitative data. In this paper a modified fuzzy TOPSIS methodology is proposed for the selection of appropriate disposal method and site for municipal solid waste (MSW). Our method is superior to existing methods since it has capability of representing vague qualitative data and presenting all possible results with different degrees of membership. In the first stage of the proposed methodology, a set of criteria of cost, reliability, feasibility, pollution and emission levels, waste and energy recovery is optimized to determine the best MSW disposal method. Landfilling, composting, conventional incineration, and refuse-derived fuel (RDF) combustion are the alternatives considered. The weights of the selection criteria are determined by fuzzy pairwise comparison matrices of Analytic Hierarchy Process (AHP). It is found that RDF combustion is the best disposal method alternative for Istanbul. In the second stage, the same methodology is used to determine the optimum RDF combustion plant location using adjacent land use, climate, road access and cost as the criteria. The results of this study illustrate the importance of the weights on the various factors in deciding the optimized location, with the best site located in Catalca. A sensitivity analysis is also conducted to monitor how sensitive our model is to changes in the various criteria weights. 2010 Elsevier Ltd. All rights reserved.

Hospital site selection using fuzzy AHP and its derivatives.

PubMed

Vahidnia, Mohammad H; Alesheikh, Ali A; Alimohammadi, Abbas

2009-07-01

Environmental managers are commonly faced with sophisticated decisions, such as choosing the location of a new facility subject to multiple conflicting criteria. This paper considers the specific problem of creating a well-distributed network of hospitals that delivers its services to the target population with minimal time, pollution and cost. We develop a Multi-Criteria Decision Analysis process that combines Geographical Information System (GIS) analysis with the Fuzzy Analytical Hierarchy Process (FAHP), and use this process to determine the optimum site for a new hospital in the Tehran urban area. The GIS was used to calculate and classify governing criteria, while FAHP was used to evaluate the decision factors and their impacts on alternative sites. Three methods were used to estimate the total weights and priorities of the candidate sites: fuzzy extent analysis, center-of-area defuzzification, and the alpha-cut method. The three methods yield identical priorities for the five alternatives considered. Fuzzy extent analysis provides less discriminating power, but is simpler to implement and compute than the other two methods. The alpha-cut method is more complicated, but integrates the uncertainty and overall attitude of the decision-maker. The usefulness of the new hospital site is evaluated by computing an accessibility index for each pixel in the GIS, defined as the ratio of population density to travel time. With the addition of a new hospital at the optimum site, this index improved over about 6.5 percent of the geographical area.

Evaluation for the ecological quality status of coastal waters in East China Sea using fuzzy integrated assessment method.

PubMed

Wu, H Y; Chen, K L; Chen, Z H; Chen, Q H; Qiu, Y P; Wu, J C; Zhang, J F

2012-03-01

This research presented an evaluation for the ecological quality status (EcoQS) of three semi-enclosed coastal areas using fuzzy integrated assessment method (FIAM). With this method, the hierarchy structure was clarified by an index system of 11 indicators selected from biotic elements and physicochemical elements, and the weight vector of index system was calculated with Delphi-Analytic Hierarchy Process (AHP) procedure. Then, the FIAM was used to achieve an EcoQS assessment. As a result of assessment, most of the sampling stations demonstrated a clear gradient in EcoQS, ranging from high to poor status. Among the four statuses, high and good, owning a ratio of 55.9% and 26.5%, respectively, were two dominant statuses for three bays, especially for Sansha Bay and Luoyuan Bay. The assessment results were found consistent with the pressure information and parameters obtained at most stations. In addition, the sources of uncertainty in classification of EcoQS were also discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Decision Support Model for Municipal Solid Waste Management at Department of Defense Installations.

DTIC Science & Technology

1995-12-01

Huang uses "Grey Dynamic Programming for Waste Management Planning Under Uncertainty." Fuzzy Dynamic Programming (FDP) is usually designed to...and Composting Programs. Washington: Island Press, 1991. Junio, D.F. Development of an Analytical Hierarchy Process ( AHP ) Model for Siting of

Macro and micro geo-spatial environment consideration for landfill site selection in Sharjah, United Arab Emirates.

PubMed

Al-Ruzouq, Rami; Shanableh, Abdallah; Omar, Maher; Al-Khayyat, Ghadeer

2018-02-17

Waste management involves various procedures and resources for proper handling of waste materials in compliance with health codes and environmental regulations. Landfills are one of the oldest, most convenient, and cheapest methods to deposit waste. However, landfill utilization involves social, environmental, geotechnical, cost, and restrictive regulation considerations. For instance, landfills are considered a source of hazardous air pollutants that can cause health and environmental problems related to landfill gas and non-methanic organic compounds. The increasing number of sensors and availability of remotely sensed images along with rapid development of spatial technology are helping with effective landfill site selection. The present study used fuzzy membership and the analytical hierarchy process (AHP) in a geo-spatial environment for landfill site selection in the city of Sharjah, United Arab Emirates. Macro- and micro-level factors were considered; the macro-level contained social and economic factors, while the micro-level accounted for geo-environmental factors. The weighted spatial layers were combined to generate landfill suitability and overall suitability index maps. Sensitivity analysis was then carried out to rectify initial theoretical weights. The results showed that 30.25% of the study area had a high suitability index for landfill sites in the Sharjah, and the most suitable site was selected based on weighted factors. The developed fuzzy-AHP methodology can be applied in neighboring regions with similar geo-natural conditions.

Improvements to IBMPIP.

DTIC Science & Technology

1984-03-01

cosines can change, some- times drastically. ’Those changes are taking-place along a temporary path which is " fuzzy " at first. It is fatal to the program...for this " fuzziness " to be allowed to influence the endpoint velocity compo- nents (located at "new"). Zherefore, the computation of the velocity...8217,CEZLX,XTEIIP .CLD,YNES,JELYETS?.IP,YCLD,ZNE’J,ZELZ, 1ZTslip ZOLC CCflMO§ /AECS/VECE3.LC,,NiI2.0ZE’,TPvo: CC2,461- /A E-4/ AG1 , AHP 1_1AI I , AJ 1 ,AJZ2

The Urban Intensive Land-use Evaluation in Xi’an, Based on Fuzzy Comprehensive Evaluation

NASA Astrophysics Data System (ADS)

Shi, Ru; Kang, Zhiyuan

2018-01-01

The intensive land-use is the basis of urban “stock optimization”, and scientific and reasonable evaluation is the important content of the land-intensive utilization. In this paper, through the survey of Xi’an urban land-use condition, we construct the suitable evaluation index system of Xi’an’ intensive land-use, by using Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) of combination. And through the analysis of the influencing factors of land-intensive utilization, we provide a reference for the future development direction.

Determining Asset Criticality for Cyber Defense

DTIC Science & Technology

2011-09-23

sciences area that may be applied to our situation. In particular, Analytic Hierarchy Process ( AHP ) [20] and Hierarchical TOPSIS [21] [22] are some examples...34 Mathematical and Computer Modeling, vol. 45, no. 7-8, pp. 801-813, 2007. 33 [22] Jia-Wen Wang, Ching-Hsue Cheng, and Kun-Cheng Huang, " Fuzzy

Study on site selection of cold chain logistics in northwest territories

NASA Astrophysics Data System (ADS)

Liu, Yubin; Ren, Zongwei

2017-08-01

In this research, we mainly studied the Site selection problem of cold chain logistics in northwest of China. In the first place, we counted the demands of cold chain products in northwest territories, and then classified it into the Site selection problem in five provinces in northwest territories(Xinjiang, Qinghai, Gansu, Ningxia, Shanxi); Next, we used the Center of gravity Method to select initial location; Finally, we established the location of distribution by using Analytic Hierarchy Process (AHP)and fuzzy comprehensive evaluation method. Comparing with the traditional method, this method not only considered the cost of transportation and distance, but also deliberated the physical condition, social environment and economics condition which associated with Site selection problem.

Instability risk assessment of construction waste pile slope based on fuzzy entropy

NASA Astrophysics Data System (ADS)

Ma, Yong; Xing, Huige; Yang, Mao; Nie, Tingting

2018-05-01

Considering the nature and characteristics of construction waste piles, this paper analyzed the factors affecting the stability of the slope of construction waste piles, and established the system of the assessment indexes for the slope failure risks of construction waste piles. Based on the basic principles and methods of fuzzy mathematics, the factor set and the remark set were established. The membership grade of continuous factor indexes is determined using the "ridge row distribution" function, while that for the discrete factor indexes was determined by the Delphi Method. For the weight of factors, the subjective weight was determined by the Analytic Hierarchy Process (AHP) and objective weight by the entropy weight method. And the distance function was introduced to determine the combination coefficient. This paper established a fuzzy comprehensive assessment model of slope failure risks of construction waste piles, and assessed pile slopes in the two dimensions of hazard and vulnerability. The root mean square of the hazard assessment result and vulnerability assessment result was the final assessment result. The paper then used a certain construction waste pile slope as the example for analysis, assessed the risks of the four stages of a landfill, verified the assessment model and analyzed the slope's failure risks and preventive measures against a slide.

An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules.

PubMed

Topuz, Emel; van Gestel, Cornelis A M

2016-01-01

The usage of Engineered Nanoparticles (ENPs) in consumer products is relatively new and there is a need to conduct environmental risk assessment (ERA) to evaluate their impacts on the environment. However, alternative approaches are required for ERA of ENPs because of the huge gap in data and knowledge compared to conventional pollutants and their unique properties that make it difficult to apply existing approaches. This study aims to propose an ERA approach for ENPs by integrating Analytical Hierarchy Process (AHP) and fuzzy inference models which provide a systematic evaluation of risk factors and reducing uncertainty about the data and information, respectively. Risk is assumed to be the combination of occurrence likelihood, exposure potential and toxic effects in the environment. A hierarchy was established to evaluate the sub factors of these components. Evaluation was made with fuzzy numbers to reduce uncertainty and incorporate the expert judgements. Overall score of each component was combined with fuzzy inference rules by using expert judgements. Proposed approach reports the risk class and its membership degree such as Minor (0.7). Therefore, results are precise and helpful to determine the risk management strategies. Moreover, priority weights calculated by comparing the risk factors based on their importance for the risk enable users to understand which factor is effective on the risk. Proposed approach was applied for Ag (two nanoparticles with different coating) and TiO2 nanoparticles for different case studies. Results verified the proposed benefits of the approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ekmekcioglu, Mehmet, E-mail: meceng3584@yahoo.co; Kaya, Tolga; Kahraman, Cengiz

The use of fuzzy multiple criteria analysis (MCA) in solid waste management has the advantage of rendering subjective and implicit decision making more objective and analytical, with its ability to accommodate both quantitative and qualitative data. In this paper a modified fuzzy TOPSIS methodology is proposed for the selection of appropriate disposal method and site for municipal solid waste (MSW). Our method is superior to existing methods since it has capability of representing vague qualitative data and presenting all possible results with different degrees of membership. In the first stage of the proposed methodology, a set of criteria of cost,more » reliability, feasibility, pollution and emission levels, waste and energy recovery is optimized to determine the best MSW disposal method. Landfilling, composting, conventional incineration, and refuse-derived fuel (RDF) combustion are the alternatives considered. The weights of the selection criteria are determined by fuzzy pairwise comparison matrices of Analytic Hierarchy Process (AHP). It is found that RDF combustion is the best disposal method alternative for Istanbul. In the second stage, the same methodology is used to determine the optimum RDF combustion plant location using adjacent land use, climate, road access and cost as the criteria. The results of this study illustrate the importance of the weights on the various factors in deciding the optimized location, with the best site located in Catalca. A sensitivity analysis is also conducted to monitor how sensitive our model is to changes in the various criteria weights.« less

The performance evaluation model of mining project founded on the weight optimization entropy value method

NASA Astrophysics Data System (ADS)

Mao, Chao; Chen, Shou

2017-01-01

According to the traditional entropy value method still have low evaluation accuracy when evaluating the performance of mining projects, a performance evaluation model of mineral project founded on improved entropy is proposed. First establish a new weight assignment model founded on compatible matrix analysis of analytic hierarchy process (AHP) and entropy value method, when the compatibility matrix analysis to achieve consistency requirements, if it has differences between subjective weights and objective weights, moderately adjust both proportions, then on this basis, the fuzzy evaluation matrix for performance evaluation. The simulation experiments show that, compared with traditional entropy and compatible matrix analysis method, the proposed performance evaluation model of mining project based on improved entropy value method has higher accuracy assessment.

National hydrogen technology competitiveness analysis with an integrated fuzzy AHP and TOPSIS approaches: In case of hydrogen production and storage technologies

NASA Astrophysics Data System (ADS)

Lee, Seongkon; Mogi, Gento

2017-02-01

The demand of fossil fuels, including oil, gas, and coal has been increasing with the rapid development of developing countries such as China and India. U.S., Japan, EU, and Korea have been making efforts to transfer to low carbon and green growth economics for sustainable development. And they also have been measuring to cope with climate change and the depletion of conventional fuels. Advanced nations implemented strategic energy technology development plans to lead the future energy market. Strategic energy technology development is crucial alternative to address the energy issues. This paper analyze the relative competitiveness of hydrogen energy technologies in case of hydrogen production and storage technologies from 2006 to 2010. Hydrogen energy technology is environmentally clean technology comparing with the previous conventional energy technologies and will play a key role to solve the greenhouse gas effect. Leading nations have increasingly focused on hydrogen technology R&D. This research is carried out the relative competitiveness of hydrogen energy technologies employed by an integrated fuzzy analytic hierarchy process (Fuzzy AHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches. We make four criteria, accounting for technological status, R&D budget, R&D human resource, and hydrogen infra. This research can be used as fundamental data for implementing national hydrogen energy R&D planning for energy policy-makers.

Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

PubMed

Yazdi, Mohammad; Korhan, Orhan; Daneshvar, Sahand

2018-05-09

This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event. To find the probability of the top event (TE), all probabilities of the basic events (BEs) should be available when the FTA is drawn. In this case, employing expert judgment can be used as an alternative to failure data in an awkward situation. The fuzzy analytical hierarchy process as a standard technique is used to give a specific weight to each expert, and fuzzy set theory is engaged for aggregating expert opinion. In this regard, the probability of BEs will be computed and, consequently, the probability of the TE obtained using Boolean algebra. Additionally, to reduce the probability of the TE in terms of three parameters (safety consequences, cost and benefit), the importance measurement technique and modified TOPSIS was employed. The effectiveness of the proposed approach is demonstrated with a real-life case study.

Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference.

PubMed

Xiao, Yangfan; Yi, Shanzhen; Tang, Zhongqian

2017-12-01

Flood is the most common natural hazard in the world and has caused serious loss of life and property. Assessment of flood prone areas is of great importance for watershed management and reduction of potential loss of life and property. In this study, a framework of multi-criteria analysis (MCA) incorporating geographic information system (GIS), fuzzy analytic hierarchy process (AHP) and spatial ordered weighted averaging (OWA) method was developed for flood hazard assessment. The factors associated with geographical, hydrological and flood-resistant characteristics of the basin were selected as evaluation criteria. The relative importance of the criteria was estimated through fuzzy AHP method. The OWA method was utilized to analyze the effects of different risk attitudes of the decision maker on the assessment result. The spatial ordered weighted averaging method with spatially variable risk preference was implemented in the GIS environment to integrate the criteria. The advantage of the proposed method is that it has considered spatial heterogeneity in assigning risk preference in the decision-making process. The presented methodology has been applied to the area including Hanyang, Caidian and Hannan of Wuhan, China, where flood events occur frequently. The outcome of flood hazard distribution presents a tendency of high risk towards populated and developed areas, especially the northeast part of Hanyang city, which has suffered frequent floods in history. The result indicates where the enhancement projects should be carried out first under the condition of limited resources. Finally, sensitivity of the criteria weights was analyzed to measure the stability of results with respect to the variation of the criteria weights. The flood hazard assessment method presented in this paper is adaptable for hazard assessment of a similar basin, which is of great significance to establish counterplan to mitigate life and property losses. Copyright © 2017 Elsevier B.V. All rights reserved.

A Fuzzy-Based Decision Support Model for Selecting the Best Dialyser Flux in Haemodialysis.

PubMed

Oztürk, Necla; Tozan, Hakan

2015-01-01

Decision making is an important procedure for every organization. The procedure is particularly challenging for complicated multi-criteria problems. Selection of dialyser flux is one of the decisions routinely made for haemodialysis treatment provided for chronic kidney failure patients. This study provides a decision support model for selecting the best dialyser flux between high-flux and low-flux dialyser alternatives. The preferences of decision makers were collected via a questionnaire. A total of 45 questionnaires filled by dialysis physicians and nephrologists were assessed. A hybrid fuzzy-based decision support software that enables the use of Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Analytic Network Process (ANP), and Fuzzy Analytic Network Process (FANP) was used to evaluate the flux selection model. In conclusion, the results showed that a high-flux dialyser is the best. option for haemodialysis treatment.

Evaluating energy saving system of data centers based on AHP and fuzzy comprehensive evaluation model

NASA Astrophysics Data System (ADS)

Jiang, Yingni

2018-03-01

Due to the high energy consumption of communication, energy saving of data centers must be enforced. But the lack of evaluation mechanisms has restrained the process on energy saving construction of data centers. In this paper, energy saving evaluation index system of data centers was constructed on the basis of clarifying the influence factors. Based on the evaluation index system, analytical hierarchy process was used to determine the weights of the evaluation indexes. Subsequently, a three-grade fuzzy comprehensive evaluation model was constructed to evaluate the energy saving system of data centers.

A method for grounding grid corrosion rate prediction

NASA Astrophysics Data System (ADS)

Han, Juan; Du, Jingyi

2017-06-01

Involved in a variety of factors, prediction of grounding grid corrosion complex, and uncertainty in the acquisition process, we propose a combination of EAHP (extended AHP) and fuzzy nearness degree of effective grounding grid corrosion rate prediction model. EAHP is used to establish judgment matrix and calculate the weight of each factors corrosion of grounding grid; different sample classification properties have different corrosion rate of contribution, and combining the principle of close to predict corrosion rate.The application result shows, the model can better capture data variation, thus to improve the validity of the model to get higher prediction precision.

Hierarchical modeling of professional skills in the field of castings manufacture engineering

NASA Astrophysics Data System (ADS)

Samuilă, V.; Soporan, V. F.; Conțiu, G.; Pădurețu, S.; Lehene, T. R.; Vescan, M. M.

2017-06-01

The paper presents a method of hierarchizing professional skills in the manufacturing of molded parts (castings) by using and adapting the FAHP algorithm (Fuzzy Analitical Hierarchy Process). Assessments are made regarding the peculiarities of the professional training process, specifying the activities to be carried out and the competences necessary for their development. The contribution of the design of the method extends to the design of the hierarchy system architecture, the linguistic determination of the importance of each characteristic, the construction of the fuzzy ordering matrices for each stage of the process, the determination of the share of the characteristics for each hierarchy step and establishing the hierarchy of the characteristics taking into account the influences of the others, grouped at the level of the steps and within the global matrix. The research carried out represents the support for generating an instrument of hierarchy of professional competencies that can be used in various professional and institutional contexts. Case study on the hierarchy of professional skills in the manufacturing of molded parts engineering. Keywords: Materials engineering, castings manufacture professional skills, hierarchy, AHP method, standard occupational curriculum.

A fuzzy model for achieving lean attributes for competitive advantages development using AHP-QFD-PROMETHEE

NASA Astrophysics Data System (ADS)

Roghanian, E.; Alipour, Mohammad

2014-06-01

Lean production has become an integral part of the manufacturing landscape as its link with superior performance and its ability to provide competitive advantage is well accepted among academics and practitioners. Lean production helps producers in overcoming the challenges organizations face through using powerful tools and enablers. However, most companies are faced with restricted resources such as financial and human resources, time, etc., in using these enablers, and are not capable of implementing all these techniques. Therefore, identifying and selecting the most appropriate and efficient tool can be a significant challenge for many companies. Hence, this literature seeks to combine competitive advantages, lean attributes, and lean enablers to determine the most appropriate enablers for improvement of lean attributes. Quality function deployment in fuzzy environment and house of quality matrix are implemented. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, for final ranking of lean enablers, a multi-criteria decision-making method (PROMETHEE) is adopted. Finally, a case study in automotive industry is presented to illustrate the implementation of the proposed methodology.

Fuzzy comprehensive evaluation of multiple environmental factors for swine building assessment and control.

PubMed

Xie, Qiuju; Ni, Ji-Qin; Su, Zhongbin

2017-10-15

In confined swine buildings, temperature, humidity, and air quality are all important for animal health and productivity. However, the current swine building environmental control is only based on temperature; and evaluation and control methods based on multiple environmental factors are needed. In this paper, fuzzy comprehensive evaluation (FCE) theory was adopted for multi-factor assessment of environmental quality in two commercial swine buildings using real measurement data. An assessment index system and membership functions were established; and predetermined weights were given using analytic hierarchy process (AHP) combined with knowledge of experts. The results show that multi-factors such as temperature, humidity, and concentrations of ammonia (NH 3 ), carbon dioxide (CO 2 ), and hydrogen sulfide (H 2 S) can be successfully integrated in FCE for swine building environment assessment. The FCE method has a high correlation coefficient of 0.737 compared with the method of single-factor evaluation (SFE). The FCE method can significantly increase the sensitivity and perform an effective and integrative assessment. It can be used as part of environmental controlling and warning systems for swine building environment management to improve swine production and welfare. Copyright © 2017 Elsevier B.V. All rights reserved.

An application of MC-SDSS for water supply management during a drought crisis.

PubMed

Jeihouni, Mehrdad; Toomanian, Ara; Alavipanah, Seyed Kazem; Shahabi, Mahmoud; Bazdar, Saba

2015-07-01

Climate change influences many countries' rainfall patterns and temperatures. In Iran, population growth has increased water demands. Tabriz is the capital of East Azerbaijan province, in northwestern Iran. A large proportion of the water required for this city is supplied from dams; thus, it is important to find alternatives to supply water for this city, which is the largest industrial city in northwestern Iran. In this paper, the groundwater quality was assessed using 70 wells in Tabriz Township. This work seeks to define the spatial distribution of groundwater quality parameters such as chloride, electrical conductivity (EC), pH, hardness, and sulfate using Geographic Information Systems (GIS) and geostatistics; map groundwater quality for drinking purposes employing multiple-criteria decision-making (MCDM), such as the Analytical Hierarchy Process (AHP) and fuzzy logic, in the study area; and develop an Spatial Decision Support System (SDSS) for managing a water crisis in the region. The map produced by the AHP is more accurate than the map produced using fuzzy logic because in the AHP, priorities were assigned to each parameter based on the weights given by water quality experts. The final map indicates that the groundwater quality increases from the north to the south and from the west to the east within the study area. During critical conditions, the groundwater quality maps and the presented SDSS core can be utilized by East Azerbaijan Regional Water Company to develop an SDSS to drill new wells or to select existing wells to supply drinking water to Tabriz City.

Weighting Criteria and Prioritizing of Heat stress indices in surface mining using a Delphi Technique and Fuzzy AHP-TOPSIS Method.

PubMed

Asghari, Mehdi; Nassiri, Parvin; Monazzam, Mohammad Reza; Golbabaei, Farideh; Arabalibeik, Hossein; Shamsipour, Aliakbar; Allahverdy, Armin

2017-01-01

Heat stress as a physical harmful agent can increase the risk of health and safety problems in different workplaces such as mining. Although there are different indices to assess the heat stress imposed on workers, choosing the best index for a specific workplace is so important. Since various criteria affect an index applicability, extracting the most effective ones and determining their weights help to prioritize the existing indices and select the optimal index. In order to achieve this aim, present study compared some heat stress indices using effective methods. The viewpoints of occupational health experts and the qualitative Delphi methods were used to extract the most important criteria. Then, the weights of 11 selected criteria were determined by Fuzzy Analytic Hierarchy Process. Finally, fuzzy TOPSIS technique was applied for choosing the most suitable heat stress index. According to result, simplicity, reliability, being low cost, and comprehensiveness were the most determinative criteria for a heat stress index. Based on these criteria and their weights, the existing indices were prioritized. Eventually, wet bulb glob temperature appropriated the first priority and it was proposed as an applicable index for evaluating the heat stress at outdoor hot environments such as surface mines. The use of these strong methods allows introducing the most simple, precise, and applicable tool for evaluation the heat stress in hot environments. It seems that WBGT acts as an appropriate index for assessing the heat stress in mining activities at outdoors.

An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

PubMed

Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

PubMed Central

Gundogar, Emin; Yılmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

Investigation of the relationship between drinking water quality based on content of inorganic components and landform classes using fuzzy AHP (case study: south of Firozabad, west of Fars province, Iran)

NASA Astrophysics Data System (ADS)

Mokarram, Marzieh; Sathyamoorthy, Dinesh

2016-10-01

In this study, the fuzzy analytic hierarchy process (AHP) is used to study the relationship between drinking water quality based on content of inorganic components and landform classes in the south of Firozabad, west of Fars province, Iran. For determination of drinking water quality based on content of inorganic components, parameters of calcium (Ca), chlorine (Cl), magnesium (Mg), thorium (TH), sodium (Na), electrical conductivity (EC), sulfate (SO4), and total dissolved solids (TDS) were used. It was found that 8.29 % of the study area has low water quality; 64.01 %, moderate; 23.33 %, high; and 4.38 %, very high. Areas with suitable drinking water quality based on content of inorganic components are located in parts of the south-eastern and south-western parts of the study area. The relationship between landform class and drinking water quality based on content of inorganic components shows that drinking water quality based on content of inorganic components is high in the stream, valleys, upland drainages, and local ridge classes, and low in the plain small and midslope classes. In fact we can predict water quality using extraction of landform classes from a digital elevation model (DEM) by the Topographic Position Index (TPI) method, so that streams, valleys, upland drainages, and local ridge classes have more water quality than the other classes. In the study we determined that without measurement of water sample characteristics, we can determine water quality by landform classes.

Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems

PubMed Central

Chang, Kuei-Hu; Chang, Yung-Chia; Chain, Kai; Chung, Hsiang-Yu

2016-01-01

The advancement of high technologies and the arrival of the information age have caused changes to the modern warfare. The military forces of many countries have replaced partially real training drills with training simulation systems to achieve combat readiness. However, considerable types of training simulation systems are used in military settings. In addition, differences in system set up time, functions, the environment, and the competency of system operators, as well as incomplete information have made it difficult to evaluate the performance of training simulation systems. To address the aforementioned problems, this study integrated analytic hierarchy process, soft set theory, and the fuzzy linguistic representation model to evaluate the performance of various training simulation systems. Furthermore, importance–performance analysis was adopted to examine the influence of saving costs and training safety of training simulation systems. The findings of this study are expected to facilitate applying military training simulation systems, avoiding wasting of resources (e.g., low utility and idle time), and providing data for subsequent applications and analysis. To verify the method proposed in this study, the numerical examples of the performance evaluation of training simulation systems were adopted and compared with the numerical results of an AHP and a novel AHP-based ranking technique. The results verified that not only could expert-provided questionnaire information be fully considered to lower the repetition rate of performance ranking, but a two-dimensional graph could also be used to help administrators allocate limited resources, thereby enhancing the investment benefits and training effectiveness of a training simulation system. PMID:27598390

Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems.

PubMed

Chang, Kuei-Hu; Chang, Yung-Chia; Chain, Kai; Chung, Hsiang-Yu

2016-01-01

The advancement of high technologies and the arrival of the information age have caused changes to the modern warfare. The military forces of many countries have replaced partially real training drills with training simulation systems to achieve combat readiness. However, considerable types of training simulation systems are used in military settings. In addition, differences in system set up time, functions, the environment, and the competency of system operators, as well as incomplete information have made it difficult to evaluate the performance of training simulation systems. To address the aforementioned problems, this study integrated analytic hierarchy process, soft set theory, and the fuzzy linguistic representation model to evaluate the performance of various training simulation systems. Furthermore, importance-performance analysis was adopted to examine the influence of saving costs and training safety of training simulation systems. The findings of this study are expected to facilitate applying military training simulation systems, avoiding wasting of resources (e.g., low utility and idle time), and providing data for subsequent applications and analysis. To verify the method proposed in this study, the numerical examples of the performance evaluation of training simulation systems were adopted and compared with the numerical results of an AHP and a novel AHP-based ranking technique. The results verified that not only could expert-provided questionnaire information be fully considered to lower the repetition rate of performance ranking, but a two-dimensional graph could also be used to help administrators allocate limited resources, thereby enhancing the investment benefits and training effectiveness of a training simulation system.

Exploring Several Methods of Groundwater Model Selection

NASA Astrophysics Data System (ADS)

Samani, Saeideh; Ye, Ming; Asghari Moghaddam, Asghar

2017-04-01

Selecting reliable models for simulating groundwater flow and solute transport is essential to groundwater resources management and protection. This work is to explore several model selection methods for avoiding over-complex and/or over-parameterized groundwater models. We consider six groundwater flow models with different numbers (6, 10, 10, 13, 13 and 15) of model parameters. These models represent alternative geological interpretations, recharge estimates, and boundary conditions at a study site in Iran. The models were developed with Model Muse, and calibrated against observations of hydraulic head using UCODE. Model selection was conducted by using the following four approaches: (1) Rank the models using their root mean square error (RMSE) obtained after UCODE-based model calibration, (2) Calculate model probability using GLUE method, (3) Evaluate model probability using model selection criteria (AIC, AICc, BIC, and KIC), and (4) Evaluate model weights using the Fuzzy Multi-Criteria-Decision-Making (MCDM) approach. MCDM is based on the fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance, which is to identify the ideal solution by a gradual expansion from the local to the global scale of model parameters. The KIC and MCDM methods are superior to other methods, as they consider not only the fit between observed and simulated data and the number of parameter, but also uncertainty in model parameters. Considering these factors can prevent from occurring over-complexity and over-parameterization, when selecting the appropriate groundwater flow models. These methods selected, as the best model, one with average complexity (10 parameters) and the best parameter estimation (model 3).

Modeling an internal gear pump

NASA Astrophysics Data System (ADS)

Chen, Zongbin; Xu, Rongwu; He, Lin; Liao, Jian

2018-05-01

Considering the nature and characteristics of construction waste piles, this paper analyzed the factors affecting the stability of the slope of construction waste piles, and established the system of the assessment indexes for the slope failure risks of construction waste piles. Based on the basic principles and methods of fuzzy mathematics, the factor set and the remark set were established. The membership grade of continuous factor indexes is determined using the "ridge row distribution" function, while that for the discrete factor indexes was determined by the Delphi Method. For the weight of factors, the subjective weight was determined by the Analytic Hierarchy Process (AHP) and objective weight by the entropy weight method. And the distance function was introduced to determine the combination coefficient. This paper established a fuzzy comprehensive assessment model of slope failure risks of construction waste piles, and assessed pile slopes in the two dimensions of hazard and vulnerability. The root mean square of the hazard assessment result and vulnerability assessment result was the final assessment result. The paper then used a certain construction waste pile slope as the example for analysis, assessed the risks of the four stages of a landfill, verified the assessment model and analyzed the slope's failure risks and preventive measures against a slide.

Environmental Risk Assessment System for Phosphogypsum Tailing Dams

PubMed Central

Sun, Xin; Tang, Xiaolong; Yi, Honghong; Li, Kai; Zhou, Lianbi; Xu, Xianmang

2013-01-01

This paper may be of particular interest to the readers as it provides a new environmental risk assessment system for phosphogypsum tailing dams. In this paper, we studied the phosphogypsum tailing dams which include characteristics of the pollution source, environmental risk characteristics and evaluation requirements to identify the applicable environmental risk assessment methods. Two analytical methods, that is, the analytic hierarchy process (AHP) and fuzzy logic, were used to handle the complexity of the environmental and nonquantitative data. Using our assessment method, different risk factors can be ranked according to their contributions to the environmental risk, thereby allowing the calculation of their relative priorities during decision making. Thus, environmental decision-makers can use this approach to develop alternative management strategies for proposed, ongoing, and completed PG tailing dams. PMID:24382947

Environmental risk assessment system for phosphogypsum tailing dams.

PubMed

Sun, Xin; Ning, Ping; Tang, Xiaolong; Yi, Honghong; Li, Kai; Zhou, Lianbi; Xu, Xianmang

2013-01-01

This paper may be of particular interest to the readers as it provides a new environmental risk assessment system for phosphogypsum tailing dams. In this paper, we studied the phosphogypsum tailing dams which include characteristics of the pollution source, environmental risk characteristics and evaluation requirements to identify the applicable environmental risk assessment methods. Two analytical methods, that is, the analytic hierarchy process (AHP) and fuzzy logic, were used to handle the complexity of the environmental and nonquantitative data. Using our assessment method, different risk factors can be ranked according to their contributions to the environmental risk, thereby allowing the calculation of their relative priorities during decision making. Thus, environmental decision-makers can use this approach to develop alternative management strategies for proposed, ongoing, and completed PG tailing dams.

[Environmental quality assessment of regional agro-ecosystem in Loess Plateau].

PubMed

Wang, Limei; Meng, Fanping; Zheng, Jiyong; Wang, Zhonglin

2004-03-01

Based on the detection and analysis of the contamination status of agro-ecosystem with apple-crops intercropping as the dominant cropping model in Loess Plateau, the individual factor and comprehensive environmental quality were assessed by multilevel fuzzy synthetic evaluation model, analytical hierarchy process(AHP), and improved standard weight deciding method. The results showed that the quality of soil, water and agricultural products was grade I, the social economical environmental quality was grade II, the ecological environmental quality was grade III, and the comprehensive environmental quality was grade I. The regional agro-ecosystem dominated by apple-crops intercropping was not the best model for the ecological benefits, but had the better social economical benefits.

Health information security: a case study of three selected medical centers in iran.

PubMed

Hajrahimi, Nafiseh; Dehaghani, Sayed Mehdi Hejazi; Sheikhtaheri, Abbas

2013-03-01

Health Information System (HIS) is considered a unique factor in improving the quality of health care activities and cost reduction, but today with the development of information technology and use of internet and computer networks, patients' electronic records and health information systems have become a source for hackers. This study aims at checking health information security of three selected medical centers in Iran using AHP fuzzy and TOPSIS compound model. To achieve that security measures were identified, based on the research literature and decision making matrix using experts' points of view. Among the 27 indicators, seven indicators were selected as effective indicators and Fuzzy AHP technique was used to determine the importance of security indicators. Based on the comparisons made between the three selected medical centers to assess the security of health information, it is concluded that Chamran hospital has the most acceptable level of security and attention in three indicators of "verification and system design, user access management, access control system", Al Zahra Hospital in two indicators of "access management and network access control" and Amin Hospital in "equipment safety and system design". In terms of information security, Chamran Hospital ranked first, Al-Zahra Hospital ranked second and Al- Zahra hospital has the third place.

Zoonotic cutaneous leishmaniasis in northeastern Iran: a GIS-based spatio-temporal multi-criteria decision-making approach.

PubMed

Mollalo, A; Khodabandehloo, E

2016-07-01

Zoonotic cutaneous leishmaniasis (ZCL) constitutes a serious public health problem in many parts of the world including Iran. This study was carried out to assess the risk of the disease in an endemic province by developing spatial environmentally based models in yearly intervals. To fill the gap of underestimated true burden of ZCL and short study period, analytical hierarchy process (AHP) and fuzzy AHP decision-making methods were used to determine the ZCL risk zones in a Geographic Information System platform. Generated risk maps showed that high-risk areas were predominantly located at the northern and northeastern parts in each of the three study years. Comparison of the generated risk maps with geocoded ZCL cases at the village level demonstrated that in both methods more than 90%, 70% and 80% of the cases occurred in high and very high risk areas for the years 2010, 2011, and 2012, respectively. Moreover, comparison of the risk categories with spatially averaged normalized difference vegetation index (NDVI) images and a digital elevation model of the study region indicated persistent strong negative relationships between these environmental variables and ZCL risk degrees. These findings identified more susceptible areas of ZCL and will help the monitoring of this zoonosis to be more targeted.

Planning and design of PGIS in Shanghai sub-civic center

NASA Astrophysics Data System (ADS)

Zhang, Baoyu; Tao, Yan; Gao, Fei

2011-10-01

To alleviate the road congestion caused by parking in urban CBD, Parking Guidance and Information System (PGIS) is paid more attention to many cities in China. It can provide effective parking information (such as the location and utilization of parking lots, the routes, the traffic situation around the parking lots) to drivers through many ways, so as to guide them to park successfully. In the paper, PGIS constructing in Shanghai Xujiahui area is taken as the background, methods and models about urban PGIS planning and design are discussed from the angle of traffic function. Fuzzy AHP is used to select parking lots which can be brought into PGIS. The principle and method of zoning guidance service range are established, the principle of information classification and guidance method of three levels are introduced. Finally, the detailed content of PGI signs is given.

Combination of uncertainty theories and decision-aiding methods for natural risk management in a context of imperfect information

NASA Astrophysics Data System (ADS)

Tacnet, Jean-Marc; Dupouy, Guillaume; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

2017-04-01

In mountain areas, natural phenomena such as snow avalanches, debris-flows and rock-falls, put people and objects at risk with sometimes dramatic consequences. Risk is classically considered as a combination of hazard, the combination of the intensity and frequency of the phenomenon, and vulnerability which corresponds to the consequences of the phenomenon on exposed people and material assets. Risk management consists in identifying the risk level as well as choosing the best strategies for risk prevention, i.e. mitigation. In the context of natural phenomena in mountainous areas, technical and scientific knowledge is often lacking. Risk management decisions are therefore based on imperfect information. This information comes from more or less reliable sources ranging from historical data, expert assessments, numerical simulations etc. Finally, risk management decisions are the result of complex knowledge management and reasoning processes. Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process. One major goal today is therefore to assist decision-making while considering the availability, quality and reliability of information content and sources. A global integrated framework is proposed to improve the risk management process in a context of information imperfection provided by more or less reliable sources: uncertainty as well as imprecision, inconsistency and incompleteness are considered. Several methods are used and associated in an original way: sequential decision context description, development of specific multi-criteria decision-making methods, imperfection propagation in numerical modeling and information fusion. This framework not only assists in decision-making but also traces the process and evaluates the impact of information quality on decision-making. We focus and present two main developments. The first one relates to uncertainty and imprecision propagation in numerical modeling using both classical Monte-Carlo probabilistic approach and also so-called Hybrid approach using possibility theory. Second approach deals with new multi-criteria decision-making methods which consider information imperfection, source reliability, importance and conflict, using fuzzy sets as well as possibility and belief function theories. Implemented methods consider information imperfection propagation and information fusion in total aggregation methods such as AHP (Saaty, 1980) or partial aggregation methods such as the Electre outranking method (see Soft Electre Tri ) or decisions in certain but also risky or uncertain contexts (see new COWA-ER and FOWA-ER- Cautious and Fuzzy Ordered Weighted Averaging-Evidential Reasoning). For example, the ER-MCDA methodology considers expert assessment as a multi-criteria decision process based on imperfect information provided by more or less heterogeneous, reliable and conflicting sources: it mixes AHP, fuzzy sets theory, possibility theory and belief function theory using DSmT (Dezert-Smarandache Theory) framework which provides powerful fusion rules.

Multi-Attribute Selection of Coal Center Location: A Case Study in Thailand

NASA Astrophysics Data System (ADS)

Kuakunrittiwong, T.; Ratanakuakangwan, S.

2016-11-01

Under Power Development Plan 2015, Thailand has to diversify its heavily gas-fired electricity generation. The main owner of electricity transmission grids is responsible to implement several coal-fired power plants with clean coal technology. To environmentally handle and economically transport unprecedented quantities of sub-bituminous and bituminous coal, a coal center is required. The location of such facility is an important strategic decision and a paramount to the success of the energy plan. As site selection involves many criteria, Fuzzy Analytical Hierarchy Process or Fuzzy-AHP is applied to select the most suitable location among three candidates. Having analyzed relevant criteria and the potential alternatives, the result reveals that engineering and socioeconomic are important criteria and Map Ta Phut is the most suitable site for the coal center.

Evaluating Pillar Industry’s Transformation Capability: A Case Study of Two Chinese Steel-Based Cities

PubMed Central

Li, Zhidong; Marinova, Dora; Guo, Xiumei; Gao, Yuan

2015-01-01

Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China’s steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities’ abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns. PMID:26422266

Evaluating Pillar Industry's Transformation Capability: A Case Study of Two Chinese Steel-Based Cities.

PubMed

Li, Zhidong; Marinova, Dora; Guo, Xiumei; Gao, Yuan

2015-01-01

Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China's steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities' abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns.

Multi-criteria decision support framework for sustainable implementation of effective green supply chain management practices.

PubMed

Boutkhoum, Omar; Hanine, Mohamed; Boukhriss, Hicham; Agouti, Tarik; Tikniouine, Abdessadek

2016-01-01

At present, environmental issues become real critical barriers for many supply chain corporations concerning the sustainability of their businesses. In this context, several studies have been proposed from both academia and industry trying to develop new measurements related to green supply chain management (GSCM) practices to overcome these barriers, which will help create new environmental strategies, implementing those practices in their manufacturing processes. The objective of this study is to present the technical and analytical contribution that multi-criteria decision making analysis (MCDA) can bring to environmental decision making problems, and especially to GSCM field. For this reason, a multi-criteria decision-making methodology, combining fuzzy analytical hierarchy process and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS), is proposed to contribute to a better understanding of new sustainable strategies through the identification and evaluation of the most appropriate GSCM practices to be adopted by industrial organizations. The fuzzy AHP process is used to construct hierarchies of the influential criteria, and then identify the importance weights of the selected criteria, while the fuzzy TOPSIS process employs these weighted criteria as inputs to evaluate and measure the performance of each alternative. To illustrate the effectiveness and performance of our MCDA approach, we have applied it to a chemical industry corporation located in Safi, Morocco.

Efficient management design for swimming exercise treatment.

PubMed

Kim, Kyunghun; Kyung, Taewon; Kim, Wonhyun; Shin, Chungsick; Song, Youngjae; Lee, Moo Yeol; Lee, Hyunwoo; Cho, Yongchan

2009-12-01

Exercise-mediated physical treatment has attracted much recent interest. In particular, swimming is a representative exercise treatment method recommended for patients experiencing muscular and cardiovascular diseases. The present study sought to design a swimming-based exercise treatment management system. A survey questionnaire was completed by participants to assess the prevalence of muscular and cardiovascular diseases among adult males and females participating in swimming programs at sport centers in metropolitan regions of country. Using the Fuzzy Analytic Hierarchy Process (AHP) technique, weighted values of indices were determined, to maximize participant clarity. A patient management system model was devised using information technology. The favorable results are evidence of the validity of this approach. Additionally, the swimming-based exercise management system can be supplemented together with analyses of weighted values considering connectivity between established indices.

Uncertainty in benefit cost analysis of smart grid demonstration-projects in the U.S., China, and Italy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Flego, Gianluca; Yu, Jiancheng

Given the substantial investments required, there has been keen interest in conducting benefits analysis, i.e., quantifying, and often monetizing, the performance of smart grid technologies. In this study, we compare two different approaches; (1) Electric Power Research Institute (EPRI)’s benefits analysis method and its adaptation to the European contexts by the European Commission, Joint Research Centre (JRC), and (2) the Analytic Hierarchy Process (AHP) and fuzzy logic decision making method. These are applied to three case demonstration projects executed in three different countries; the U.S., China, and Italy, considering uncertainty in each case. This work is conducted under the U.S.more » (United States)-China Climate Change Working Group, smart grid, with an additional major contribution by the European Commission. The following is a brief description of the three demonstration projects.« less

Evaluation of Supply Chain Management Systems Used in Civil Engineering

NASA Astrophysics Data System (ADS)

Tomczak, Michał; Rzepecki, Łukasz

2017-10-01

One of the most important factors which have an effect on the cost and time of the building process is the organization of physical resources and the information flow structure. Depending on how effective this system is, a building project may end with a success or a failure. Because of many conditions of the construction executing and different needs of the contractors, there are different Supply Chain Management (SCM) systems connected with supplying construction projects: single-stage, multi-stage or combined. The article presents a comparative analysis of construction SCM systems based on a modified fuzzy AHP. The modification of this method is based on the use of interval type-2 fuzzy sets to aggregate evaluation according to the idea proposed by Mikhailov. The use of such a model of group preferences of decision-makers, makes it possible to take into consideration both the linguistic imprecision of an evaluation and the small number of experts. The weight values of specific criteria and the final scale vector of considered variants are obtained during the analysis. This may give a recommendation to general contractors in construction projects about which evaluation criteria and supply systems are preferred.

Performance Analysis of Hospital Managers Using Fuzzy AHP and Fuzzy TOPSIS: Iranian Experience

PubMed Central

Shafii, Milad; Hosseini, Seyed Mostafa; Arab, Mohammad; Asgharizadeh, Ezzatollah; Farzianpour, Fereshteh

2016-01-01

Background and Objectives: Hospitals are complex organizations that require strong and effective management. The success of such organizations depends on the performance of managers. This study provides a comprehensive set of indicators to assess the performance of hospital managers in Iranian Ministry of Health owned hospitals. Methods: This research was a cross-sectional study. First, reviewing the literature and using experts’ viewpoints and convening a panel of experts, the dimensions of performance have been selected and came in the form of a performance model. Then, using Fuzzy Analytic Hierarchy Process (FAHP), the chosen dimensions were weighted. Finally, based on the weighted performance dimensions, a questionnaire was designed and after confirming the reliability and validity, through a census, 407 senior and middle managers from 10 hospitals in Yazd, Iran completed it and performance of CEOs in these hospitals was evaluated using the Fuzzy Technique for Order Preference by Similarity Ideal Solution (FTOPSIS). Results: To measure the performance of hospital managers, a performance assessment model consisted of 19 sub-dimensions in 5 main dimensions (Functional, Professional, Organizational, Individual and Human) was developed. The functional area had the most weight and the individual area had the least weight, as well. The hospital managers had different performance levels in each category and sub-dimensions. In terms of overall performance, the hospital managers C and H had the best and the worst performance, respectively. Conclusions: The use of appropriate dimensions for performance, prioritizing them and evaluating the performance of hospital managers using appropriate techniques, can play an effective role in the selection of qualified managers, identifying strengths and weaknesses in performance and continuous improvement of them. PMID:26383216

Optimal feature selection using a modified differential evolution algorithm and its effectiveness for prediction of heart disease.

PubMed

Vivekanandan, T; Sriman Narayana Iyengar, N Ch

2017-11-01

Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems. A modified differential evolution (DE) algorithm is used to perform feature selection for cardiovascular disease and optimization of selected features. Of the 10 available strategies for the traditional DE algorithm, the seventh strategy, which is represented by DE/rand/2/exp, is considered for comparative study. The performance analysis of the developed modified DE strategy is given in this paper. With the selected critical features, prediction of heart disease is carried out using fuzzy AHP and a feed-forward neural network. Various performance measures of integrating the modified differential evolution algorithm with fuzzy AHP and a feed-forward neural network in the prediction of heart disease are evaluated in this paper. The accuracy of the proposed hybrid model is 83%, which is higher than that of some other existing models. In addition, the prediction time of the proposed hybrid model is also evaluated and has shown promising results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiattribute Decision Modeling Techniques: A Comparative Analysis

DTIC Science & Technology

1988-08-01

Analytic Hierarchy Process ( AHP ). It is structurally similar to SMART, but elicitation methods are different and there are several algorithms for...reconciliation of inconsistent judgments and for consistency checks that are not available in any of the utility procedures. The AHP has been applied...of commercially available software packages that implement the AHP algorithms. Elicitation Methods. The AHP builds heavily on value trees, which

GIS-based flood risk model evaluated by Fuzzy Analytic Hierarchy Process (FAHP)

NASA Astrophysics Data System (ADS)

Sukcharoen, Tharapong; Weng, Jingnong; Teetat, Charoenkalunyuta

2016-10-01

Over the last 2-3 decades, the economy of many countries around the world has been developed rapidly but it was unbalanced development because of expecting on economic growth only. Meanwhile it lacked of effective planning in the use of natural resources. This can significantly induce climate change which is major cause of natural disaster. Hereby, Thailand has also suffered from natural disaster for ages. Especially, the flood which is most hazardous disaster in Thailand can annually result in the great loss of life and property, environment and economy. Since the flood management of country is inadequate efficiency. It is unable to support the flood analysis comprehensively. This paper applied Geographic Information System and Multi-Criteria Decision Making to create flood risk model at regional scale. Angthong province in Thailand was used as the study area. In practical process, Fuzzy logic technique has been used to improve specialist's assessment by implementing with Fuzzy membership because human decision is flawed under uncertainty then AHP technique was processed orderly. The hierarchy structure in this paper was categorized the spatial flood factors into two levels as following: 6 criteria (Meteorology, Geology, Topography, Hydrology, Human and Flood history) and 8 factors (Average Rainfall, Distance from Stream, Soil drainage capability, Slope, Elevation, Land use, Distance from road and Flooded area in the past). The validity of the pair-wise comparison in AHP was shown as C.R. value which indicated that the specialist judgment was reasonably consistent. FAHP computation result has shown that the first priority of criteria was Meteorology. In addition, the Rainfall was the most influencing factor for flooding. Finally, the output was displayed in thematic map of Angthong province with flood risk level processed by GIS tools. The map was classified into: High Risk, Moderate Risk and Low Risk (13.20%, 75.58%, and 11.22% of total area).

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparing Analytic Hierarchy Process and Discrete-Choice Experiment to Elicit Patient Preferences for Treatment Characteristics in Age-Related Macular Degeneration.

PubMed

Danner, Marion; Vennedey, Vera; Hiligsmann, Mickaël; Fauser, Sascha; Gross, Christian; Stock, Stephanie

2017-09-01

In this study, we conducted an analytic hierarchy process (AHP) and a discrete choice experiment (DCE) to elicit the preferences of patients with age-related macular degeneration using identical attributes and levels. To compare preference-based weights for age-related macular degeneration treatment attributes and levels generated by two elicitation methods. The properties of both methods were assessed, including ease of instrument use. A DCE and an AHP experiment were designed on the basis of five attributes. Preference-based weights were generated using the matrix multiplication method for attributes and levels in AHP and a mixed multinomial logit model for levels in the DCE. Attribute importance was further compared using coefficient (DCE) and weight (AHP) level ranges. The questionnaire difficulty was rated on a qualitative scale. Patients were asked to think aloud while providing their judgments. AHP and DCE generated similar results regarding levels, stressing a preference for visual improvement, frequent monitoring, on-demand and less frequent injection schemes, approved drugs, and mild side effects. Attribute weights derived on the basis of level ranges led to a ranking that was opposite to the AHP directly calculated attribute weights. For example, visual function ranked first in the AHP and last on the basis of level ranges. The results across the methods were similar, with one exception: the directly measured AHP attribute weights were different from the level-based interpretation of attribute importance in both DCE and AHP. The dependence/independence of attribute importance on level ranges in DCE and AHP, respectively, should be taken into account when choosing a method to support decision making. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A review of techniques to determine alternative selection in design for remanufacturing

NASA Astrophysics Data System (ADS)

Noor, A. Z. Mohamed; Fauadi, M. H. F. Md; Jafar, F. A.; Mohamad, N. R.; Yunos, A. S. Mohd

2017-10-01

This paper discusses the techniques used for optimization in manufacturing system. Although problem domain is focused on sustainable manufacturing, techniques used to optimize general manufacturing system were also discussed. Important aspects of Design for Remanufacturing (DFReM) considered include indexes, weighted average, grey decision making and Fuzzy TOPSIS. The limitation of existing techniques are most of them is highly based on decision maker’s perspective. Different experts may have different understanding and eventually scale it differently. Therefore, the objective of this paper is to determine available techniques and identify the lacking feature in it. Once all the techniques have been reviewed, a decision will be made by create another technique which should counter the lacking of discussed techniques. In this paper, shows that the hybrid computation of Fuzzy Analytic Hierarchy Process (AHP) and Artificial Neural Network (ANN) is suitable and fill the gap of all discussed technique.

A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation.

PubMed

Ijzerman, Maarten J; van Til, Janine A; Bridges, John F P

2012-01-01

With growing emphasis on patient involvement in health technology assessment, there is a need for scientific methods that formally elicit patient preferences. Analytic hierarchy process (AHP) and conjoint analysis (CA) are two established scientific methods - albeit with very different objectives. The objective of this study was to compare the performance of AHP and CA in eliciting patient preferences for treatment alternatives for stroke rehabilitation. Five competing treatments for drop-foot impairment in stroke were identified. One survey, including the AHP and CA questions, was sent to 142 patients, resulting in 89 patients for final analysis (response rate 63%). Standard software was used to calculate attribute weights from both AHP and CA. Performance weights for the treatments were obtained from an expert panel using AHP. Subsequently, the mean predicted preference for each of the five treatments was calculated using the AHP and CA weights. Differences were tested using non-parametric tests. Furthermore, all treatments were rank ordered for each individual patient, using the AHP and CA weights. Important attributes in both AHP and CA were the clinical outcome (0.3 in AHP and 0.33 in CA) and risk of complications (about 0.2 in both AHP and CA). Main differences between the methods were found for the attributes 'impact of treatment' (0.06 for AHP and 0.28 for two combined attributes in CA) and 'cosmetics and comfort' (0.28 for two combined attributes in AHP and 0.05 for CA). On a group level, the most preferred treatments were soft tissue surgery (STS) and orthopedic shoes (OS). However, STS was most preferred using AHP weights versus OS using CA weights (p < 0.001). This difference was even more obvious when interpreting the individual treatment ranks. Nearly all patients preferred STS according to the AHP predictions, while >50% of the patients chose OS instead of STS, as most preferred treatment using CA weights. While we found differences between AHP and CA, these differences were most likely caused by the labeling of the attributes and the elicitation of performance judgments. CA scenarios are built using the level descriptions, and hence provide realistic treatment scenarios. In AHP, patients only compared less concrete attributes such as 'impact of treatment.' This led to less realistic choices, and thus overestimation of the preference for the surgical scenarios. Several recommendations are given on how to use AHP and CA in assessing patient preferences.

A multi-criteria spatial deprivation index to support health inequality analyses.

PubMed

Cabrera-Barona, Pablo; Murphy, Thomas; Kienberger, Stefan; Blaschke, Thomas

2015-03-20

Deprivation indices are useful measures to analyze health inequalities. There are several methods to construct these indices, however, few studies have used Geographic Information Systems (GIS) and Multi-Criteria methods to construct a deprivation index. Therefore, this study applies Multi-Criteria Evaluation to calculate weights for the indicators that make up the deprivation index and a GIS-based fuzzy approach to create different scenarios of this index is also implemented. The Analytical Hierarchy Process (AHP) is used to obtain the weights for the indicators of the index. The Ordered Weighted Averaging (OWA) method using linguistic quantifiers is applied in order to create different deprivation scenarios. Geographically Weighted Regression (GWR) and a Moran's I analysis are employed to explore spatial relationships between the different deprivation measures and two health factors: the distance to health services and the percentage of people that have never had a live birth. This last indicator was considered as the dependent variable in the GWR. The case study is Quito City, in Ecuador. The AHP-based deprivation index show medium and high levels of deprivation (0,511 to 1,000) in specific zones of the study area, even though most of the study area has low values of deprivation. OWA results show deprivation scenarios that can be evaluated considering the different attitudes of decision makers. GWR results indicate that the deprivation index and its OWA scenarios can be considered as local estimators for health related phenomena. Moran's I calculations demonstrate that several deprivation scenarios, in combination with the 'distance to health services' factor, could be explanatory variables to predict the percentage of people that have never had a live birth. The AHP-based deprivation index and the OWA deprivation scenarios developed in this study are Multi-Criteria instruments that can support the identification of highly deprived zones and can support health inequalities analysis in combination with different health factors. The methodology described in this study can be applied in other regions of the world to develop spatial deprivation indices based on Multi-Criteria analysis.

[An integrated assessment method of ecological quality status in coastal waters: taking Tong'an Bay as a case].

PubMed

Chen, Zhao-hua; Wu, Hai-yan; Chen, Ke-liang; Chen, Qing-hui; Wu, Ji-chun; Zhang, Jing-fei

2011-07-01

Based on the integrated assessment methods of ecological quality status (EcoQS) in coastal waters abroad as well as the domestic related research status, 11 indices were selected from the biotic and physicochemical elements of water and sediment to built an integrated EcoQS assessment index system, and, with the comprehensive consideration of domestic and international evaluation standards, 5 levels of EcoQS classified as "high, good, moderate, poor, and bad" were determined. Then, an integrated assessment method of EcoQS in coastal waters was established by using analytic hierarchy process (AHP) and fuzzy mathematics method, and tested by the analysis of the correlations between the EcoQS grade and the major anthropogenic disturbances and pollutant concentrations of Tong' an Bay. The EcoQS of Tong' an Bay was assessed as moderate, i.e., the Bay was moderately disturbed and in transitional to poor status. The established integrated assessment method could not only reflect the major anthropogenic environmental pressure and risk factors, but also give an early warning of the pollutants satisfied by law in the study area.

Evaluation and Selection of Predicaments in Pharmaceutical Supply Chain using AHP under Fuzzy Environment

NASA Astrophysics Data System (ADS)

Nikhil, E. V. S.; Sai Ram, V.; Charan Yadav, V.; Kiran Kumar, Kalla; Nagaraju, Dega

2017-05-01

Pharmaceutical sector plays an important role in the medical and health system. Due to the globalization of the business, increasing demand and supply for drugs, growing regulatory requirements, all stages of the pharmaceutical supply chain (SC) are facing numerous predicaments. The traditional way of selection and evaluation of these predicaments is customarily done using technical information. This approach lacks the ability to project the burning issue that to be addressed first. Hence, a computing method of selecting the crucial issue from the existing issues is essential in a pharmaceutical supply chain. This paper considers seven different predicaments as criteria and five sub-criteria under each main predicament of a pharmaceutical supply chain. The intention of this project is to manifest the process of assessing and selecting the issue that to be addressed first by using multi-criteria decision making technique (MCDM), i.e., fuzzy analytical hierarchy process (FAHP). The criteria and sub-criteria weights are calculated and priority assessment of the predicaments is done by using FAHP. Finally, from the findings of this work, the predicaments are ranked from most important to least important. This gives information to the decision maker (DM) to solve the issue that is affecting the SC the most with respect to the others.

An integrated approach of AHP and DEMATEL methods in evaluating the criteria of auto spare parts industry

NASA Astrophysics Data System (ADS)

Wu, Hsin-Hung; Tsai, Ya-Ning

2012-11-01

This study uses both analytic hierarchy process (AHP) and decision-making trial and evaluation laboratory (DEMATEL) methods to evaluate the criteria in auto spare parts industry in Taiwan. Traditionally, AHP does not consider indirect effects for each criterion and assumes that criteria are independent without further addressing the interdependence between or among the criteria. Thus, the importance computed by AHP can be viewed as short-term improvement opportunity. On the contrary, DEMATEL method not only evaluates the importance of criteria but also depicts the causal relations of criteria. By observing the causal diagrams, the improvement based on cause-oriented criteria might improve the performance effectively and efficiently for the long-term perspective. As a result, the major advantage of integrating AHP and DEMATEL methods is that the decision maker can continuously improve suppliers' performance from both short-term and long-term viewpoints.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

Interactive data based on Apriori - AHP - C4.5 results assessment method

NASA Astrophysics Data System (ADS)

Zhao, Quan; Zhang, Li

2017-05-01

AHP method for weight calculation method, will introduce the subjective concept of "experts, supposed steps", for the objective result has certain uncertainty, causes the classroom interaction data attribute weights proportion difference is not big, the whole class achievement trend of convergence, introduce the concept of Apriori-AHP. C4.5 is used to calculate the weight of attribute column, and then using the Apriori-AHP algorithm calculate attribute weights, attribute importance weights on judgment performance indicators table overall consideration, with the weight of index table of gifted student achievement, make the class performance trends to fluctuate, have tended to be "standard" real results for teacher reference.

A fuzzy linguistic model for the prediction of carpal tunnel syndrome risks in an occupational environment.

PubMed

Bell, P M; Crumpton, L

1997-08-01

This research presents the development and evaluation of a fuzzy linguistic model designated to predict the risk of carpal tunnel syndrome (CTS) in an occupational setting. CTS has become one of the largest problems facing ergonomists and the medical community because it is developing in epidemic proportions within the occupational environment. In addition, practitioners are interested in identifying accurate methods for evaluating the risk of CTS in an occupational setting. It is hypothesized that many factors impact an individual's likelihood of developing CTS and the eventual development of CTS. This disparity in the occurrence of CTS for workers with similar backgrounds and work activities has confused researchers and has been a stumbling block in the development of a model for widespread use in evaluating the development of CTS. Thus this research is an attempt to develop a method that can be used to predict the likelihood of CTS risk in a variety of environments. The intent is that this model will be applied eventually in an occupational setting, thus model development was focused on a method that provided a usable interface and the desired system inputs can also be obtained without the benefit of a medical practitioner. The methodology involves knowledge acquisition to identify and categorize a holistic set of risk factors that include task-related, personal, and organizational categories. The determination of relative factor importance was accomplished using analytic hierarchy processing (AHP) analysis. Finally a mathematical representation of the CTS risk was accomplished by utilizing fuzzy set theory in order to quantify linguistic input parameters. An evaluation of the model including determination of sensitivity and specificity is conducted and the results of the model indicate that the results are fairly accurate and this method has the potential for widespread use. A significant aspect of this research is the comparison of this technique to other methods for assessing presence of CTS. The results of this evaluation technique are compared with more traditional methods for assessing the presence of CTS.

Groundwater resource exploration in Salem district, Tamil Nadu using GIS and remote sensing

NASA Astrophysics Data System (ADS)

Maheswaran, G.; Selvarani, A. Geetha; Elangovan, K.

2016-03-01

Since last decade, the value per barrel of potable groundwater has outpaced the value of a barrel of oil in many areas of the world. Hence, proper assessment of groundwater potential and management practices are the needs of the day. Establishing relationship between remote sensing data and hydrologic phenomenon can maximize the efficiency of water resources development projects. Present study focuses on groundwater potential assessment in Salem district, Tamil Nadu to investigate groundwater resource potential. At the same, all thematic layers important from ground water occurrence and movement point of view were digitized and integrated in the GIS environment. The weights of different parameters/themes were computed using weighed index overlay analysis (WIOA), analytic hierarchy process (AHP) and fuzzy logic technique. Through this integrated GIS analysis, groundwater prospect map of the study area was prepared qualitatively. Field verification at observation wells was used to verify identified potential zones and depth of water measured at observation wells. Generated map from weighed overlay using AHP performed very well in predicting the groundwater surface and hence this methodology proves to be a promising tool for future.

Comparison AHP and SAW to promotion of head major department SMK Muhammadiyah 04 Medan

NASA Astrophysics Data System (ADS)

Saputra, M.; Sitompul, O. S.; Sihombing, P.

2018-04-01

Decision Support System (DSS) is a system that can help a person to make informed decisions about various types of choices that are performed accurately and in accordance with the desired goals. Many problems can be solved by using decision support systems. In this journal the decision support system is used to assist the Chief of Muhammadiyah Medan branch in the selection of the department chief. The criteria used for the election of department chiefs are: Loyalty, Job Performance, Responsibility, Obedience, Honesty, Cooperation, Education, and Leadership. The selection promotion process consists of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The data were obtained through teacher assessment questionnaires by principals and colleagues. The results of this study used a comparison with two decision methods namely SAW method and AHP method so that the decision maker (principal) is more appropriate in the determination of candidates who will be elected head of department at school. The final result of this research is the first rank obtained by muhammad musa with weight value on AHP method (0.274) and weight value on SAW method (0.993), alvin syahrin with weight value on AHP method (0.241) and weight value on SAW method (0.883), noviyanti with weight value on AHP method (0.193) and weight value on SAW method (0.707). So the conclusion on the research that is by using SAW method the value of weight produced more accurate.

Landfill site selection using combination of GIS and fuzzy AHP, a case study: Iranshahr, Iran.

PubMed

Torabi-Kaveh, M; Babazadeh, R; Mohammadi, S D; Zaresefat, M

2016-03-09

One of the most important recent challenges in solid waste management throughout the world is site selection of sanitary landfill. Commonly, because of simultaneous effects of social, environmental, and technical parameters on suitability of a landfill site, landfill site selection is a complex process and depends on several criteria and regulations. This study develops a multi-criteria decision analysis (MCDA) process, which combines geographic information system (GIS) analysis with a fuzzy analytical hierarchy process (FAHP), to determine suitable sites for landfill construction in Iranshahr County, Iran. The GIS was used to calculate and classify selected criteria and FAHP was used to assess the criteria weights based on their effectiveness on selection of potential landfill sites. Finally, a suitability map was prepared by overlay analyses and suitable areas were identified. Four suitability classes within the study area were separated, including high, medium, low, and very low suitability areas, which represented 18%, 15%, 55%, and 12% of the study area, respectively. © The Author(s) 2016.

Priority Determination of Underwater Tourism Site Development in Gorontalo Province using Analytical Hierarchy Process (AHP)

NASA Astrophysics Data System (ADS)

Rohandi, M.; Tuloli, M. Y.; Jassin, R. T.

2018-02-01

This research aims to determine the development of priority of underwater tourism in Gorontalo province using the Analytical Hierarchy Process (AHP) method which is one of DSS methods applying Multi-Attribute Decision Making (MADM). This method used 5 criteria and 28 alternatives to determine the best priority of underwater tourism site development in Gorontalo province. Based on the AHP calculation it appeared that the best priority development of underwater tourism site is Pulau Cinta whose total AHP score is 0.489 or 48.9%. This DSS produced a reliable result, faster solution, time-saving, and low cost for the decision makers to obtain the best underwater tourism site to be developed.

Selecting Proper Plant Species for Mine Reclamation Using Fuzzy AHP Approach (Case Study: Chadormaloo Iron Mine of Iran)

NASA Astrophysics Data System (ADS)

Ebrahimabadi, Arash

2016-12-01

This paper describes an effective approach to select suitable plant species for reclamation of mined lands in Chadormaloo iron mine which is located in central part of Iran, near the city of Bafgh in Yazd province. After mine's total reserves are excavated, the mine requires to be permanently closed and reclaimed. Mine reclamation and post-mining land-use are the main issues in the phase of mine closure. In general, among various scenarios for mine reclamation process, i.e. planting, agriculture, forestry, residency, tourist attraction, etc., planting is the oldest and commonly-used technology for the reclamation of lands damaged by mining activities. Planting and vegetation play a major role in restoring productivity, ecosystem stability and biological diversity to degraded areas, therefore the main goal of this research work is to choose proper and suitable plants compatible with the conditions of Chadormaloo mined area, providing consistent conditions for future use. To ensure the sustainability of the reclaimed landscape, the most suitable plant species adapted to the mine conditions are selected. Plant species selection is a Multi Criteria Decision Making (MCDM) problem. In this paper, a fuzzy MCDM technique, namely Fuzzy Analytic Hierarchy Process (FAHP) is developed to assist chadormaloo iron mine managers and designers in the process of plant type selection for reclamation of the mine under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The results achieved from using FAHP approach demonstrate that the most proper plant species are ranked as Artemisia sieberi, Salsola yazdiana, Halophytes types, and Zygophyllum, respectively for reclamation of Chadormaloo iron mine.

An improved hybrid multi-criteria/multidimensional model for strategic industrial location selection: Casablanca industrial zones as a case study.

PubMed

Boutkhoum, Omar; Hanine, Mohamed; Agouti, Tarik; Tikniouine, Abdessadek

2015-01-01

In this paper, we examine the issue of strategic industrial location selection in uncertain decision making environments for implanting new industrial corporation. In fact, the industrial location issue is typically considered as a crucial factor in business research field which is related to many calculations about natural resources, distributors, suppliers, customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis with analytical capabilities that OLAP systems can provide for successful and optimal industrial location selection. The proposed model mainly consists in three stages. In the first stage, a decision-making committee has been established to identify the evaluation criteria impacting the location selection process. In the second stage, we develop fuzzy AHP software based on the extent analysis method to assign the importance weights to the selected criteria, which allows us to model the linguistic vagueness, ambiguity, and incomplete knowledge. In the last stage, OLAP analysis integrated with multi-criteria analysis employs these weighted criteria as inputs to evaluate, rank and select the strategic industrial location for implanting new business corporation in the region of Casablanca, Morocco. Finally, a sensitivity analysis is performed to evaluate the impact of criteria weights and the preferences given by decision makers on the final rankings of strategic industrial locations.

Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP)

PubMed Central

Dolan, James G.

2008-01-01

Objective To illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician-patient communication. Methods Tutorial review. Results The AHP promotes shared decision making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders. Conclusions The AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness. Practice Implications Many clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient-provider communication, clinical decision-making, and the quality of patient care in these situations. PMID:18760559

An application of the AHP in water resources management: a case study on urban drainage rehabilitation in Medan City

NASA Astrophysics Data System (ADS)

Tarigan, A. P. M.; Rahmad, D.; Sembiring, R. A.; Iskandar, R.

2018-02-01

This paper illustrates an application of Analytical Hierarchy Process (AHP) as a potential decision-making method in water resource management related to drainage rehabilitation. The prioritization problem of urban drainage rehabilitation in Medan City due to limited budget is used as a study case. A hierarchical structure is formed for the prioritization criteria and the alternative drainages to be rehabilitated. Based on the AHP, the prioritization criteria are ranked and a descending-order list of drainage is made in order to select the most favorable drainages to have rehabilitation. A sensitivity analysis is then conducted to check the consistency of the final decisions in case of minor changes in judgements. The results of AHP computed manually are compared with that using the software Expert Choice. It is observed that the top three ranked drainages are consistent, and both results of the AHP methods, calculated manually and performed using Expert Choice, are in agreement. It is hoped that the application of the AHP will help the decision-making process by the city government in the problem of urban drainage rehabilitation.

Application of Delphi-AHP methods to select the priorities of WEEE for recycling in a waste management decision-making tool.

PubMed

Kim, Mincheol; Jang, Yong-Chul; Lee, Seunguk

2013-10-15

The management of waste electrical and electronic equipment (WEEE) or electronic waste (e-waste) has become a major issue of concern for solid waste communities due to the large volumes of waste being generated from the consumption of modern electrical and electronic products. In 2003, Korea introduced the extended producer responsibility (EPR) system to reduce the amount of electronic products to be disposed and to promote resource recovery from WEEE. The EPR currently regulates a total of 10 electrical and electronic products. This paper presents the results of the application of the Delphi method and analytical hierarchy process (AHP) modeling to the WEEE management tool in the policy-making process. Specifically, this paper focuses on the application of the Delphi-AHP technique to determine the WEEE priority to be included in the EPR system. Appropriate evaluation criteria were derived using the Delphi method to assess the potential selection and priority among electrical and electronic products that will be regulated by the EPR system. Quantitative weightings from the AHP model were calculated to identify the priorities of electrical and electronic products to be potentially regulated. After applying all the criteria using the AHP model, the results indicate that the top 10 target recycling products for the expansion of the WEEE list were found to be vacuum cleaners, electric fans, rice cookers, large freezers, microwave ovens, water purifiers, air purifiers, humidifiers, dryers, and telephones in order from the first to last. The proposed Delphi-AHP method can offer a more efficient means of selecting WEEE than subjective assessment methods that are often based on professional judgment or limited available data. By providing WEEE items to be regulated, the proposed Delphi-AHP method can eliminate uncertainty and subjective assessment and enable WEEE management policy-makers to identify the priority of potential WEEE. More generally, the work performed in this study is an example of how Delphi-AHP modeling can be used as a decision-making process tool in WEEE management. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Evaluation of purchase intention of customers in two wheeler automobile segment: AHP and TOPSIS

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

Winning heart of customers is preeminent main design of any business organization in global business environment. This paper explored customer’s priorities while purchasing a two wheeler automobile segment using Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a multi criteria decision making tools to accomplish the research objectives. Study has been done to analyze different criteria to be considered during purchasing of two wheeler automobiles among respondents using structured questionnaire based on SAATY scale. Based on our previous work on empirical & fuzzy logic approach to product quality and purchase intention of customers in two wheeler- operational, performance, economic, brand value and maintenance aspects are considered as decision criteria of customers while purchasing a two wheeler. The study suggests high pick up during overtaking, petrol saving, reasonable spare parts price, unique in design and identity and easy to change gear as main criterion in purchasing process. We also found some leading two wheeler automobiles models available in Indian market using some objective function criterion in choosing some important characteristics like price, cylinder capacity, brake horse power and weight during purchasing process of two wheeler automobile in Indian market based on respondents perception.

Suitability assessment and mapping of Oyo State, Nigeria, for rice cultivation using GIS

NASA Astrophysics Data System (ADS)

Ayoade, Modupe Alake

2017-08-01

Rice is one of the most preferred food crops in Nigeria. However, local rice production has declined with the oil boom of the 1970s causing demand to outstrip supply. Rice production can be increased through the integration of Geographic Information Systems (GIS) and crop-land suitability analysis and mapping. Based on the key predictor variables that determine rice yield mentioned in relevant literature, data on rainfall, temperature, relative humidity, slope, and soil of Oyo state were obtained. To develop rice suitability maps for the state, two MCE-GIS techniques, namely the Overlay approach and weighted linear combination (WLC), using fuzzy AHP were used and compared. A Boolean land use map derived from a landsat imagery was used in masking out areas currently unavailable for rice production. Both suitability maps were classified into four categories of very suitable, suitable, moderate, and fairly moderate. Although the maps differ slightly, the overlay and WLC (AHP) approach found most parts of Oyo state (51.79 and 82.9 % respectively) to be moderately suitable for rice production. However, in areas like Eruwa, Oyo, and Shaki, rainfall amount received needs to be supplemented by irrigation for increased rice yield.

Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders.

PubMed

Ijzerman, Maarten J; van Til, Janine A; Snoek, Govert J

2008-12-01

To present and compare two multi-criteria decision techniques (analytic hierarchy process [AHP] and conjoint analysis [CA]) for eliciting preferences in patients with cervical spinal cord injury (SCI) who are eligible for surgical augmentation of hand function, either with or without implantation of a neuroprosthesis. The methods were compared in respect to attribute weights, overall preference, and practical experiences. Two previously designed and administered multi-criteria decision surveys in patients with SCI were compared and further analysed. Attributes and their weights in the AHP experiment were determined by an expert panel, followed by determination of the weights in the patient group. Attributes for the CA were selected and validated using an expert panel, piloted in six patients with SCI and subsequently administered to the same group of patients as participated in the AHP experiment. Both experiments showed the importance of non-outcome-related factors such as inpatient stay and number of surgical procedures. In particular, patients were less concerned with clinical outcomes in actual decision making. Overall preference in both the AHP and CA was in favor of tendon reconstruction (0.6 vs 0.4 for neuroprosthetic implantation). Both methods were easy to apply, but AHP was less easily explained and understood. Both the AHP and CA methods produced similar outcomes, which may have been caused by the obvious preferences of patients. CA may be preferred because of the holistic approach of considering all treatment attributes simultaneously and, hence, its power in simulating real market decisions. On the other hand, the AHP method is preferred as a hands-on, easy-to-implement task with immediate feedback to the respondent. This flexibility allows AHP to be used in shared decision making. However, the way the technique is composed results in many inconsistencies. Patients preferred CA but complained about the number of choice tasks.

Performance Analysis of Hospital Managers Using Fuzzy AHP and Fuzzy TOPSIS: Iranian Experience.

PubMed

Shafii, Milad; Hosseini, Seyed Mostafa; Arab, Mohammad; Asgharizadeh, Ezzatollah; Farzianpour, Fereshteh

2015-06-12

Hospitals are complex organizations that require strong and effective management. The success of such organizations depends on the performance of managers. This study provides a comprehensive set of indicators to assess the performance of hospital managers in Iranian Ministry of Health owned hospitals. This research was a cross-sectional study. First, reviewing the literature and using experts' viewpoints and convening a panel of experts, the dimensions of performance have been selected and came in the form of a performance model. Then, using Fuzzy Analytic Hierarchy Process (FAHP), the chosen dimensions were weighted. Finally, based on the weighted performance dimensions, a questionnaire was designed and after confirming the reliability and validity, through a census, 407 senior and middle managers from 10 hospitals in Yazd, Iran completed it and performance of CEOs in these hospitals was evaluated using the Fuzzy Technique for Order Preference by Similarity Ideal Solution (FTOPSIS). To measure the performance of hospital managers, a performance assessment model consisted of 19 sub-dimensions in 5 main dimensions (Functional, Professional, Organizational, Individual and Human) was developed. The functional area had the most weight and the individual area had the least weight, as well. The hospital managers had different performance levels in each category and sub-dimensions. In terms of overall performance, the hospital managers C and H had the best and the worst performance, respectively. The use of appropriate dimensions for performance, prioritizing them and evaluating the performance of hospital managers using appropriate techniques, can play an effective role in the selection of qualified managers, identifying strengths and weaknesses in performance and continuous improvement of them.

Study on Influencing Factor Analysis and Application of Consumer Mobile Commerce Acceptance

NASA Astrophysics Data System (ADS)

Li, Gaoguang; Lv, Tingjie

Mobile commerce (MC) refers to e-commerce activities carried out using a mobile device such as a phone or PDA. With new technology, MC will be rapidly growing in the near future. At the present time, what factors making consumer accept MC and what MC applications are acceptable by consumers are two of hot issues both for MC providers and f or MC researchers. This study presents a proposed MC acceptance model that integrates perceived playfulness, perceived risk and cost into the TAM to study which factors affect consumer MC acceptance. The proposed model includes five variables, namely perceived risk, cost, perceived usefulness, perceived playfulness, perceived ease of use, perceived playfulness. Then, using analytic hierarchy process (AHP) to calculate weight of criteria involved in proposed model. Finally, the study utilizes fuzzy comprehensive evaluation method to evaluate MC applications accepted possibility, and then a MC application is empirically tested using data collected from a survey of MC consumers.

DE-CERTS: A Decision Support System for a Comparative Evaluation Method for Risk Management Methodologies and Tools

DTIC Science & Technology

1991-09-01

iv III. THE ANALYTIC HIERARCHY PROCESS ..... ........ 15 A. INTRODUCTION ...... ................. 15 B. THE AHP PROCESS ...... ................ 16 C...INTRODUCTION ...... ................. 26 B. IMPLEMENTATION OF CERTS USING AHP ........ .. 27 1. Consistency ...... ................ 29 2. User Interface...the proposed technique into a Decision Support System. Expert Choice implements the Analytic Hierarchy Process ( AHP ), an approach to multi- criteria

Using an analytical hierarchy process (AHP) for weighting items of a measurement scale: a pilot study.

PubMed

Benaïm, C; Perennou, D-A; Pelissier, J-Y; Daures, J-P

2010-02-01

Many clinical scales contain items that are scored separately prior to being compiled into a single score. However, if the items have different degrees of importance, they should be weighted differently before being compiled. The principal aims of this study were to show how the "analytic hierarchy process" (AHP), which has never been used for this purpose, can be applied to weighting the six items of the "London handicap scale", and to compare the AHP to the "conjoint analysis" (CA), which was previously implemented by Harwood et al. (1994) [1]. In order to assess the relative importance of the six items, we submitted AHP and CA to a group of 10 physiatrists. We compared the methods in terms of item ranking according to importance, assessment of fictitious patients based on weights determined by each method, and perceived difficulty by the physiatrist. For both techniques, "Physical independence" (PHY) was the best-weighted item, but other ranks varied depending on the technique. AHP was better than CA in terms of accuracy (global assessment of the clinical status) and perceived difficulty. AHP may be used to reveal the importance that experts assign to the items of a multidimensional scale, and to calculate the appropriate weights for specific items. For this purpose, AHP seems to be more accurate than CA.

Economic benefit evaluation for renewable energy transmitted by HVDC based on production simulation (PS) and analytic hierarchy process(AHP)

NASA Astrophysics Data System (ADS)

Zhang, Jinfang; Zheng, Kuan; Liu, Jun; Huang, Xinting

2018-02-01

In order to support North and West China’s RE (RE) development and enhance accommodation in reasonable high level, HVDC’s traditional operation curves need some change to follow the output characteristic of RE, which helps to shrink curtailment electricity and curtailment ratio of RE. In this paper, an economic benefit analysis method based on production simulation (PS) and Analytic hierarchy process (AHP) has been proposed. PS is the basic tool to analyze chosen power system operation situation, and AHP method could give a suitable comparison result among many candidate schemes. Based on four different transmission curve combinations, related economic benefit has been evaluated by PS and AHP. The results and related index have shown the efficiency of suggested method, and finally it has been validated that HVDC operation curve in following RE output mode could have benefit in decreasing RE curtailment level and improving economic operation.

A novel method for designing and optimizing the layout of facilities in bathroom for the elderly in home-based rehabilitation.

PubMed

Wang, Duojin; Wu, Jing; Lin, Qinglian

2018-05-01

The home-based rehabilitation of elderly patients improves their autonomy, independence and reintegration into society. Hence, a suitable environment plays an important role in rehabilitation, as do different assistance technologies. The majority of accidents at home involving elderly people occur in the bathroom. Therefore, the planning of the layout of facilities is important in this potentially dangerous area. This paper proposes an approach towards designing and optimizing the layout of facilities in the bathroom, based on logistical and nonlogistical relationships. A fuzzy-based analytical hierarchical process (fuzzy-AHP) is then proposed for a comprehensive evaluation of the alternatives for this layout plan. This approach was applied to the home of a 71 years old female patient, who was experiencing home-based rehabilitation. After the initial designing and optimizing of the layout of the facilities in her bathroom, a plan could then be created for her particular needs. The results of this research could then enable the home-based rehabilitation of elderly patients to be more effective. Value: This paper develops a new approach to design and optimize the layout of facilities in bathroom for the elderly. Implications for Rehabilitation Develop a new approach to design and optimize the layout of facilities in bathroom. Provide a mathematical and more scientific approach to home layout design for home-based rehabilitation. Provide new opportunities for research, for both the therapist and the patient to analyse the home facility layout.

Stimuli-responsive magnetic nanoparticles for tumor-targeted bimodal imaging and photodynamic/hyperthermia combination therapy

NASA Astrophysics Data System (ADS)

Kim, Kyoung Sub; Kim, Jiyoung; Lee, Joo Young; Matsuda, Shofu; Hideshima, Sho; Mori, Yasurou; Osaka, Tetsuya; Na, Kun

2016-06-01

Despite magnetic nanoparticles having shown great potential in cancer treatment, tremendous challenges related to diagnostic sensitivity and treatment efficacy for clinical application remain. Herein, we designed optimized multifunctional magnetite nanoparticles (AHP@MNPs), composed of Fe3O4 nanoparticles and photosensitizer conjugated hyaluronic acid (AHP), to achieve enhanced tumor diagnosis and therapy. Fe3O4 nanoparticles (MNPs) were synthesized by a facile hydrolysis method. MNPs have higher biocompatibility, controllable particle sizes, and desirable magnetic properties. The fabricated AHP@MNPs have enhanced water solubility (average size: 108.13 +/- 1.08 nm), heat generation properties, and singlet oxygen generation properties upon magnetic and laser irradiation. The AHP@MNPs can target tumors via CD44 receptor-mediated endocytosis, which have enhanced tumor therapeutic effects through photodynamic/hyperthermia-combined treatment without any drugs. We successfully detected tumors implanted in mice via magnetic resonance imaging and optical imaging. Furthermore, we demonstrated the photodynamic/hyperthermia-combined therapeutic efficacy of AHP@MNPs with synergistically enhanced efficacy against cancer.Despite magnetic nanoparticles having shown great potential in cancer treatment, tremendous challenges related to diagnostic sensitivity and treatment efficacy for clinical application remain. Herein, we designed optimized multifunctional magnetite nanoparticles (AHP@MNPs), composed of Fe3O4 nanoparticles and photosensitizer conjugated hyaluronic acid (AHP), to achieve enhanced tumor diagnosis and therapy. Fe3O4 nanoparticles (MNPs) were synthesized by a facile hydrolysis method. MNPs have higher biocompatibility, controllable particle sizes, and desirable magnetic properties. The fabricated AHP@MNPs have enhanced water solubility (average size: 108.13 +/- 1.08 nm), heat generation properties, and singlet oxygen generation properties upon magnetic and laser irradiation. The AHP@MNPs can target tumors via CD44 receptor-mediated endocytosis, which have enhanced tumor therapeutic effects through photodynamic/hyperthermia-combined treatment without any drugs. We successfully detected tumors implanted in mice via magnetic resonance imaging and optical imaging. Furthermore, we demonstrated the photodynamic/hyperthermia-combined therapeutic efficacy of AHP@MNPs with synergistically enhanced efficacy against cancer. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr02273a

A Mixed Prioritization Operators Strategy Using A Single Measurement Criterion For AHP Application Development

NASA Astrophysics Data System (ADS)

Yuen, Kevin Kam Fung

2009-10-01

The most appropriate prioritization method is still one of the unsettled issues of the Analytic Hierarchy Process, although many studies have been made and applied. Interestingly, many AHP applications apply only Saaty's Eigenvector method as many studies have found that this method may produce rank reversals and have proposed various prioritization methods as alternatives. Some methods have been proved to be better than the Eigenvector method. However, these methods seem not to attract the attention of researchers. In this paper, eight important prioritization methods are reviewed. A Mixed Prioritization Operators Strategy (MPOS) is developed to select a vector which is prioritized by the most appropriate prioritization operator. To verify this new method, a case study of high school selection is revised using the proposed method. The contribution is that MPOS is useful for solving prioritization problems in the AHP.

The Evaluation of ERP Sandtable Simulation Based on AHP

NASA Astrophysics Data System (ADS)

Xu, Lan

Due to the trend of world globalization, many enterprises have extended their business to operate globally. Enterprise resource planning is a powerful management system providing the best business resources information. This paper proposed the theory of AHP, and presented ERP sandtable simulation evaluation to discuss how to make a decision using AHP. Using this method can make enterprises consider factors influence operation of enterprise adequately, including feedback and dependence among the factors.

Mining method selection by integrated AHP and PROMETHEE method.

PubMed

Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

2012-03-01

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

Integrated optimisation technique based on computer-aided capacity and safety evaluation for managing downstream lane-drop merging area of signalised junctions

NASA Astrophysics Data System (ADS)

Chen, CHAI; Yiik Diew, WONG

2017-02-01

This study provides an integrated strategy, encompassing microscopic simulation, safety assessment, and multi-attribute decision-making, to optimize traffic performance at downstream merging area of signalized intersections. A Fuzzy Cellular Automata (FCA) model is developed to replicate microscopic movement and merging behavior. Based on simulation experiment, the proposed FCA approach is able to provide capacity and safety evaluation of different traffic scenarios. The results are then evaluated through data envelopment analysis (DEA) and analytic hierarchy process (AHP). Optimized geometric layout and control strategies are then suggested for various traffic conditions. An optimal lane-drop distance that is dependent on traffic volume and speed limit can thus be established at the downstream merging area.

Investment risk evaluation and countermeasures suggestions of Power Grid Corp under the background of electric power reform

NASA Astrophysics Data System (ADS)

Yang, Chunhui; Su, Zhixiong; Wang, Yuqing; Liu, Yiqun; Qi, Yongwei

2017-03-01

Investment management is an important part of Power Grid Corp. The new electricity reform put forward the general idea of "three release, three strengthening, one independence", which brings new risks to the investment management of the Power Grid Corp. First, the paper analyzes the new risks faced by the Power Grid Corp investment under the background of the electricity reform. Second, the AHP-Fuzzy evaluation model of investment risk of Power Grid Corp is established, and taking Shenzhen Power Supply Bureau as an example, the paper evaluated its risk level of investment plan in 2017. Finally, in the context of the electricity reform, the strategy of the Power Grid Corp's investment risk is proposed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sahoo, Satiprasad; Dhar, Anirban, E-mail: anirban.dhar@gmail.com; Kar, Amlanjyoti

Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, windmore » speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.« less

Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer.

PubMed

Suner, Aslı; Çelikoğlu, Can Cengiz; Dicle, Oğuz; Sökmen, Selman

2012-09-01

The aim of the study is to determine the most appropriate method for construction of a sequential decision tree in the management of rectal cancer, using various patient-specific criteria and treatments such as surgery, chemotherapy, and radiotherapy. An analytic hierarchy process (AHP) was used to determine the priorities of variables. Relevant criteria used in two decision steps and their relative priorities were established by a panel of five general surgeons. Data were collected via a web-based application and analyzed using the "Expert Choice" software specifically developed for the AHP. Consistency ratios in the AHP method were calculated for each set of judgments, and the priorities of sub-criteria were determined. A sequential decision tree was constructed for the best treatment decision process, using priorities determined by the AHP method. Consistency ratios in the AHP method were calculated for each decision step, and the judgments were considered consistent. The tumor-related criterion "presence of perforation" (0.331) and the patient-surgeon-related criterion "surgeon's experience" (0.630) had the highest priority in the first decision step. In the second decision step, the tumor-related criterion "the stage of the disease" (0.230) and the patient-surgeon-related criterion "surgeon's experience" (0.281) were the paramount criteria. The results showed some variation in the ranking of criteria between the decision steps. In the second decision step, for instance, the tumor-related criterion "presence of perforation" was just the fifth. The consistency of decision support systems largely depends on the quality of the underlying decision tree. When several choices and variables have to be considered in a decision, it is very important to determine priorities. The AHP method seems to be effective for this purpose. The decision algorithm developed by this method is more realistic and will improve the quality of the decision tree. Copyright © 2012 Elsevier B.V. All rights reserved.

Modeling and evaluation of the oil-spill emergency response capability based on linguistic variables.

PubMed

Kang, Jian; Zhang, Jixin; Bai, Yongqiang

2016-12-15

An evaluation of the oil-spill emergency response capability (OS-ERC) currently in place in modern marine management is required to prevent pollution and loss accidents. The objective of this paper is to develop a novel OS-ERC evaluation model, the importance of which stems from the current lack of integrated approaches for interpreting, ranking and assessing OS-ERC performance factors. In the first part of this paper, the factors influencing OS-ERC are analyzed and classified to generate a global evaluation index system. Then, a semantic tree is adopted to illustrate linguistic variables in the evaluation process, followed by the application of a combination of Fuzzy Cognitive Maps (FCM) and the Analytic Hierarchy Process (AHP) to construct and calculate the weight distribution. Finally, considering that the OS-ERC evaluation process is a complex system, a fuzzy comprehensive evaluation (FCE) is employed to calculate the OS-ERC level. The entire evaluation framework obtains the overall level of OS-ERC, and also highlights the potential major issues concerning OS-ERC, as well as expert opinions for improving the feasibility of oil-spill accident prevention and protection. Copyright © 2016 Elsevier Ltd. All rights reserved.

Priority Determination for Higher Education Strategic Planning Using Balanced Scorecard, FAHP and TOPSIS (Case study: XYZ University)

NASA Astrophysics Data System (ADS)

Yudatama, Uky; Sarno, Riyanarto

2016-01-01

The process of strategic planning is needed by a higher education in some cases, especially in preparing to face the challenges and competition. The results of strategic planning will help the higher education to provide a framework for achieving a competitive advantage as well as determine the direction of future policy in accordance with the desired objectives. In recent decades, the Balanced Scorecard has been applied in the field of information technology as a very popular tool and is used extensively, because it is a model that can explain between information technologies with "Business Objectives" in a comprehensive manner. This study uses 4 perspectives in the Balanced Scorecard and 7 standards in higher education quality assessment as sub-criteria. Fuzzy AHP and Fuzzy TOPSIS are used to determine the priority as making strategic policy recommendations in a higher education. The final result of this research shows the score of Customer Perspective 0.35365 is higher than other perspective, while the score in Research and Student Affairs gains significant score when compared with the others, namely 0.69753948 is also higher. This means that both of them get very serious attention as a strategic planning basis for policy making.

Hydrophilic interaction liquid chromatographic analysis of aminohydroxyphenylalanines from melanin pigments.

PubMed

Nezirević, Dzeneta; Arstrand, Kerstin; Kågedal, Bertil

2007-09-07

Malignant melanomas are more often seen in subjects with light colored skin who tan poorly than in persons who tan more rapidly. This has been attributed to the structure of their pigment, pheomelanin, which differs markedly from the eumelanin of persons with darker skin. To study the hydrolysis products of pheomelanin pigments a new method was developed for analysis of 4-amino-3-hydroxyphenylalanine (4-AHP) and 3-amino-4-hydroxyphenylalanine (3-AHP). Pheomelanin samples were hydrolyzed and extracted with solid-phase extraction columns using strong cation-exchange (SCX) cartridges. Separation of 4-AHP and 3-AHP was achieved on a ZIC-HILIC column (150 mm x 2.1mm I.D.) with a mobile phase consisting of acetonitrile: 0.1 M ammonium acetate buffer, pH 4.5 (82:18, v/v). Detection was performed with an electrochemical detector at +400 mV. Run time was 30 min. The limits of detection were 73 pg and 51 pg for 4-AHP and 3-AHP respectively, using 2 microl injections. Good linearity was found within the range 0.05-5.0 microg/ml. Absolute recovery was 70% and relative recovery was 100%. The AHPs were stable for 1 year in the hydrolyzed samples, for 4 days in the eluates from solid-phase sorbents stored in the refrigerator, and for 2 days diluted with mobile phase and stored in the autosampler at 10 degrees C. The within-day imprecision was <5% and the between-day imprecision was <7% for the two analytes. The method, applied to the analysis of pheomelanin in urine from human melanoma patients, allows the analysis of 30 samples in one set and is suitable for routine work with human hair and melanoma cells. By using the ZIC-HILIC stationary phase, ion-pairing reagents could be avoided, which makes the method suitable to further analysis of degradation products from pheomelanins using mass spectrometric detection.

Mapping the contribution of Allied Health Professions to the wider public health workforce: a rapid review of evidence-based interventions.

PubMed

Davis, S Fowler; Enderby, P; Harrop, D; Hindle, L

2017-03-01

The objective was to identify a selection of the best examples of the public health contributions by Allied Health Professionals (AHPs) in order to encourage a wider awareness and participation from that workforce to public health practice. A mapping exercise was used to identify evidence-based interventions that could lead to health improvements across a population. A rapid review was undertaken to identify evidence, followed by a survey of Allied Health Profession (AHP) practitioners and an expert panel consensus method to select the examples of AHP public health interventions. Nine evidence-based interventions are identified and selected as examples of current AHP good practice. These examples represent a contribution to public health and include screening interventions, secondary prevention and risk management. This study contributes to a strategy for AHPs in public health by appraising the effectiveness and impact of some exemplar AHP practices that contribute to health improvement. There is a need for AHPs to measure the impact of their interventions and to demonstrate evidence of outcomes at population level. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Selection of reference standard during method development using the analytical hierarchy process.

PubMed

Sun, Wan-yang; Tong, Ling; Li, Dong-xiang; Huang, Jing-yi; Zhou, Shui-ping; Sun, Henry; Bi, Kai-shun

2015-03-25

Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development. Copyright © 2015 Elsevier B.V. All rights reserved.

Application of a Cloud Model-Set Pair Analysis in Hazard Assessment for Biomass Gasification Stations.

PubMed

Yan, Fang; Xu, Kaili

2017-01-01

Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific.

Application of a Cloud Model-Set Pair Analysis in Hazard Assessment for Biomass Gasification Stations

PubMed Central

Yan, Fang; Xu, Kaili

2017-01-01

Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific. PMID:28076440

Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

PubMed Central

Alguliyev, Rasim M.; Aliguliyev, Ramiz M.; Mahmudova, Rasmiyya S.

2015-01-01

Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method. PMID:26516634

Solutions of interval type-2 fuzzy polynomials using a new ranking method

NASA Astrophysics Data System (ADS)

Rahman, Nurhakimah Ab.; Abdullah, Lazim; Ghani, Ahmad Termimi Ab.; Ahmad, Noor'Ani

2015-10-01

A few years ago, a ranking method have been introduced in the fuzzy polynomial equations. Concept of the ranking method is proposed to find actual roots of fuzzy polynomials (if exists). Fuzzy polynomials are transformed to system of crisp polynomials, performed by using ranking method based on three parameters namely, Value, Ambiguity and Fuzziness. However, it was found that solutions based on these three parameters are quite inefficient to produce answers. Therefore in this study a new ranking method have been developed with the aim to overcome the inherent weakness. The new ranking method which have four parameters are then applied in the interval type-2 fuzzy polynomials, covering the interval type-2 of fuzzy polynomial equation, dual fuzzy polynomial equations and system of fuzzy polynomials. The efficiency of the new ranking method then numerically considered in the triangular fuzzy numbers and the trapezoidal fuzzy numbers. Finally, the approximate solutions produced from the numerical examples indicate that the new ranking method successfully produced actual roots for the interval type-2 fuzzy polynomials.

Siting MSW landfill using weighted linear combination and analytical hierarchy process (AHP) methodology in GIS environment (case study: Karaj).

PubMed

Moeinaddini, Mazaher; Khorasani, Nematollah; Danehkar, Afshin; Darvishsefat, Ali Asghar; Zienalyan, Mehdi

2010-05-01

Selection of landfill site is a complex process and needs many diverse criteria. The purpose of this paper is to evaluate the suitability of the studied site as landfill for MSW in Karaj. Using weighted linear combination (WLC) method and spatial cluster analysis (SCA), suitable sites for allocation of landfill for a 20-year period were identified. For analyzing spatial auto-correlation of the land suitability map layer (LSML), Maron's I was used. Finally, using the analytical hierarchy process (AHP), the most preferred alternative for the landfill siting was identified. Main advantages of AHP are: relative ease of handling multiple criteria, easy to understand and effective handling of both qualitative and quantitative data. As a result, 6% of the study area is suitable for landfill siting and third alternative was identified as the most preferred for siting MSW landfill by AHP. The ranking of alternatives were obtained only by applying the WLC approach showed different results from the AHP. The WLC should be used only for the identification of alternatives and the AHP is used for prioritization. We suggest the employed procedure for other similar regions. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Influence of alkaline hydrogen peroxide pre-hydrolysis on the isolation of microcrystalline cellulose from oil palm fronds.

PubMed

Owolabi, Abdulwahab F; Haafiz, M K Mohamad; Hossain, Md Sohrab; Hussin, M Hazwan; Fazita, M R Nurul

2017-02-01

In the present study, microcrystalline cellulose (MCC) was isolated from oil palm fronds (OPF) using chemo-mechanical process. Wherein, alkaline hydrogen peroxide (AHP) was utilized to extract OPF fibre at different AHP concentrations. The OPF pulp fibre was then bleached with acidified sodium chlorite solution followed by the acid hydrolysis using hydrochloric acid. Several analytical methods were conducted to determine the influence of AHP concentration on thermal properties, morphological properties, microscopic and crystalline behaviour of isolated MCC. Results showed that the MCC extracted from OPF fibres had fibre diameters of 7.55-9.11nm. X-ray diffraction (XRD) analyses revealed that the obtained microcrystalline fibre had both celluloses I and cellulose II polymorphs structure, depending on the AHP concentrations. The Fourier transmission infrared (FTIR) analyses showed that the AHP pre-hydrolysis was successfully removed hemicelluloses and lignin from the OPF fibre. The crystallinity of the MCC was increased with the AHP concentrations. The degradation temperature of MCC was about 300°C. The finding of the present study showed that pre-treatment process potentially influenced the quality of the isolation of MCC from oil palm fronds. Copyright © 2016 Elsevier B.V. All rights reserved.

Insights into the Function of a Second, Nonclassical Ahp Peroxidase, AhpA, in Oxidative Stress Resistance in Bacillus subtilis

PubMed Central

Broden, Nicole J.; Flury, Sarah; King, Alyssa N.; Schroeder, Braden W.; Coe, Gabrielle Dierker

2016-01-01

ABSTRACT Organisms growing aerobically generate reactive oxygen-containing molecules, such as hydrogen peroxide (H2O2). These reactive oxygen molecules damage enzymes and DNA and may even cause cell death. In response, Bacillus subtilis produces at least nine potential peroxide-scavenging enzymes, two of which appear to be the primary enzymes responsible for detoxifying peroxides during vegetative growth: a catalase (encoded by katA) and an alkylhydroperoxide reductase (Ahp, encoded by ahpC). AhpC uses two redox-active cysteine residues to reduce peroxides to nontoxic molecules. A specialized thioredoxin-like protein, AhpF, is then required to restore oxidized AhpC back to its reduced state. Curiously, B. subtilis has two genes encoding Ahp: ahpC and ahpA. Although AhpC is well characterized, very little is known about AhpA. In fact, numerous bacterial species have multiple ahp genes; however, these additional Ahp proteins are generally uncharacterized. We seek to understand the role of AhpA in the bacterium's defense against toxic peroxide molecules in relation to the roles previously assigned to AhpC and catalase. Our results demonstrate that AhpA has catalytic activity similar to that of the primary enzyme, AhpC. Furthermore, our results suggest that a unique thioredoxin redox protein, AhpT, may reduce AhpA upon its oxidation by peroxides. However, unlike AhpC, which is expressed well during vegetative growth, our results suggest that AhpA is expressed primarily during postexponential growth. IMPORTANCE B. subtilis appears to produce nine enzymes designed to protect cells against peroxides; two belong to the Ahp class of peroxidases. These studies provide an initial characterization of one of these Ahp homologs and demonstrate that the two Ahp enzymes are not simply replicates of each other, suggesting that they instead are expressed at different times during growth of the cells. These results highlight the need to further study the Ahp homologs to better understand how they differ from one another and to identify their function, if any, in protection against oxidative stress. Through these studies, we may better understand why bacteria have multiple enzymes designed to scavenge peroxides and thus have a more accurate understanding of oxidative stress resistance. PMID:26787766

Using AHP to analyze and ascertain the priority protective order of endangered plants in East Alashan-West Erdos

NASA Astrophysics Data System (ADS)

Tao, Zhang; Wei, Wang; Wang, Gary Z.; Luo, Hongyan; Liang, Cunzhu; Liu, Jiahui; An, Huijun; Pei, Hao; Zhong, Huidong; Chen, Xiaojun

2006-08-01

AHP is a kind of very effective systematic analytical method, widely applied to energy utilizing and resource analyzing, talent predicting, economic management project, urban industries planning, communications and transportation, water resource using and so on, using this method to solve the problem of ecology also have very strong practicability and validity. Using 15 kinds of endured plants in East Alashan-West Erdos as the research objects, this paper adopts 3S technique and outfield investigates to confirm the geographical distributions, extent density in the distribution area, plant community construction, and plant community environment of the plants. Then invite the experts to give marks according to this datum and using the AHP method to deal with the results, thereby get the priority protective order of endangered plants in East Alashan-West Erdos.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

Solving the interval type-2 fuzzy polynomial equation using the ranking method

NASA Astrophysics Data System (ADS)

Rahman, Nurhakimah Ab.; Abdullah, Lazim

2014-07-01

Polynomial equations with trapezoidal and triangular fuzzy numbers have attracted some interest among researchers in mathematics, engineering and social sciences. There are some methods that have been developed in order to solve these equations. In this study we are interested in introducing the interval type-2 fuzzy polynomial equation and solving it using the ranking method of fuzzy numbers. The ranking method concept was firstly proposed to find real roots of fuzzy polynomial equation. Therefore, the ranking method is applied to find real roots of the interval type-2 fuzzy polynomial equation. We transform the interval type-2 fuzzy polynomial equation to a system of crisp interval type-2 fuzzy polynomial equation. This transformation is performed using the ranking method of fuzzy numbers based on three parameters, namely value, ambiguity and fuzziness. Finally, we illustrate our approach by numerical example.

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

Fuzzy forecasting based on fuzzy-trend logical relationship groups.

PubMed

Chen, Shyi-Ming; Wang, Nai-Yi

2010-10-01

In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

Use of the Analytic Hierarchy Process for Medication Decision-Making in Type 2 Diabetes

PubMed Central

Maruthur, Nisa M.; Joy, Susan M.; Dolan, James G.; Shihab, Hasan M.; Singh, Sonal

2015-01-01

Aim To investigate the feasibility and utility of the Analytic Hierarchy Process (AHP) for medication decision-making in type 2 diabetes. Methods We conducted an AHP with nine diabetes experts using structured interviews to rank add-on therapies (to metformin) for type 2 diabetes. During the AHP, participants compared treatment alternatives relative to eight outcomes (hemoglobin A1c-lowering and seven potential harms) and the relative importance of the different outcomes. The AHP model and instrument were pre-tested and pilot-tested prior to use. Results were discussed and an evaluation of the AHP was conducted during a group session. We conducted the quantitative analysis using Expert Choice software with the ideal mode to determine the priority of treatment alternatives. Results Participants judged exenatide to be the best add-on therapy followed by sitagliptin, sulfonylureas, and then pioglitazone. Maximizing benefit was judged 21% more important than minimizing harm. Minimizing severe hypoglycemia was judged to be the most important harm to avoid. Exenatide was the best overall alternative if the importance of minimizing harms was prioritized completely over maximizing benefits. Participants reported that the AHP improved transparency, consistency, and an understanding of others’ perspectives and agreed that the results reflected the views of the group. Conclusions The AHP is feasible and useful to make decisions about diabetes medications. Future studies which incorporate stakeholder preferences should evaluate other decision contexts, objectives, and treatments. PMID:26000636

Optimal solution of full fuzzy transportation problems using total integral ranking

NASA Astrophysics Data System (ADS)

Sam’an, M.; Farikhin; Hariyanto, S.; Surarso, B.

2018-03-01

Full fuzzy transportation problem (FFTP) is a transportation problem where transport costs, demand, supply and decision variables are expressed in form of fuzzy numbers. To solve fuzzy transportation problem, fuzzy number parameter must be converted to a crisp number called defuzzyfication method. In this new total integral ranking method with fuzzy numbers from conversion of trapezoidal fuzzy numbers to hexagonal fuzzy numbers obtained result of consistency defuzzyfication on symmetrical fuzzy hexagonal and non symmetrical type 2 numbers with fuzzy triangular numbers. To calculate of optimum solution FTP used fuzzy transportation algorithm with least cost method. From this optimum solution, it is found that use of fuzzy number form total integral ranking with index of optimism gives different optimum value. In addition, total integral ranking value using hexagonal fuzzy numbers has an optimal value better than the total integral ranking value using trapezoidal fuzzy numbers.

The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.

PubMed

Narayanamoorthy, S; Kalyani, S

2015-01-01

An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.

A combined approach based on MAF analysis and AHP method to fault detection mapping: A case study from a gas field, southwest of Iran

NASA Astrophysics Data System (ADS)

Shakiba, Sima; Asghari, Omid; Khah, Nasser Keshavarz Faraj

2018-01-01

A combined geostatitical methodology based on Min/Max Auto-correlation Factor (MAF) analysis and Analytical Hierarchy Process (AHP) is presented to generate a suitable Fault Detection Map (FDM) through seismic attributes. Five seismic attributes derived from a 2D time slice obtained from data related to a gas field located in southwest of Iran are used including instantaneous amplitude, similarity, energy, frequency, and Fault Enhancement Filter (FEF). The MAF analysis is implemented to reduce dimension of input variables, and then AHP method is applied on three obtained de-correlated MAF factors as evidential layer. Three Decision Makers (DMs) are used to construct PCMs for determining weights of selected evidential layer. Finally, weights obtained by AHP were multiplied in normalized valued of each alternative (MAF layers) and the concluded weighted layers were integrated in order to prepare final FDM. Results proved that applying algorithm proposed in this study generate a map more acceptable than the each individual attribute and sharpen the non-surface discontinuities as well as enhancing continuity of detected faults.

Research on AHP decision algorithms based on BP algorithm

NASA Astrophysics Data System (ADS)

Ma, Ning; Guan, Jianhe

2017-10-01

Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.

Evaluation System and Implementation Countermeasure of Automobile Green Maintenance

NASA Astrophysics Data System (ADS)

Zhang, Fei; Xie, Xinxin; Yan, Chaoyong

2018-01-01

Green maintenance research is in the beginning of our country, the work is being explored. Based on the existing research results at home and abroad, this paper learns and draws lessons from the experiences and lessons of foreign advanced countries and domestic advanced enterprises. In the face of the challenges brought by economic development and energy saving and emission reduction, this paper discusses the green maintenance theory and security system, And the research status of green maintenance content and system at home and abroad, through the deletion and selection of green maintenance index, through the AHP method to determine the green evaluation criteria, and the introduction of C equivalent evaluation system, the use of fuzzy synthesis Evaluation method to build a green maintenance evaluation model, and the actual validation, put forward the implementation of green maintenance feasibility programs and related security recommendations, vehicle maintenance enterprises to carry out green maintenance, improve business efficiency and reduce environmental management costs to provide theoretical basis. And to achieve effective reduction of environmental pollution, reduce maintenance costs of the target, a reasonable promotion of maintenance and environmental protection and sustainable development. Promote green maintenance from research to practice, from the laboratory to the maintenance of enterprises, from the pilot to the overall development and transformation.

The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem

PubMed Central

Narayanamoorthy, S.; Kalyani, S.

2015-01-01

An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example. PMID:25810713

Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

PubMed

Chen, Shyi-Ming; Chen, Shen-Wen

2015-03-01

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

Yager’s ranking method for solving the trapezoidal fuzzy number linear programming

NASA Astrophysics Data System (ADS)

Karyati; Wutsqa, D. U.; Insani, N.

2018-03-01

In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.

A hybrid design methodology for structuring an Integrated Environmental Management System (IEMS) for shipping business.

PubMed

Celik, Metin

2009-03-01

The International Safety Management (ISM) Code defines a broad framework for the safe management and operation of merchant ships, maintaining high standards of safety and environmental protection. On the other hand, ISO 14001:2004 provides a generic, worldwide environmental management standard that has been utilized by several industries. Both the ISM Code and ISO 14001:2004 have the practical goal of establishing a sustainable Integrated Environmental Management System (IEMS) for shipping businesses. This paper presents a hybrid design methodology that shows how requirements from both standards can be combined into a single execution scheme. Specifically, the Analytic Hierarchy Process (AHP) and Fuzzy Axiomatic Design (FAD) are used to structure an IEMS for ship management companies. This research provides decision aid to maritime executives in order to enhance the environmental performance in the shipping industry.

Fuzzy Comprehensive Evaluation of Rural Information Poverty in China - - Case Study of Hebei Province

NASA Astrophysics Data System (ADS)

Sun, Guizhen; Wang, Shuanjun; Li, Yaqing; Wang, Huijun

Information poverty is a new form of poverty in information society. With the growing information-gap between urban and rural areas, information poverty is prevailing in the vast rural areas in China. It is largely restricted the new rural construction and the social harmonious development of villages and towns and must be resolved. The evaluation of rural information poverty is the premise to resolve it. In order to estimate the problem, index system of rural informatization evaluation of Hebei province was designed by means of Delphi. Then, according to the survey of farmers' information demand, AHP and FCE were used to estimate rural information poverty of Hebei province. The purpose of this study is to provide a new operational approach in evaluating or solving rural information poverty and constructing rural informatization in China.

A combined approach of AHP and TOPSIS methods applied in the field of integrated software systems

NASA Astrophysics Data System (ADS)

Berdie, A. D.; Osaci, M.; Muscalagiu, I.; Barz, C.

2017-05-01

Adopting the most appropriate technology for developing applications on an integrated software system for enterprises, may result in great savings both in cost and hours of work. This paper proposes a research study for the determination of a hierarchy between three SAP (System Applications and Products in Data Processing) technologies. The technologies Web Dynpro -WD, Floorplan Manager - FPM and CRM WebClient UI - CRM WCUI are multi-criteria evaluated in terms of the obtained performances through the implementation of the same web business application. To establish the hierarchy a multi-criteria analysis model that combines the AHP (Analytic Hierarchy Process) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods was proposed. This model was built with the help of the SuperDecision software. This software is based on the AHP method and determines the weights for the selected sets of criteria. The TOPSIS method was used to obtain the final ranking and the technologies hierarchy.

Selection of infectious medical waste disposal firms by using the analytic hierarchy process and sensitivity analysis.

PubMed

Hsu, Pi-Fang; Wu, Cheng-Ru; Li, Ya-Ting

2008-01-01

While Taiwanese hospitals dispose of large amounts of medical waste to ensure sanitation and personal hygiene, doing so inefficiently creates potential environmental hazards and increases operational expenses. However, hospitals lack objective criteria to select the most appropriate waste disposal firm and evaluate its performance, instead relying on their own subjective judgment and previous experiences. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select medical waste disposal firms based on the results of interviews with experts in the field, thus reducing overhead costs and enhancing medical waste management. An appropriate weight criterion based on AHP is derived to assess the effectiveness of medical waste disposal firms. The proposed AHP-based method offers a more efficient and precise means of selecting medical waste firms than subjective assessment methods do, thus reducing the potential risks for hospitals. Analysis results indicate that the medical sector selects the most appropriate infectious medical waste disposal firm based on the following rank: matching degree, contractor's qualifications, contractor's service capability, contractor's equipment and economic factors. By providing hospitals with an effective means of evaluating medical waste disposal firms, the proposed AHP method can reduce overhead costs and enable medical waste management to understand the market demand in the health sector. Moreover, performed through use of Expert Choice software, sensitivity analysis can survey the criterion weight of the degree of influence with an alternative hierarchy.

Collaborative decision-making on wind power projects based on AHP method

NASA Astrophysics Data System (ADS)

Badea, A.; Proştean, G.; Tămăşilă, M.; Vârtosu, A.

2017-01-01

The complexity of projects implementation in Renewable Energy Sources (RES) requires finding collaborative alliances between suppliers and project developers in RES. Links activities in supply chain in RES, respectively, transportation of heavy components, processing orders to purchase quality raw materials, storage and materials handling, packaging, and other complex activities requiring a logistics system collaboratively to be permanently dimensioned properly selected and monitored. Requirements imposed by stringency of wind power energy projects implementation inevitably involves constraints in infrastructure, implementation and logistics. Thus, following an extensive research in RES project, to eliminate these constraints were identified alternative collaboration to provide feasible solutions on different levels of performance. The paper presents a critical analysis of different collaboration alternatives in supply chain for RES projects, selecting the ones most suitable for particular situations by using decision-making method Analytic Hierarchy Process (AHP). The role of AHP method was to formulate a decision model by which can be establish the collaboration alternative choice through mathematical calculation to reduce the impact created by constraints encountered. The solution provided through AHP provides a framework for detecting optimal alternative collaboration between suppliers and project developers in RES and avoids some breaks in the chain by resizing safety buffers for leveling orders in RES projects.

A duality approach for solving bounded linear programming problems with fuzzy variables based on ranking functions and its application in bounded transportation problems

NASA Astrophysics Data System (ADS)

Ebrahimnejad, Ali

2015-08-01

There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.

A head-to-head comparison of hydrogen peroxide vapor and aerosol room decontamination systems.

PubMed

Holmdahl, T; Lanbeck, P; Wullt, M; Walder, M H

2011-09-01

New technologies have emerged in recent years for the disinfection of hospital rooms and equipment that may not be disinfected adequately using conventional methods. There are several hydrogen peroxide-based area decontamination technologies on the market, but no head-to-head studies have been performed. We conducted a head-to-head in vitro comparison of a hydrogen peroxide vapor (HPV) system (Bioquell) and an aerosolized hydrogen peroxide (aHP) system (Sterinis). The tests were conducted in a purpose-built 136-m(3) test room. One HPV generator and 2 aHP machines were used, following recommendations of the manufacturers. Three repeated tests were performed for each system. The microbiological efficacy of the 2 systems was tested using 6-log Tyvek-pouched Geobacillus stearothermophilus biological indicators (BIs). The indicators were placed at 20 locations in the first test and 14 locations in the subsequent 2 tests for each system. All BIs were inactivated for the 3 HPV tests, compared with only 10% in the first aHP test and 79% in the other 2 aHP tests. The peak hydrogen peroxide concentration was 338 ppm for HPV and 160 ppm for aHP. The total cycle time (including aeration) was 3 and 3.5 hours for the 3 HPV tests and the 3 aHP tests, respectively. Monitoring around the perimeter of the enclosure with a handheld sensor during tests of both systems did not identify leakage. One HPV generator was more effective than 2 aHP machines for the inactivation of G. stearothermophilus BIs, and cycle times were faster for the HPV system.

Method of fuzzy inference for one class of MISO-structure systems with non-singleton inputs

NASA Astrophysics Data System (ADS)

Sinuk, V. G.; Panchenko, M. V.

2018-03-01

In fuzzy modeling, the inputs of the simulated systems can receive both crisp values and non-Singleton. Computational complexity of fuzzy inference with fuzzy non-Singleton inputs corresponds to an exponential. This paper describes a new method of inference, based on the theorem of decomposition of a multidimensional fuzzy implication and a fuzzy truth value. This method is considered for fuzzy inputs and has a polynomial complexity, which makes it possible to use it for modeling large-dimensional MISO-structure systems.

Arabidopsis Response Regulator1 and Arabidopsis Histidine Phosphotransfer Protein2 (AHP2), AHP3, and AHP5 Function in Cold Signaling1[W][OA

PubMed Central

Jeon, Jin; Kim, Jungmook

2013-01-01

The Arabidopsis (Arabidopsis thaliana) two-component signaling system, which is composed of sensor histidine kinases, histidine phosphotransfer proteins, and response regulators, mediates the cytokinin response and various other plant responses. We have previously shown that ARABIDOPSIS HISTIDINE KINASE2 (AHK2), AHK3, and cold-inducible type A ARABIDOPSIS RESPONSE REGULATORS (ARRs) play roles in cold signaling. However, the roles of type B ARRs and ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEINS (AHPs) have not been investigated in cold signaling. Here, we show that ARR1 and AHP2, AHP3, and AHP5 play positive roles in the cold-inducible expression of type A ARRs. arr1 mutants showed greatly reduced cold-responsive expression of type A ARRs compared with the wild type, whereas ARR1-overexpressing Arabidopsis exhibited the hypersensitive cold response of type A ARRs as well as enhanced freezing tolerance with cytokinin, suggesting that ARR1 functions as a positive factor of cold signaling. Transgenic Arabidopsis expressing ARR1ΔDDK:GR lacking the amino-terminal receiver domain showed wild-type expression levels of type A ARRs in response to cold, indicating that the signal receiver domain of ARR1 might be important for cold-responsive expression of type A ARRs. ahp2 ahp3 ahp5 triple mutations greatly reduced type A ARR expression in response to cold, whereas the single or double ahp mutants displayed wild-type levels of ARR expression, suggesting that AHP2, AHP3, and AHP5 are redundantly involved in cold signaling. Taken together, these results suggest that ARR1 mediates cold signal via AHP2, AHP3, or AHP5 from AHK2 and AHK3 to express type A ARRs. We further identified a cold transcriptome affected by ahk2 ahk3 mutations by microarray analysis, revealing a new cold-responsive gene network regulated downstream of AHK2 and AHK3. PMID:23124324

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.

PubMed

Li, Pu; Chen, Bing

2011-04-01

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.

AhpA is a peroxidase expressed during biofilm formation in Bacillus subtilis.

PubMed

Zwick, Joelie V; Noble, Sarah; Ellaicy, Yasser K; Coe, Gabrielle Dierker; Hakey, Dylan J; King, Alyssa N; Sadauskas, Alex J; Faulkner, Melinda J

2017-02-01

Organisms growing aerobically generate reactive oxygen species such as hydrogen peroxide. These reactive oxygen molecules damage enzymes and DNA, potentially causing cell death. In response, Bacillus subtilis produces at least nine potential peroxide-scavenging enzymes; two belong to the alkylhydroperoxide reductase (Ahp) class of peroxidases. Here, we explore the role of one of these Ahp homologs, AhpA. While previous studies demonstrated that AhpA can scavenge peroxides and thus defend cells against peroxides, they did not clarify when during growth the cell produces AhpA. The results presented here show that the expression of ahpA is regulated in a manner distinct from that of the other peroxide-scavenging enzymes in B. subtilis. While the primary Ahp, AhpC, is expressed during exponential growth and stationary phase, these studies demonstrate that the expression of ahpA is dependent on the transition-state regulator AbrB and the sporulation and biofilm formation transcription factor Spo0A. Furthermore, these results show that ahpA is specifically expressed during biofilm formation, and not during sporulation or stationary phase, suggesting that derepression of ahpA by AbrB requires a signal other than those present upon entry into stationary phase. Despite this expression pattern, ahpA mutant strains still form and maintain robust biofilms, even in the presence of peroxides. Thus, the role of AhpA with regard to protecting cells within biofilms from environmental stresses is still uncertain. These studies highlight the need to further study the Ahp homologs to better understand how they differ from one another and the unique roles they may play in oxidative stress resistance. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Prediction of Floor Water Inrush: The Application of GIS-Based AHP Vulnerable Index Method to Donghuantuo Coal Mine, China

NASA Astrophysics Data System (ADS)

Wu, Qiang; Liu, Yuanzhang; Liu, Donghai; Zhou, Wanfang

2011-09-01

Floor water inrush represents a geohazard that can pose significant threat to safe operations for instance in coal mines in China and elsewhere. Its occurrence is controlled by many factors, and the processes are often not amenable to mathematical expressions. To evaluate the water inrush risk, the paper proposes the vulnerability index approach by coupling the analytic hierarchy process (AHP) and geographic information system (GIS). The detailed procedures of using this innovative approach are shown in a case study in China (Donghuantuo Coal Mine). The powerful spatial data analysis functions of GIS was used to establish the thematic layer of each of the six factors that control the water inrush, and the contribution weights of each factor was determined with the AHP method. The established AHP evaluation model was used to determine the threshold value for each risk level with a histogram of the water inrush vulnerability index. As a result, the mine area was divided into five regions with different vulnerability levels which served as general guidelines for the mine operations. The prediction results were further corroborated with the actual mining data, and the evaluation result is satisfactory.

Implementation of Steiner point of fuzzy set.

PubMed

Liang, Jiuzhen; Wang, Dejiang

2014-01-01

This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

Efficacy of accelerated hydrogen peroxide® disinfectant on foot-and-mouth disease virus, swine vesicular disease virus and Senecavirus A.

PubMed

Hole, K; Ahmadpour, F; Krishnan, J; Stansfield, C; Copps, J; Nfon, C

2017-03-01

In a laboratory, disinfectants used to inactivate pathogens on contaminated surfaces and to prevent spread of diseases often have adverse side effects on personnel and the environment. It is, therefore, essential to find safer, fast-acting and yet effective disinfectants. The objective of this study was to evaluate an accelerated hydrogen peroxide ® (AHP ® )-based disinfectant against high consequence foreign animal disease pathogens such as foot-and-mouth disease virus (FMDV) and swine vesicular disease virus (SVDV), as well as Senecavirus A (SVA), which causes similar lesions as FMDV and SVDV. We tested varying dilutions and contact times of AHP against FMDV, SVDV and SVA by the standard US EPA and modified methods. AHP was effective against all three viruses, albeit at a higher concentration and double the manufacturer recommended contact time when testing wet films of SVDV. AHP is an effective disinfectant against FMDV, SVDV and SVA. AHP-based disinfectant can, therefore, be used in high containment laboratories working with FMDV, SVDV and related pathogens. © 2016 The Canadian Food Inspection Agency. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology.

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Paskibraka Member Selection Using A Combination Of AHP and TOPSIS Methods On The Office Of Youth And Sports Of Kutai Kartanegara Regency

NASA Astrophysics Data System (ADS)

Maharani, Septya; Hatta, Heliza Rahmania; Anzhari, Afif Nur; Khairina, Dyna Marisa

2018-02-01

Paskibraka as troops whose job is to flap the heritage duplicates flag. To become a Paskibraka a selection that participants are high school students are made. Because the number of participants of the selection of many support systems to facilitate the assessment process is made. This system uses Analytical Hierarchy Process (AHP) to determine the weight value criteria that comprise the value of the interview, health, physical, .height and value rules for marching as well as using Technique For Others Preference by Similarity to Ideal Solution (TOPSIS) methods to seek best alternative participants. The calculation results of 21 alternative names best male and female of the participants and their school origin. The system has also been tested by performing the calculations manually using Microsoft Excel (Ms.Excel) to calculate the calculation of the system using AHP and TOPSIS.

Selection of infectious medical waste disposal firms by using the analytic hierarchy process and sensitivity analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hsu, P.-F.; Wu, C.-R.; Li, Y.-T.

2008-07-01

While Taiwanese hospitals dispose of large amounts of medical waste to ensure sanitation and personal hygiene, doing so inefficiently creates potential environmental hazards and increases operational expenses. However, hospitals lack objective criteria to select the most appropriate waste disposal firm and evaluate its performance, instead relying on their own subjective judgment and previous experiences. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select medical waste disposal firms based on the results of interviews with experts in the field, thus reducing overhead costs and enhancing medical waste management. An appropriate weight criterion based on AHP is derivedmore » to assess the effectiveness of medical waste disposal firms. The proposed AHP-based method offers a more efficient and precise means of selecting medical waste firms than subjective assessment methods do, thus reducing the potential risks for hospitals. Analysis results indicate that the medical sector selects the most appropriate infectious medical waste disposal firm based on the following rank: matching degree, contractor's qualifications, contractor's service capability, contractor's equipment and economic factors. By providing hospitals with an effective means of evaluating medical waste disposal firms, the proposed AHP method can reduce overhead costs and enable medical waste management to understand the market demand in the health sector. Moreover, performed through use of Expert Choice software, sensitivity analysis can survey the criterion weight of the degree of influence with an alternative hierarchy.« less

Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment (case study: Garabaygan Basin, Iran).

PubMed

Nasiri, Hossein; Boloorani, Ali Darvishi; Sabokbar, Hassan Ali Faraji; Jafari, Hamid Reza; Hamzeh, Mohamad; Rafii, Yusef

2013-01-01

Flood spreading is a suitable strategy for controlling and benefiting from floods. Selecting suitable areas for flood spreading and directing the floodwater into permeable formations are amongst the most effective strategies in flood spreading projects. Having combined geographic information systems (GIS) and multi-criteria decision analysis approaches, the present study sought to locate the most suitable areas for flood spreading operation in the Garabaygan Basin of Iran. To this end, the data layers relating to the eight effective factors were prepared in GIS environment. This stage was followed by elimination of the exclusionary areas for flood spreading while determining the potentially suitable ones. Having closely examined the potentially suitable areas using the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II and analytic hierarchy process (AHP) methods, the land suitability map for flood spreading was produced. The PROMETHEE II and AHP were used for ranking all the alternatives and weighting the criteria involved, respectively. The results of the study showed that most suitable areas for the artificial groundwater recharge are located in Quaternary Q(g) and Q(gsc) geologic units and in geomorphological units of pediment and Alluvial fans with slopes not exceeding 3%. Furthermore, significant correspondence between the produced map and the control areas, where the flood spreading projects were successfully performed, provided further evidence for the acceptable efficiency of the integrated PROMETHEE II-AHP method in locating suitable flood spreading areas.

Using fuzzy fractal features of digital images for the material surface analisys

NASA Astrophysics Data System (ADS)

Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

2018-01-01

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

Acute hypopituitarism complicating Russell's viper envenomation: case series and systematic review.

PubMed

Rajagopala, S; Thabah, M M; Ariga, K K; Gopalakrishnan, M

2015-09-01

Chronic hypopituitarism following Russell viper envenomation (RVE) is a rare but well-recognized syndrome. The clinical features, associations, management and outcomes of RVE associated-acute hypopituitarism (AHP) are not well described. To describe the clinical features, intensive care unit (ICU) management and outcomes of a series of patients with RVE-AHP and identify the clinical associations of RVE-AHP. We describe a series of patients with prospectively identified AHP related to RVE and describe our findings comparing RVE with and without AHP and a systematic search of literature on AHP related to RVE. We identified nine cases of AHP related to RVE. Unexplained hypoglycemia (100%) and hypotension (66.7%) were the most common findings at presentation. AHP occurred after a median of 9 (range, 2-14) days after severe envenomation and was associated with multi-organ dysfunction, lower platelet counts, more bleeding and transfusions when compared to patients with RVE alone. The presence of clinically defined capillary leak syndrome, disseminated intravascular coagulation and mortality were not different from those without AHP. Our systematic search yielded 12 cases of AHP related to RVE; data on associated clinical manifestations, therapy and ASV administration were not available in most reports. AHP is a very rare complication of RVE. Unexplained hypoglycemia and hypotension should prompt evaluation for AHP in RVE. AHP is associated with severe RVE, multi-organ dysfunction, bleeding and need for transfusion. Prompt treatment with steroids may reduce mortality related to AHP in RVE. © The Author 2015. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

NASA Astrophysics Data System (ADS)

Indarsih, Indrati, Ch. Rini

2016-02-01

In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

[Spatiotemporal dynamic fuzzy evaluation of wetland environmental pollution risk in Dayang estuary of Liaoning Province, Northeast China based on remote sensing].

PubMed

Sun, Yong-Guang; Zhao, Dong-Zhi; Zhang, Feng-Shou; Wei, Bao-Quan; Chu, Jia-Lan; Su, Xiu

2012-11-01

Based on the aerial image data of Dayang estuary in 2008, and by virtue of Analytic Hierarchy Process (AHP) , remote sensing technology, and GIS spatial analysis, a spatiotemporal evaluation was made on the comprehensive level of wetland environmental pollution risk in Dayang estuary, with the impacts of typical human activities on the dynamic variation of this comprehensive level discussed. From 1958 to 2008, the comprehensive level of the environmental pollution risk in study area presented an increasing trend. Spatially, this comprehensive level declined from land to ocean, and showed a zonal distribution. Tourism development activities unlikely led to the increase of the comprehensive level, while human inhabitation, transportation, and aquaculture would exacerbate the risk of environmental pollution. This study could provide reference for the sea area use planning, ecological function planning, and pollutants control of estuary region.

Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

NASA Astrophysics Data System (ADS)

Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

2017-08-01

Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

Modelling a suitable location for Urban Solid Waste Management using AHP method and GIS -A geospatial approach and MCDM Model

NASA Astrophysics Data System (ADS)

Iqbal, M.; Islam, A.; Hossain, A.; Mustaque, S.

2016-12-01

Multi-Criteria Decision Making(MCDM) is advanced analytical method to evaluate appropriate result or decision from multiple criterion environment. Present time in advanced research, MCDM technique is progressive analytical process to evaluate a logical decision from various conflict. In addition, Present day Geospatial approach (e.g. Remote sensing and GIS) also another advanced technical approach in a research to collect, process and analyze various spatial data at a time. GIS and Remote sensing together with the MCDM technique could be the best platform to solve a complex decision making process. These two latest process combined very effectively used in site selection for solid waste management in urban policy. The most popular MCDM technique is Weighted Linear Method (WLC) where Analytical Hierarchy Process (AHP) is another popular and consistent techniques used in worldwide as dependable decision making. Consequently, the main objective of this study is improving a AHP model as MCDM technique with Geographic Information System (GIS) to select a suitable landfill site for urban solid waste management. Here AHP technique used as a MCDM tool to select the best suitable landfill location for urban solid waste management. To protect the urban environment in a sustainable way municipal waste needs an appropriate landfill site considering environmental, geological, social and technical aspect of the region. A MCDM model generate from five class related which related to environmental, geological, social and technical using AHP method and input the result set in GIS for final model location for urban solid waste management. The final suitable location comes out that 12.2% of the area corresponds to 22.89 km2 considering the total study area. In this study, Keraniganj sub-district of Dhaka district in Bangladesh is consider as study area which is densely populated city currently undergoes an unmanaged waste management system especially the suitable landfill sites for waste dumping site.

Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.

PubMed

Carrascal, A; Manrique, D; Ríos, J; Rossi, C

2003-01-01

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques.

PubMed

Chen, Shyi-Ming; Manalu, Gandhi Maruli Tua; Pan, Jeng-Shyang; Liu, Hsiang-Chuan

2013-06-01

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization (PSO) techniques. First, we fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors second-order fuzzy logical relationships. Then, we group the two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, we obtain the optimal weighting vector for each fuzzy-trend logical relationship group by using PSO techniques to perform the forecasting. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index and the NTD/USD exchange rates. The experimental results show that the proposed method gets better forecasting performance than the existing methods.

Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions

PubMed Central

Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi

2015-01-01

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models. PMID:25775452

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research

PubMed Central

Singh, Sonal

2013-01-01

Background: Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  Methods: This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Discussion: Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences. PMID:24555077

A fuzzy inventory model with acceptable shortage using graded mean integration value method

NASA Astrophysics Data System (ADS)

Saranya, R.; Varadarajan, R.

2018-04-01

In many inventory models uncertainty is due to fuzziness and fuzziness is the closed possible approach to reality. In this paper, we proposed a fuzzy inventory model with acceptable shortage which is completely backlogged. We fuzzily the carrying cost, backorder cost and ordering cost using Triangular and Trapezoidal fuzzy numbers to obtain the fuzzy total cost. The purpose of our study is to defuzzify the total profit function by Graded Mean Integration Value Method. Further a numerical example is also given to demonstrate the developed crisp and fuzzy models.

Health Care Professionals’ Beliefs About Using Wiki-Based Reminders to Promote Best Practices in Trauma Care

PubMed Central

Bilodeau, Andrea; Gagnon, Marie-Pierre; Aubin, Karine; Lavoie, André; Lapointe, Jean; Poitras, Julien; Croteau, Sylvain; Pham-Dinh, Martin; Légaré, France

2012-01-01

Background Wikis are knowledge translation tools that could help health professionals implement best practices in acute care. Little is known about the factors influencing professionals’ use of wikis. Objectives To identify and compare the beliefs of emergency physicians (EPs) and allied health professionals (AHPs) about using a wiki-based reminder that promotes evidence-based care for traumatic brain injuries. Methods Drawing on the theory of planned behavior, we conducted semistructured interviews to elicit EPs’ and AHPs’ beliefs about using a wiki-based reminder. Previous studies suggested a sample of 25 EPs and 25 AHPs. We purposefully selected participants from three trauma centers in Quebec, Canada, to obtain a representative sample. Using univariate analyses, we assessed whether our participants’ gender, age, and level of experience were similar to those of all eligible individuals. Participants viewed a video showing a clinician using a wiki-based reminder, and we interviewed participants about their behavioral, control, and normative beliefs—that is, what they saw as advantages, disadvantages, barriers, and facilitators to their use of a reminder, and how they felt important referents would perceive their use of a reminder. Two reviewers independently analyzed the content of the interview transcripts. We considered the 75% most frequently mentioned beliefs as salient. We retained some less frequently mentioned beliefs as well. Results Of 66 eligible EPs and 444 eligible AHPs, we invited 55 EPs and 39 AHPs to participate, and 25 EPs and 25 AHPs (15 nurses, 7 respiratory therapists, and 3 pharmacists) accepted. Participating AHPs had more experience than eligible AHPs (mean 14 vs 11 years; P = .04). We noted no other significant differences. Among EPs, the most frequently reported advantage of using a wiki-based reminder was that it refreshes the memory (n = 14); among AHPs, it was that it provides rapid access to protocols (n = 16). Only 2 EPs mentioned a disadvantage (the wiki added stress). The most frequently reported favorable referent was nurses for EPs (n = 16) and EPs for AHPs (n = 19). The most frequently reported unfavorable referents were people resistant to standardized care for EPs (n = 8) and people less comfortable with computers for AHPs (n = 11). The most frequent facilitator for EPs was ease of use (n = 19); for AHPs, it was having a bedside computer (n = 20). EPs’ most frequently reported barrier was irregularly updated wiki-based reminders (n = 18); AHPs’ was undetermined legal responsibility (n = 10). Conclusions We identified EPs’ and AHPs’ salient beliefs about using a wiki-based reminder. We will draw on these beliefs to construct a questionnaire to measure the importance of these determinants to EPs’ and AHPs’ intention to use a wiki-based reminder promoting evidence-based care for traumatic brain injuries. PMID:22515985

Ahp2 (Hop2) function in Arabidopsis thaliana (Ler) is required for stabilization of close alignment and synaptonemal complex formation except for the two short arms that contain nucleolus organizer regions.

PubMed

Stronghill, P; Pathan, N; Ha, H; Supijono, E; Hasenkampf, C

2010-08-01

A cytological comparative analysis of male meiocytes was performed for Arabidopsis wild type and the ahp2 (hop2) mutant with emphasis on ahp2's largely uncharacterized prophase I. Leptotene progression appeared normal in ahp2 meiocytes; chromosomes exhibited regular axis formation and assumed a typical polarized nuclear organization. In contrast, 4',6'-diamidino-2-phenylindole-stained ahp2 pachytene chromosome spreads demonstrated a severe reduction in stabilized pairing. However, transmission electron microscopy (TEM) analysis of sections from meiocytes revealed that ahp2 chromosome axes underwent significant amounts of close alignment (44% of total axis). This apparent paradox strongly suggests that the Ahp2 protein is involved in the stabilization of homologous chromosome close alignment. Fluorescent in situ hybridization in combination with Zyp1 immunostaining revealed that ahp2 mutants undergo homologous synapsis of the nucleolus-organizer-region-bearing short arms of chromosomes 2 and 4, despite the otherwise "nucleus-wide" lack of stabilized pairing. The duration of ahp2 zygotene was significantly prolonged and is most likely due to difficulties in chromosome alignment stabilization and subsequent synaptonemal complex formation. Ahp2 and Mnd1 proteins have previously been shown, "in vitro," to form a heterodimer. Here we show, "in situ," that the Ahp2 and Mnd1 proteins are synchronous in their appearance and disappearance from meiotic chromosomes. Both the Ahp2 and Mnd1 proteins localize along the chromosomal axis. However, localization of the Ahp2 protein was entirely foci-based whereas Mnd1 protein exhibited an immunostaining pattern with some foci along the axis and a diffuse staining for the rest of the chromosome.

Serotonergic modulation of afterhyperpolarization in a neuron that contributes to learning in the leech.

PubMed

Burrell, Brian D; Crisp, Kevin M

2008-02-01

Modulation of afterhyperpolarization (AHP) represents an important mechanism by which excitability of a neuron can be regulated. In the leech brain, sensitization enhances excitability of the S-cell, an interneuron thought to play an important role in this form of nonassociative learning. This increase in excitability is serotonin (5-HT) dependent, but it is not known whether changes in AHP contribute to 5-HT-mediated enhancement of excitability. Therefore electrophysiological recordings and computational modeling were used to determine whether 5-HT enhances excitability via modulation of AHP. 5-HT reduced S-cell AHP and this decrease in the AHP corresponded with an increase in excitability. Little or no AHP is observed in the presence of Ca2+-free saline, suggesting the involvement of Ca2+-dependent K+ channels. Furthermore, AHP amplitude decreased following treatment with drugs (tubocurare and charybdotoxin) that block Ca2+-dependent K+ channel activity. The S-cell also exhibits an afterdepolarization (ADP), which is usually masked by the AHP, and was inhibited by the Na+ channel blocker saxitoxin. A model of the S-cell AHP was constructed using two Ca2+-dependent K+ currents and a Na+-driven ADP current. Reduction of the model conductances underlying the AHP to mimic the effects of 5-HT was sufficient to enhance excitability. These findings were confirmed in occlusion experiments in which pretreatment with tubocurare was able to block 5-HT-mediated decreases in mAHP levels and increases in excitability. These data show that modulation of S-cell AHP can contribute to 5-HT-mediated increases in excitability and that the S-cell afterpotential is due to the combined effects of AHP- and ADP-producing currents.

Systematic methods for the design of a class of fuzzy logic controllers

NASA Astrophysics Data System (ADS)

Yasin, Saad Yaser

2002-09-01

Fuzzy logic control, a relatively new branch of control, can be used effectively whenever conventional control techniques become inapplicable or impractical. Various attempts have been made to create a generalized fuzzy control system and to formulate an analytically based fuzzy control law. In this study, two methods, the left and right parameterization method and the normalized spline-base membership function method, were utilized for formulating analytical fuzzy control laws in important practical control applications. The first model was used to design an idle speed controller, while the second was used to control an inverted control problem. The results of both showed that a fuzzy logic control system based on the developed models could be used effectively to control highly nonlinear and complex systems. This study also investigated the application of fuzzy control in areas not fully utilizing fuzzy logic control. Three important practical applications pertaining to the automotive industries were studied. The first automotive-related application was the idle speed of spark ignition engines, using two fuzzy control methods: (1) left and right parameterization, and (2) fuzzy clustering techniques and experimental data. The simulation and experimental results showed that a conventional controller-like performance fuzzy controller could be designed based only on experimental data and intuitive knowledge of the system. In the second application, the automotive cruise control problem, a fuzzy control model was developed using parameters adaptive Proportional plus Integral plus Derivative (PID)-type fuzzy logic controller. Results were comparable to those using linearized conventional PID and linear quadratic regulator (LQR) controllers and, in certain cases and conditions, the developed controller outperformed the conventional PID and LQR controllers. The third application involved the air/fuel ratio control problem, using fuzzy clustering techniques, experimental data, and a conversion algorithm, to develop a fuzzy-based control algorithm. Results were similar to those obtained by recently published conventional control based studies. The influence of the fuzzy inference operators and parameters on performance and stability of the fuzzy logic controller was studied Results indicated that, the selections of certain parameters or combinations of parameters, affect greatly the performance and stability of the fuzzy controller. Diagnostic guidelines used to tune or change certain factors or parameters to improve controller performance were developed based on knowledge gained from conventional control methods and knowledge gained from the experimental and the simulation results of this study.

Transportation optimization with fuzzy trapezoidal numbers based on possibility theory.

PubMed

He, Dayi; Li, Ran; Huang, Qi; Lei, Ping

2014-01-01

In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods.

Recurrent fuzzy ranking methods

NASA Astrophysics Data System (ADS)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Measuring Distance of Fuzzy Numbers by Trapezoidal Fuzzy Numbers

NASA Astrophysics Data System (ADS)

Hajjari, Tayebeh

2010-11-01

Fuzzy numbers and more generally linguistic values are approximate assessments, given by experts and accepted by decision-makers when obtaining value that is more accurate is impossible or unnecessary. Distance between two fuzzy numbers plays an important role in linguistic decision-making. It is reasonable to define a fuzzy distance between fuzzy objects. To achieve this aim, the researcher presents a new distance measure for fuzzy numbers by means of improved centroid distance method. The metric properties are also studied. The advantage is the calculation of the proposed method is far simple than previous approaches.

Efficient solution of a multi objective fuzzy transportation problem

NASA Astrophysics Data System (ADS)

Vidhya, V.; Ganesan, K.

2018-04-01

In this paper we present a methodology for the solution of multi-objective fuzzy transportation problem when all the cost and time coefficients are trapezoidal fuzzy numbers and the supply and demand are crisp numbers. Using a new fuzzy arithmetic on parametric form of trapezoidal fuzzy numbers and a new ranking method all efficient solutions are obtained. The proposed method is illustrated with an example.

An analysis of possible applications of fuzzy set theory to the actuarial credibility theory

NASA Technical Reports Server (NTRS)

Ostaszewski, Krzysztof; Karwowski, Waldemar

1992-01-01

In this work, we review the basic concepts of actuarial credibility theory from the point of view of introducing applications of the fuzzy set-theoretic method. We show how the concept of actuarial credibility can be modeled through the fuzzy set membership functions and how fuzzy set methods, especially fuzzy pattern recognition, can provide an alternative tool for estimating credibility.

A online credit evaluation method based on AHP and SPA

NASA Astrophysics Data System (ADS)

Xu, Yingtao; Zhang, Ying

2009-07-01

Online credit evaluation is the foundation for the establishment of trust and for the management of risk between buyers and sellers in e-commerce. In this paper, a new credit evaluation method based on the analytic hierarchy process (AHP) and the set pair analysis (SPA) is presented to determine the credibility of the electronic commerce participants. It solves some of the drawbacks found in classical credit evaluation methods and broadens the scope of current approaches. Both qualitative and quantitative indicators are considered in the proposed method, then a overall credit score is achieved from the optimal perspective. In the end, a case analysis of China Garment Network is provided for illustrative purposes.

Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers

NASA Astrophysics Data System (ADS)

Ridzuan, Siti Amnah Mohd; Mohamad, Daud; Kamis, Nor Hanimah

2014-12-01

Multi-Criteria Decision Making (MCDM) methods have been developed to help decision makers in selecting the best criteria or alternatives from the options given. One of the well known methods in MCDM is the Consistent Fuzzy Preference Relation (CFPR) method, essentially utilizes a pairwise comparison approach. This method was later improved to cater subjectivity in the data by using fuzzy set, known as the Consistent Linguistic Fuzzy Preference Relations (CLFPR). The CLFPR method uses the additive transitivity property in the evaluation of pairwise comparison matrices. However, the calculation involved is lengthy and cumbersome. To overcome this problem, a method of defuzzification was introduced by researchers. Nevertheless, the defuzzification process has a major setback where some information may lose due to the simplification process. In this paper, we propose a method of CLFPR that preserves the fuzzy numbers form throughout the process. In obtaining the desired ordering result, a method of ranking fuzzy numbers is utilized in the procedure. This improved procedure for CLFPR is implemented to a case study to verify its effectiveness. This method is useful for solving decision making problems and can be applied to many areas of applications.

Adaptive Fuzzy Control for Nonstrict Feedback Systems With Unmodeled Dynamics and Fuzzy Dead Zone via Output Feedback.

PubMed

Wang, Lijie; Li, Hongyi; Zhou, Qi; Lu, Renquan

2017-09-01

This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify the unknown functions. And combining small-gain approach with adaptive backstepping control technique, a novel adaptive fuzzy output feedback control strategy is developed, which ensures that all signals involved are semi-globally uniformly bounded. Simulation results are given to demonstrate the effectiveness of the presented method.

Equipment Selection by using Fuzzy TOPSIS Method

NASA Astrophysics Data System (ADS)

Yavuz, Mahmut

2016-10-01

In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

[Patients' Priorities in the Treatment of Neuroendocrine Tumours: An Analytical Hierarchy Process].

PubMed

Mühlbacher, A C; Juhnke, C; Kaczynski, A

2016-10-01

Background: Neuroendocrine tumours (NET) are relatively rare, usually slow-growing malignant tumours. So far there are no data on the patient preferences/priorities regarding the therapy for NET. This empirical study aimed at the elicitation of patient priorities in the drug treatment of NET. Method: Qualitative patient interviews (N=9) were conducted. To elicit the patient's perspective regarding various treatment aspects of NET a self-administered questionnaire using the Analytical Hierarchy Process (AHP) was developed. The data collection was carried out using paper questionnaires supported by an item response system in a group discussion. To evaluate the patient-relevant outcomes, the eigenvector method was applied. Results: N=24 patients, experts and relatives participated in the AHP survey. In the AHP all respondents had clear priorities for all considered attributes. The attribute "overall survival" was the most significant feature of a drug therapy for all respondents. As in the qualitative interviews, "efficacy attributes" dominated the side effects in the AHP as well. The evaluation of all participants thus showed the attributes "overall survival" (Wglobal:0.418), "progression-free survival" (Wglobal:0.172) and "response to treatment" (Wglobal:0.161) to be most relevant. "Occurrence of abdominal pain" (Wglobal:0.051) was ranked sixth, with "tiredness/fatigue" and "risk of a hypoglycaemia" (Wglobal:0.034) in a shared seventh place. Conclusion: The results thus provide evidence about how much influence a treatment capacity has on therapeutic decisions. Using the AHP major aspects of drug therapy from the perspective of those affected were captured, and positive and negative therapeutic properties could be related against each other. Based on the assessment of the patient's perspective further investigation must elicit patient preferences for NET drug therapy. In the context of a discrete choice experiment or another choice-based method of preference measurement, the results obtained here can be validated and the therapeutic features weighted according to their preferability. © Georg Thieme Verlag KG Stuttgart · New York.

Degradation of ciprofloxacin antibiotic by Homogeneous Fenton oxidation: Hybrid AHP-PROMETHEE method, optimization, biodegradability improvement and identification of oxidized by-products.

PubMed

Salari, Marjan; Rakhshandehroo, Gholam Reza; Nikoo, Mohammad Reza

2018-09-01

The main purpose of this experimental study was to optimize Homogeneous Fenton oxidation (HFO) and identification of oxidized by-products from degradation of Ciprofloxacin (CIP) using hybrid AHP-PROMETHEE, Response Surface Methodology (RSM) and High Performance Liquid Chromatography coupled with Mass Spectrometry (HPLC-MS). At the first step, an assessment was made for performances of two catalysts (FeSO 4 ·7H 2 O and FeCl 2 ·4H 2 O) based on hybrid AHP-PROMETHEE decision making method. Then, RSM was utilized to examine and optimize the influence of different variables including initial CIP concentration, Fe 2+ concentration, [H 2 O 2 ]/[ Fe 2+ ] mole ratio and initial pH as independent variables on CIP removal, COD removal, and sludge to iron (SIR) as the response functions in a reaction time of 25 min. Weights of the mentioned responses as well as cost criteria were determined by AHP model based on pairwise comparison and then used as inputs to PROMETHEE method to develop hybrid AHP-PROMETHEE. Based on net flow results of this hybrid model, FeCl 2 ·4H 2 O was more efficient because of its less environmental stability as well as lower SIR production. Then, optimization of experiments using Central Composite Design (CCD) under RSM was performed with the FeCl 2 ·4H 2 O catalyst. Biodegradability of wastewater was determined in terms of BOD 5 /COD ratio, showing that HFO process is able to improve wastewater biodegradability from zero to 0.42. Finally, the main intermediaries of degradation and degradation pathways of CIP were investigated with (HPLC-MS). Major degradation pathways from hydroxylation of both piperazine and quinolonic rings, oxidation and cleavage of the piperazine ring, and defluorination (OH/F substitution) were suggested. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prioritizing Project Risks Using AHP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thibadeau, Barbara M

2007-01-01

This essay introduces the Analytic Hierarchy Process (AHP) as a method by which to rank project risks, in terms of importance as well as likelihood. AHP is way to handle quantifiable and/or intangible criteria in the decision making process. It is a multi-objective multi-criteria decision-making approach that is based on the idea of pair-wise comparisons of alternatives with respect to a given criterion (e.g., which alternative, A or B, is preferred and by how much more is it preferred) or with respect to an objective (e.g., which is more important, A or B, and by how much more is itmore » important). This approach was pioneered by Thomas Saaty in the late 1970's. It has been suggested that a successful project is one that successfully manages risk and that project management is the management of uncertainty. Risk management relies on the quantification of uncertainty which, in turn, is predicated upon the accuracy of probabilistic approaches (in terms of likelihood as well as magnitude). In many cases, the appropriate probability distribution (or probability value) is unknown. And, researchers have shown that probability values are not made very accurately, that the use of verbal expressions is not a suitable alternative, that there is great variability in the use and interpretation of these values and that there is a great reluctance to assign them in the first place. Data from an ongoing project is used to show that AHP can be used to obtain these values, thus overcoming some of the problems associated with the direct assignment of discrete probability values. A novel method by which to calculate the consistency of the data is introduced. The AHP approach is easily implemented and, typically, offers results that are consistent with the decision maker's intuition.« less

Design and implementation of fuzzy logic controllers. Thesis Final Report, 27 Jul. 1992 - 1 Jan. 1993

NASA Technical Reports Server (NTRS)

Abihana, Osama A.; Gonzalez, Oscar R.

1993-01-01

The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design procedure is illustrated via four examples, showing the capabilities and robustness of fuzzy logic control systems. This is followed by a tuning procedure that we developed from our design experience. Third, we present two Lyapunov based techniques for stability analysis. Finally, we present our design and implementation of a fuzzy logic controller for a linear actuator to be used to control the direction of the Free Flight Rotorcraft Research Vehicle at LaRC.

Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans

PubMed Central

Si, Guangsen; Xu, Zeshui

2018-01-01

Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method. PMID:29614019

Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans.

PubMed

Liao, Huchang; Si, Guangsen; Xu, Zeshui; Fujita, Hamido

2018-04-03

Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers' subjective cognition. In general, different decision-makers' sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method.

Synthesis, spectral and thermal studies of some transition metal mixed ligand complexes: Modeling of equilibrium composition and biological activity

NASA Astrophysics Data System (ADS)

Neelakantan, M. A.; Sundaram, M.; Nair, M. Sivasankaran

2011-09-01

Several mixed ligand Ni(II), Cu(II) and Zn(II) complexes of 2-amino-3-hydroxypyridine (AHP) and imidazoles viz., imidazole (him), benzimidazole (bim), histamine (hist) and L-histidine (his) have been synthesized and characterized by elemental and spectral (vibrational, electronic, 1H NMR and EPR) data as well as by magnetic moment values. On the basis of elemental analysis and molar conductance values, all the complexes can be formulated as [MAB]Cl except histidine complexes as MAB. Thermogravimetric studies reveal the presence of coordinated water molecules in most of the complexes. From the magnetic measurements and electronic spectral data, octahedral structure was proposed for Ni(II) and Cu(II)-AHP-his, tetrahedral for Cu(II)-AHP-him/bim/hist, but square planar for the Cu(II)-AHP complex. The g∥/ A∥ calculated supports tetrahedral environment around the Cu(II) in Cu(II)-AHP-him/bim/hist and distorted octahedral for Cu(II)-AHP-his complexes. The morphology of the reported metal complexes was investigated by scanning electron micrographs (SEM). The potentiometric study has been performed in aqueous solution at 37 °C and I = 0.15 mol dm -3 NaClO 4. MABH, MAB and MAB 2 species has been identified in the present systems. Proton dissociation constants of AHP and stability constants of metal complexes were determined using MINIQUAD-75. The most probable structure of the mixed ligand species is discussed based upon their stability constants. The in vitro biological activity of the complexes was tested against the Gram positive and Gram negative bacteria, fungus and yeast. The oxidative DNA cleavage studies of the complexes were performed using gel electrophoresis method. Cu(II) complexes have been found to promote DNA cleavage in presence of biological reductant such as ascorbate and oxidant like hydrogen peroxide.

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

NASA Astrophysics Data System (ADS)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

Fuzzy Hungarian Method for Solving Intuitionistic Fuzzy Travelling Salesman Problem

NASA Astrophysics Data System (ADS)

Prabakaran, K.; Ganesan, K.

2018-04-01

The travelling salesman problem is to identify the shortest route that the salesman journey all the places and return the starting place with minimum cost. We develop a fuzzy version of Hungarian algorithm for the solution of intuitionistic fuzzy travelling salesman problem using triangular intuitionistic fuzzy numbers without changing them to classical travelling salesman problem. The purposed method is easy to empathize and to implement for finding solution of intuitionistic travelling salesman problem happening in real life situations. To illustrate the proposed method numerical example are provided.

Forecasting Jakarta composite index (IHSG) based on chen fuzzy time series and firefly clustering algorithm

NASA Astrophysics Data System (ADS)

Ningrum, R. W.; Surarso, B.; Farikhin; Safarudin, Y. M.

2018-03-01

This paper proposes the combination of Firefly Algorithm (FA) and Chen Fuzzy Time Series Forecasting. Most of the existing fuzzy forecasting methods based on fuzzy time series use the static length of intervals. Therefore, we apply an artificial intelligence, i.e., Firefly Algorithm (FA) to set non-stationary length of intervals for each cluster on Chen Method. The method is evaluated by applying on the Jakarta Composite Index (IHSG) and compare with classical Chen Fuzzy Time Series Forecasting. Its performance verified through simulation using Matlab.

Genetic reinforcement learning through symbiotic evolution for fuzzy controller design.

PubMed

Juang, C F; Lin, J Y; Lin, C T

2000-01-01

An efficient genetic reinforcement learning algorithm for designing fuzzy controllers is proposed in this paper. The genetic algorithm (GA) adopted in this paper is based upon symbiotic evolution which, when applied to fuzzy controller design, complements the local mapping property of a fuzzy rule. Using this Symbiotic-Evolution-based Fuzzy Controller (SEFC) design method, the number of control trials, as well as consumed CPU time, are considerably reduced when compared to traditional GA-based fuzzy controller design methods and other types of genetic reinforcement learning schemes. Moreover, unlike traditional fuzzy controllers, which partition the input space into a grid, SEFC partitions the input space in a flexible way, thus creating fewer fuzzy rules. In SEFC, different types of fuzzy rules whose consequent parts are singletons, fuzzy sets, or linear equations (TSK-type fuzzy rules) are allowed. Further, the free parameters (e.g., centers and widths of membership functions) and fuzzy rules are all tuned automatically. For the TSK-type fuzzy rule especially, which put the proposed learning algorithm in use, only the significant input variables are selected to participate in the consequent of a rule. The proposed SEFC design method has been applied to different simulated control problems, including the cart-pole balancing system, a magnetic levitation system, and a water bath temperature control system. The proposed SEFC has been verified to be efficient and superior from these control problems, and from comparisons with some traditional GA-based fuzzy systems.

Comparing Classic and Interval Analytical Hierarchy Process Methodologies for Measuring Area-Level Deprivation to Analyze Health Inequalities.

PubMed

Cabrera-Barona, Pablo; Ghorbanzadeh, Omid

2018-01-16

Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas.

Comparing Classic and Interval Analytical Hierarchy Process Methodologies for Measuring Area-Level Deprivation to Analyze Health Inequalities

PubMed Central

Cabrera-Barona, Pablo

2018-01-01

Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas. PMID:29337915

Selecting appropriate wastewater treatment technologies using a choosing-by-advantages approach.

PubMed

Arroyo, Paz; Molinos-Senante, María

2018-06-01

Selecting the most sustainable wastewater treatment (WWT) technology among possible alternatives is a very complex task because the choice must integrate economic, environmental, and social criteria. Traditionally, several multi-criteria decision-making approaches have been applied, with the most often used being the analytical hierarchical process (AHP). However, AHP allows users to offset poor environmental and/or social performance with low cost. To overcome this limitation, our study examines a choosing-by-advantages (CBA) approach to rank seven WWT technologies for secondary WWT. CBA results were compared with results obtained by using the AHP approach. The rankings of WWT alternatives differed, depending on whether the CBA or AHP approach was used, which highlights the importance of the method used to support decision-making processes, particularly ones that rely on subjective interpretations by experts. This paper uses a holistic perspective to demonstrate the benefits of using the CBA approach to support a decision-making process when a group of experts must come to a consensus in selecting the most suitable WWT technology among several available. Copyright © 2017 Elsevier B.V. All rights reserved.

Demand-based urban forest planning using high-resolution remote sensing and AHP

NASA Astrophysics Data System (ADS)

Kolanuvada, Srinivasa Raju; Mariappan, Muneeswaran; Krishnan, Vani

2016-05-01

Urban forest planning is important for providing better urban ecosystem services and conserve the natural carbon sinks inside the urban area. In this study, a demand based urban forest plan was developed for Chennai city by using Analytical Hierarchy Process (AHP) method. Population density, Tree cover, Air quality index and Carbon stocks are the parameters were considered in this study. Tree cover and Above Ground Biomass (AGB) layers were prepared at a resolution of 1m from airborne LiDAR and aerial photos. The ranks and weights are assigned by the spatial priority using AHP. The results show that, the actual status of the urban forest is not adequate to provide ecosystem services on spatial priority. From this perspective, we prepared a demand based plan for improving the urban ecosystem.

Assessment of groundwater vulnerability by applying the modified DRASTIC model in Beihai City, China.

PubMed

Wu, Xiaoyu; Li, Bin; Ma, Chuanming

2018-05-01

This study assesses vulnerability of groundwater to pollution in Beihai City, China, as a support of groundwater resource protection. The assessment result not only objectively reflects potential possibility of groundwater to contamination but also provides scientific basis for the planning and utilization of groundwater resources. This study optimizes the parameters consisting of natural factors and human factors upon the DRASTIC model and modifies the ratings of these parameters, based on the local environmental conditions for the study area. And a weight of each parameter is assigned by the analytic hierarchy process (AHP) to reduce the subjectivity of humans to vulnerability assessment. The resulting scientific ratings and weights of modified DRASTIC model (AHP-DRASTLE model) contribute to obtain the more realistic assessment of vulnerability of groundwater to contaminant. The comparison analysis validates the accuracy and rationality of the AHP-DRASTLE model and shows it suits the particularity of the study area. The new assessment method (AHP-DRASTLE model) can provide a guide for other scholars to assess the vulnerability of groundwater to contamination. The final vulnerability map for the AHP-DRASTLE model shows four classes: highest (2%), high (29%), low (55%), and lowest (14%). The vulnerability map serves as a guide for decision makers on groundwater resource protection and land use planning at the regional scale and that it is adapted to a specific area.

[Vulnerability of eco-economy in northern slope region of Tianshan Mountains].

PubMed

Wu, Jian-zhai; Li, Bo; Zhang, Xin-shi; Zhao, Wen-wu; Jiang, Guang-hui

2008-04-01

Based on the theoretical meaning of vulnerability, a vulnerability assessment of eco-econom in fifteen counties in the northern slope region of Tianshan Mountains was conducted. The ecosystem services change to land use was regarded as the impact, and based on the fourteen indices from resource holding, society development, and economy development statistic data, the adaptive ability was evaluated by using the methods of analytic hierarchy process (AHP) and fuzzy synthetic evaluation. On the basis of assessment results of impact and adaptive capacity, the fifteen counties were divided into five classes under the assessment principles, and the district with higher-class number was of more vulnerability. The first class included Usu City and Changji City, the second class included Hutubi County, Miquan County, Fukang City, Jimsar County, Qitai County and Mori Kazak Autonomous County, the third class included Karamay City and Urumqi City, the fourth class included Kuitun City and Shawan County, and the fifth class included Jinghe County, Shihezi City and Manas County. The vulnerability reflected the level of eco-environment change and socioeconomic development, and the vulnerability assessment could be a good way to ensure the sustainable development. Aiming to decrease the vulnerability, various districts belonging to different class of vulnerability should establish relevant tactics according to the vulnerability factors to accelerate the region's sustainable development.

[Study on the quantitative evaluation on the degree of TCM basic syndromes often encountered in patients with primary liver cancer].

PubMed

Li, Dong-tao; Ling, Chang-quan; Zhu, De-zeng

2007-07-01

To establish a quantitative model for evaluating the degree of the TCM basic syndromes often encountered in patients with primary liver cancer (PLC). Medical literatures concerning the clinical investigation and TCM syndrome of PLC were collected and analyzed adopting expert-composed symposium method, and the 100 millimeter scaling was applied in combining with scoring on degree of symptoms to establish a quantitative criterion for symptoms and signs degree classification in patients with PLC. Two models, i.e. the additive model and the additive-multiplicative model, were established by using comprehensive analytic hierarchy process (AHP) as the mathematical tool to estimate the weight of the criterion for evaluating basic syndromes in various layers by specialists. Then the two models were verified in clinical practice and the outcomes were compared with that fuzzy evaluated by specialists. Verification on 459 times/case of PLC showed that the coincidence rate between the outcomes derived from specialists with that from the additive model was 84.53 %, and with that from the additive-multificative model was 62.75 %, the difference between the two showed statistical significance (P<0.01). It could be decided that the additive model is the principle model suitable for quantitative evaluation on the degree of TCM basic syndromes in patients with PLC.

Using GIS and Ahp for Planning Primer Transportation of Forest Products

NASA Astrophysics Data System (ADS)

Akay, A. E.; Yılmaz, B.

2017-11-01

Primer transportation is one of the most costly and time consuming forestry activities in extraction of timber from forest lands. Transportation methods are essentially determined based on terrain characteristics, especially ground slope. Besides, unsuitable machine selection and unplanned operations may cause ecological damages such as soil disturbance. Soil damage can lead to long term impacts on forest ecosystem. Thus, the optimum transportation methods should be determined by considering not only economic factors but also topographical factors and soil conditions. In recent decades, some of the advanced features of Geographical Information System (GIS) assist decision makers to solve such complex transportation problems with various constraints. In this study, it was aimed to plan forest transportation operation by using GIS integrated Analytical Hierarchy Process (AHP) method, considering ground slope, soil type, and available transportation equipment in the region. This method was implemented within the border of İnegöl Forest Enterprise Chief in the city of Bursa in Turkey. Alternative transportation method included cable system, chute system, skidder, and farm tractor. GIS-based method integrated with AHP found that skidder was the optimal transportation method for about 60% of the study area, while farm tractor was the second most suitable method with 25% ground cover. The results indicated that GIS-based decision support systems can be effectively used as rational, quick, and economic tool for forest transportation planning.

Designing boosting ensemble of relational fuzzy systems.

PubMed

Scherer, Rafał

2010-10-01

A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Knowledge and intelligent computing system in medicine.

PubMed

Pandey, Babita; Mishra, R B

2009-03-01

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Cung, E. S.

2014-09-01

This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Alkyl hydroperoxide reductase from Bacillus aquimaris MKSC 6.2 protects Esherichia coli from oxidative stress.

PubMed

Natalia, Dessy; Jumadila, Ozi; Anggraini, Irika Devi; Meutia, Febrina; Puspasari, Fernita; Hasan, Khomaini

2016-07-01

Alkyl hydroperoxide reductase genes (ahpCF) from the soft coral associated Bacillus aquimaris MKSC6.2 have been isolated. The cloned 546 bp ahpC gene encodes a 181 amino acid residues polypeptide. The AhpC belongs to typical 2-Cys peroxiredoxin (Prx) containing conserved peroxidatic cysteine residue (C46 ) required for hydroperoxide reduction and conserved resolving cysteine (C166 ). The isolated 1530 bp ahpF gene encodes a polypeptide of 509 amino acid residues with two conserved C128 HNC131 and C337 PHC340 catalytic residues required for reduction of oxidized-AhpC during catalytic turnover. A survival study with Escherichia coli showed that overexpression of AhpC and AhpF resulted in a total protection against 0.16 mM t-butyl hydroperoxide. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting.

PubMed

Schmidt, Katharina; Aumann, Ines; Hollander, Ines; Damm, Kathrin; von der Schulenburg, J-Matthias Graf

2015-12-24

The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context. A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: "Analytic Hierarchy Process," "Analytical Hierarchy Process," "multi-criteria decision analysis," "multiple criteria decision," "stated preference," and "pairwise comparison." In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies' reporting. The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30%), followed by the US (25.6%). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria. The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP.

Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

PubMed Central

Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

2015-01-01

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

Mathematical models of the simplest fuzzy PI/PD controllers with skewed input and output fuzzy sets.

PubMed

Mohan, B M; Sinha, Arpita

2008-07-01

This paper unveils mathematical models for fuzzy PI/PD controllers which employ two skewed fuzzy sets for each of the two-input variables and three skewed fuzzy sets for the output variable. The basic constituents of these models are Gamma-type and L-type membership functions for each input, trapezoidal/triangular membership functions for output, intersection/algebraic product triangular norm, maximum/drastic sum triangular conorm, Mamdani minimum/Larsen product/drastic product inference method, and center of sums defuzzification method. The existing simplest fuzzy PI/PD controller structures derived via symmetrical fuzzy sets become special cases of the mathematical models revealed in this paper. Finally, a numerical example along with its simulation results are included to demonstrate the effectiveness of the simplest fuzzy PI controllers.

Essential role of the flexible linker on the conformational equilibrium of bacterial peroxiredoxin reductase for effective regeneration of peroxiredoxin

PubMed Central

Kamariah, Neelagandan; Eisenhaber, Birgit; Eisenhaber, Frank; Grüber, Gerhard

2017-01-01

Reactive oxygen species (ROS) can damage DNA, proteins, and lipids, so cells have antioxidant systems that regulate ROS. In many bacteria, a dedicated peroxiredoxin reductase, alkyl hydroperoxide reductase subunit F (AhpF), catalyzes the rapid reduction of the redox-active disulfide center of the antioxidant protein peroxiredoxin (AhpC) to detoxify ROS such as hydrogen peroxide, organic hydroperoxide, and peroxynitrite. AhpF is a flexible multidomain protein that enables a series of electron transfers among the redox centers by accepting reducing equivalents from NADH. A flexible linker connecting the N-terminal domain (NTD) and C-terminal domain (CTD) of AhpF suggests that the enzyme adopts a large-scale domain motion that alternates between the closed and open states to shuttle electrons from the CTD via the NTD to AhpC. Here, we conducted comprehensive mutational, biochemical, and biophysical analyses to gain insights into the role of the flexible linker and the residues critical for the domain motions of Escherichia coli AhpF (EcAhpF) during electron transfer. Small-angle X-ray scattering studies of linker mutants revealed that a group of charged residues, 200EKR202, is crucial for the swiveling motion of the NTD. Moreover, NADH binding significantly affected EcAhpF flexibility and the movement of the NTD relative to the CTD. The mutants also exhibited a decrease in H2O2 reduction by the AhpF-AhpC ensemble. We propose that a concerted movement involving the NTD, C-terminal NADH, and FAD domains, and the flexible linker between them is essential for optimal intra-domain cross-talk and for efficient electron transfer to the redox partner AhpC required for peroxidation. PMID:28270505

Expression of alkyl hydroperoxide reductase is regulated negatively by OxyR1 and positively by RpoE2 sigma factor in Azospirillum brasilense Sp7.

PubMed

Singh, Sudhir; Dwivedi, Susheel Kumar; Singh, Vijay Shankar; Tripathi, Anil Kumar

2016-10-01

OxyR proteins are LysR-type transcriptional regulators, which play an important role in responding to oxidative stress in bacteria. Azospirillum brasilense Sp7 harbours two copies of OxyR. The inactivation of the oxyR1, the gene organized divergently to ahpC in A. brasilense Sp7, led to an increased tolerance to alkyl hydroperoxides, which was corroborated by an increase in alkyl hydroperoxide reductase (AhpC) activity, enhanced expression of ahpC :lacZ fusion and increased synthesis of AhpC protein in the oxyR1::km mutant. The upstream region of ahpC promoter harboured a putative OxyR binding site, T-N11-A. Mutation of T, A or both in the T-N11-Amotif caused derepression of ahpC in A. brasilense suggesting that T-N11-A might be the binding site for a negative regulator. Retardation of the electrophoretic mobility of the T-N11-A motif harbouring oxyR1-ahpC intergenic DNA by recombinant OxyR1, under reducing as well as oxidizing conditions, indicated that OxyR1 acts as a negative regulator of ahpC in A. brasilense. Sequence of the promoter of ahpC, predicted on the basis of transcriptional start site, and an enhanced expression of ahpC:lacZ fusion in chrR2::km mutant background suggested that ahpC promoter was RpoE2 dependent. Thus, this study shows that in A. brasilense Sp7, ahpC expression is regulated negatively by OxyR1 but is regulated positively by RpoE2, an oxidative-stress-responsive sigma factor. It also shows that OxyR1 regulates the expression RpoE1, which is known to play an important role during photooxidative stress in A. brasilense.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Chung, E.-S.

2015-04-01

This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Water supply management using an extended group fuzzy decision-making method: a case study in north-eastern Iran

NASA Astrophysics Data System (ADS)

Minatour, Yasser; Bonakdari, Hossein; Zarghami, Mahdi; Bakhshi, Maryam Ali

2015-09-01

The purpose of this study was to develop a group fuzzy multi-criteria decision-making method to be applied in rating problems associated with water resources management. Thus, here Chen's group fuzzy TOPSIS method extended by a difference technique to handle uncertainties of applying a group decision making. Then, the extended group fuzzy TOPSIS method combined with a consistency check. In the presented method, initially linguistic judgments are being surveyed via a consistency checking process, and afterward these judgments are being used in the extended Chen's fuzzy TOPSIS method. Here, each expert's opinion is turned to accurate mathematical numbers and, then, to apply uncertainties, the opinions of group are turned to fuzzy numbers using three mathematical operators. The proposed method is applied to select the optimal strategy for the rural water supply of Nohoor village in north-eastern Iran, as a case study and illustrated example. Sensitivity analyses test over results and comparing results with project reality showed that proposed method offered good results for water resources projects.

Robust Takagi-Sugeno fuzzy control for fractional order hydro-turbine governing system.

PubMed

Wang, Bin; Xue, Jianyi; Wu, Fengjiao; Zhu, Delan

2016-11-01

A robust fuzzy control method for fractional order hydro-turbine governing system (FOHGS) in the presence of random disturbances is investigated in this paper. Firstly, the mathematical model of FOHGS is introduced, and based on Takagi-Sugeno (T-S) fuzzy rules, the generalized T-S fuzzy model of FOHGS is presented. Secondly, based on fractional order Lyapunov stability theory, a novel T-S fuzzy control method is designed for the stability control of FOHGS. Thirdly, the relatively loose sufficient stability condition is acquired, which could be transformed into a group of linear matrix inequalities (LMIs) via Schur complement as well as the strict mathematical derivation is given. Furthermore, the control method could resist random disturbances, which shows the good robustness. Simulation results indicate the designed fractional order T-S fuzzy control scheme works well compared with the existing method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluation on Electronic Securities Settlements Systems by AHP Methods

NASA Astrophysics Data System (ADS)

Fukaya, Kiyoyuki; Komoda, Norihisa

Accompanying the spread of Internet and the change of business models, electronic commerce expands buisness areas. Electronic finance commerce becomes popular and especially online security tradings becoome very popular in this area. This online securitiy tradings have some good points such as less mistakes than telephone calls. In order to expand this online security tradings, the transfer of the security paper is one the largest problems to be solved. Because it takes a few days to transfer the security paper from a seller to a buyer. So the dematerialization of security papers is one of the solutions. The demterilization needs the information systems for setteling security. Some countries such as France, German, United Kingdom and U.S.A. have been strating the dematerialization projects. The legacy assesments on these projects focus from the viewpoint of the legal schemes only and there is no assessment from system architectures. This paper focuses on the information system scheme and valuates these dematerlization projects by AHP methods from the viewpoints of “dematerializaion of security papers", “speed of transfer", “usefulness on the system" and “accumulation of risks". This is the first case of valuations on security settlements systems by AHP methods, especially four counties’ systems.

An analytical fuzzy-based approach to ?-gain optimal control of input-affine nonlinear systems using Newton-type algorithm

NASA Astrophysics Data System (ADS)

Milic, Vladimir; Kasac, Josip; Novakovic, Branko

2015-10-01

This paper is concerned with ?-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone-Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for ?-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton's method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

PubMed

Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches

PubMed Central

Bolin, Jocelyn H.; Edwards, Julianne M.; Finch, W. Holmes; Cassady, Jerrell C.

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering. PMID:24795683

Selection of representative embankments based on rough set - fuzzy clustering method

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.

Modified Levenberg-Marquardt Method for RÖSSLER Chaotic System Fuzzy Modeling Training

NASA Astrophysics Data System (ADS)

Wang, Yu-Hui; Wu, Qing-Xian; Jiang, Chang-Sheng; Xue, Ya-Li; Fang, Wei

Generally, fuzzy approximation models require some human knowledge and experience. Operator's experience is involved in the mathematics of fuzzy theory as a collection of heuristic rules. The main goal of this paper is to present a new method for identifying unknown nonlinear dynamics such as Rössler system without any human knowledge. Instead of heuristic rules, the presented method uses the input-output data pairs to identify the Rössler chaotic system. The training algorithm is a modified Levenberg-Marquardt (L-M) method, which can adjust the parameters of each linear polynomial and fuzzy membership functions on line, and do not rely on experts' experience excessively. Finally, it is applied to training Rössler chaotic system fuzzy identification. Comparing this method with the standard L-M method, the convergence speed is accelerated. The simulation results demonstrate the effectiveness of the proposed method.

[Evaluating comprehensive quality of sediment in Dianchi Lake using adjusted AHP method and 137Cs dating].

PubMed

Zhang, Yan; Deng, Xi-Hai; Peng, Bu-Zhuo

2006-08-01

It is difficult to evaluate comprehensive quality of sediment and to understand development trend of pollution because of absence of monitoring data, especially history data. Combining the method of 137Cs dating with the ways of general sampling and measurement can easily resolve the problem of absence of data and also provide the possibility for calculating weighted environmental quality comprehensive index using the adjusted analytical hierarchy process (AHP) method. In order to overcome the willfulness the judgment matrix is formed objectively based on calculating monitoring data. Based on the monitoring data of sediment pollution and the weights of various factors gained by adjusted AHP method the comprehensive quality of sediment in each zone of Dianchi Lake was evaluated and the results indicated that the pollution of sediments in each zone at the present be serious more than that in the history. The condition may be related to the industrial development and distribution of industries in Dianchi Lake basin. Therefore, in order to improve the comprehensive quality of sediment in Dianchi Lake and to prevent the secondary pollution of heavy metals in sediment from happening, it is necessary to control the pollutants discharge and to remove the pollutants with various ways.

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

Health care professionals' beliefs about using wiki-based reminders to promote best practices in trauma care.

PubMed

Archambault, Patrick Michel; Bilodeau, Andrea; Gagnon, Marie-Pierre; Aubin, Karine; Lavoie, André; Lapointe, Jean; Poitras, Julien; Croteau, Sylvain; Pham-Dinh, Martin; Légaré, France

2012-04-19

Wikis are knowledge translation tools that could help health professionals implement best practices in acute care. Little is known about the factors influencing professionals' use of wikis. To identify and compare the beliefs of emergency physicians (EPs) and allied health professionals (AHPs) about using a wiki-based reminder that promotes evidence-based care for traumatic brain injuries. Drawing on the theory of planned behavior, we conducted semistructured interviews to elicit EPs' and AHPs' beliefs about using a wiki-based reminder. Previous studies suggested a sample of 25 EPs and 25 AHPs. We purposefully selected participants from three trauma centers in Quebec, Canada, to obtain a representative sample. Using univariate analyses, we assessed whether our participants' gender, age, and level of experience were similar to those of all eligible individuals. Participants viewed a video showing a clinician using a wiki-based reminder, and we interviewed participants about their behavioral, control, and normative beliefs-that is, what they saw as advantages, disadvantages, barriers, and facilitators to their use of a reminder, and how they felt important referents would perceive their use of a reminder. Two reviewers independently analyzed the content of the interview transcripts. We considered the 75% most frequently mentioned beliefs as salient. We retained some less frequently mentioned beliefs as well. Of 66 eligible EPs and 444 eligible AHPs, we invited 55 EPs and 39 AHPs to participate, and 25 EPs and 25 AHPs (15 nurses, 7 respiratory therapists, and 3 pharmacists) accepted. Participating AHPs had more experience than eligible AHPs (mean 14 vs 11 years; P = .04). We noted no other significant differences. Among EPs, the most frequently reported advantage of using a wiki-based reminder was that it refreshes the memory (n = 14); among AHPs, it was that it provides rapid access to protocols (n = 16). Only 2 EPs mentioned a disadvantage (the wiki added stress). The most frequently reported favorable referent was nurses for EPs (n = 16) and EPs for AHPs (n = 19). The most frequently reported unfavorable referents were people resistant to standardized care for EPs (n = 8) and people less comfortable with computers for AHPs (n = 11). The most frequent facilitator for EPs was ease of use (n = 19); for AHPs, it was having a bedside computer (n = 20). EPs' most frequently reported barrier was irregularly updated wiki-based reminders (n = 18); AHPs' was undetermined legal responsibility (n = 10). We identified EPs' and AHPs' salient beliefs about using a wiki-based reminder. We will draw on these beliefs to construct a questionnaire to measure the importance of these determinants to EPs' and AHPs' intention to use a wiki-based reminder promoting evidence-based care for traumatic brain injuries.

Integrated assessment of urban drainage system under the framework of uncertainty analysis.

PubMed

Dong, X; Chen, J; Zeng, S; Zhao, D

2008-01-01

Due to a rapid urbanization as well as the presence of large number of aging urban infrastructures in China, the urban drainage system is facing a dual pressure of construction and renovation nationwide. This leads to the need for an integrated assessment when an urban drainage system is under planning or re-design. In this paper, an integrated assessment methodology is proposed based upon the approaches of analytic hierarchy process (AHP), uncertainty analysis, mathematical simulation of urban drainage system and fuzzy assessment. To illustrate this methodology, a case study in Shenzhen City of south China has been implemented to evaluate and compare two different urban drainage system renovation plans, i.e., the distributed plan and the centralized plan. By comparing their water quality impacts, ecological impacts, technological feasibility and economic costs, the integrated performance of the distributed plan is found to be both better and robust. The proposed methodology is also found to be both effective and practical. (c) IWA Publishing 2008.

Comprehensive benefit analysis of regional water resources based on multi-objective evaluation

NASA Astrophysics Data System (ADS)

Chi, Yixia; Xue, Lianqing; Zhang, Hui

2018-01-01

The purpose of the water resources comprehensive benefits analysis is to maximize the comprehensive benefits on the aspects of social, economic and ecological environment. Aiming at the defects of the traditional analytic hierarchy process in the evaluation of water resources, it proposed a comprehensive benefit evaluation of social, economic and environmental benefits index from the perspective of water resources comprehensive benefit in the social system, economic system and environmental system; determined the index weight by the improved fuzzy analytic hierarchy process (AHP), calculated the relative index of water resources comprehensive benefit and analyzed the comprehensive benefit of water resources in Xiangshui County by the multi-objective evaluation model. Based on the water resources data in Xiangshui County, 20 main comprehensive benefit assessment factors of 5 districts belonged to Xiangshui County were evaluated. The results showed that the comprehensive benefit of Xiangshui County was 0.7317, meanwhile the social economy has a further development space in the current situation of water resources.

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

PubMed Central

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-01

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management. PMID:29342852

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region.

PubMed

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-13

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

New similarity of triangular fuzzy number and its application.

PubMed

Zhang, Xixiang; Ma, Weimin; Chen, Liping

2014-01-01

The similarity of triangular fuzzy numbers is an important metric for application of it. There exist several approaches to measure similarity of triangular fuzzy numbers. However, some of them are opt to be large. To make the similarity well distributed, a new method SIAM (Shape's Indifferent Area and Midpoint) to measure triangular fuzzy number is put forward, which takes the shape's indifferent area and midpoint of two triangular fuzzy numbers into consideration. Comparison with other similarity measurements shows the effectiveness of the proposed method. Then, it is applied to collaborative filtering recommendation to measure users' similarity. A collaborative filtering case is used to illustrate users' similarity based on cloud model and triangular fuzzy number; the result indicates that users' similarity based on triangular fuzzy number can obtain better discrimination. Finally, a simulated collaborative filtering recommendation system is developed which uses cloud model and triangular fuzzy number to express users' comprehensive evaluation on items, and result shows that the accuracy of collaborative filtering recommendation based on triangular fuzzy number is higher.

Fuzzy Sarsa with Focussed Replacing Eligibility Traces for Robust and Accurate Control

NASA Astrophysics Data System (ADS)

Kamdem, Sylvain; Ohki, Hidehiro; Sueda, Naomichi

Several methods of reinforcement learning in continuous state and action spaces that utilize fuzzy logic have been proposed in recent years. This paper introduces Fuzzy Sarsa(λ), an on-policy algorithm for fuzzy learning that relies on a novel way of computing replacing eligibility traces to accelerate the policy evaluation. It is tested against several temporal difference learning algorithms: Sarsa(λ), Fuzzy Q(λ), an earlier fuzzy version of Sarsa and an actor-critic algorithm. We perform detailed evaluations on two benchmark problems : a maze domain and the cart pole. Results of various tests highlight the strengths and weaknesses of these algorithms and show that Fuzzy Sarsa(λ) outperforms all other algorithms tested for a larger granularity of design and under noisy conditions. It is a highly competitive method of learning in realistic noisy domains where a denser fuzzy design over the state space is needed for a more precise control.

Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Actually, a set of ETL software (Extract, Transform and Load) is available to constitute a major investment market. Each ETL uses its own techniques for extracting, transforming and loading data into data warehouse, which makes the task of evaluating ETL software very difficult. However, choosing the right software of ETL is critical to the success or failure of any Business Intelligence project. As there are many impacting factors in the selection of ETL software, the same process is considered as a complex multi-criteria decision making (MCDM) problem. In this study, an application of decision-making methodology that employs the two well-known MCDM techniques, namely Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is designed. In this respect, the aim of using AHP is to analyze the structure of the ETL software selection problem and obtain weights of the selected criteria. Then, TOPSIS technique is used to calculate the alternatives' ratings. An example is given to illustrate the proposed methodology. Finally, a software prototype for demonstrating both methods is implemented.

Using analytic hierarchy process approach in ontological multicriterial decision making - Preliminary considerations

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.

2012-10-01

In this paper we consider combining ontologically demarcated information with Saaty's Analytic Hierarchy Process (AHP) [1] for the multicriterial assessment of offers during contract negotiations. The context for the proposal is provided by the Agents in Grid project (AiG; [2]), which aims at development of an agent-based infrastructure for efficient resource management in the Grid. In the AiG project, software agents representing users can either (1) join a team and earn money, or (2) find a team to execute a job. Moreover, agents form teams, managers of which negotiate with clients and workers terms of potential collaboration. Here, ontologically described contracts (Service Level Agreements) are the results of autonomous multiround negotiations. Therefore, taking into account relatively complex nature of the negotiated contracts, multicriterial assessment of proposals plays a crucial role. The AHP method is based on pairwise comparisons of criteria and relies on the judgement of a panel of experts. It measures how well does an offer serve the objective of a decision maker. In this paper, we propose how the AHP method can be used to assess ontologically described contract proposals.

User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner.

PubMed

Pecchia, Leandro; Martin, Jennifer L; Ragozzino, Angela; Vanzanella, Carmela; Scognamiglio, Arturo; Mirarchi, Luciano; Morgan, Stephen P

2013-01-05

The rigorous elicitation of user needs is a crucial step for both medical device design and purchasing. However, user needs elicitation is often based on qualitative methods whose findings can be difficult to integrate into medical decision-making. This paper describes the application of AHP to elicit user needs for a new CT scanner for use in a public hospital. AHP was used to design a hierarchy of 12 needs for a new CT scanner, grouped into 4 homogenous categories, and to prepare a paper questionnaire to investigate the relative priorities of these. The questionnaire was completed by 5 senior clinicians working in a variety of clinical specialisations and departments in the same Italian public hospital. Although safety and performance were considered the most important issues, user needs changed according to clinical scenario. For elective surgery, the five most important needs were: spatial resolution, processing software, radiation dose, patient monitoring, and contrast medium. For emergency, the top five most important needs were: patient monitoring, radiation dose, contrast medium control, speed run, spatial resolution. AHP effectively supported user need elicitation, helping to develop an analytic and intelligible framework of decision-making. User needs varied according to working scenario (elective versus emergency medicine) more than clinical specialization. This method should be considered by practitioners involved in decisions about new medical technology, whether that be during device design or before deciding whether to allocate budgets for new medical devices according to clinical functions or according to hospital department.

Eco-tourism Education Effectiveness Indicator System Research for Macau SAR in Practice

NASA Astrophysics Data System (ADS)

Ge, Mei

2018-01-01

The study of education in Ecotourism is one of the many important focuses among the field of Ecotourism; and the evaluation of Ecotourism education effectiveness in Ecotourism is a key topic in it. The result of this study can be very useful in the development of Ecotourism education. In addition, affect greatly in its improvement in the future. The Delphi method had been used in this study to establish a valid indicator system of evaluation in Ecotourism education; then followed by the analytic hierarchy process (AHP) with 11 paired-comparison matrices being constructed. Weights of these evaluation indicators were then determined by using Matlab 7.1. Throughout, data was obtained by doing sampling surveys, and the fuzzy comprehensive evaluation method was used to calculate the validity of Ecotourism education, where validity was classified into different levels. As the result, the evaluation model of the education effectiveness in Ecotourism was constructed. The Macau Special Administrative Region (Macau SAR) was chosen in this case for the empirical stage. Data of ecological knowledge, ecological cultural level, ecological consciousness, ecological ethics and ecological behaviors of tourists, who had entered and exited Macau SAR, was collected and analyzed in SPSS. Differences and impact of these indicators were studied to conclude the effect of its education in Ecotourism of this region. In addition, the results of education effectiveness in Ecotourism were also compared among different population subgroups and observations were given accordingly.

Application of fuzzy system theory in addressing the presence of uncertainties

NASA Astrophysics Data System (ADS)

Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K.

2015-02-01

In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.

A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

NASA Astrophysics Data System (ADS)

Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

2018-04-01

This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Type-2 fuzzy set extension of DEMATEL method combined with perceptual computing for decision making

NASA Astrophysics Data System (ADS)

Hosseini, Mitra Bokaei; Tarokh, Mohammad Jafar

2013-05-01

Most decision making methods used to evaluate a system or demonstrate the weak and strength points are based on fuzzy sets and evaluate the criteria with words that are modeled with fuzzy sets. The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods. For this reason, the decision making methods that consider the perceptions of decision makers are desirable. Perceptual computing is a subjective judgment method that considers that words mean different things to different people. This method models words with interval type-2 fuzzy sets that consider the uncertainty of the words. Also, there are interrelations and dependency between the decision making criteria in the real world; therefore, using decision making methods that cannot consider these relations is not feasible in some situations. The Decision-Making Trail and Evaluation Laboratory (DEMATEL) method considers the interrelations between decision making criteria. The current study used the combination of DEMATEL and perceptual computing in order to improve the decision making methods. For this reason, the fuzzy DEMATEL method was extended into type-2 fuzzy sets in order to obtain the weights of dependent criteria based on the words. The application of the proposed method is presented for knowledge management evaluation criteria.

Dynamic Fuzzy Model Development for a Drum-type Boiler-turbine Plant Through GK Clustering

NASA Astrophysics Data System (ADS)

Habbi, Ahcène; Zelmat, Mimoun

2008-10-01

This paper discusses a TS fuzzy model identification method for an industrial drum-type boiler plant using the GK fuzzy clustering approach. The fuzzy model is constructed from a set of input-output data that covers a wide operating range of the physical plant. The reference data is generated using a complex first-principle-based mathematical model that describes the key dynamical properties of the boiler-turbine dynamics. The proposed fuzzy model is derived by means of fuzzy clustering method with particular attention on structure flexibility and model interpretability issues. This may provide a basement of a new way to design model based control and diagnosis mechanisms for the complex nonlinear plant.

Fuzzy and neural control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Fuzzy interval Finite Element/Statistical Energy Analysis for mid-frequency analysis of built-up systems with mixed fuzzy and interval parameters

NASA Astrophysics Data System (ADS)

Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan

2016-10-01

This paper introduces mixed fuzzy and interval parametric uncertainties into the FE components of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model for mid-frequency analysis of built-up systems, thus an uncertain ensemble combining non-parametric with mixed fuzzy and interval parametric uncertainties comes into being. A fuzzy interval Finite Element/Statistical Energy Analysis (FIFE/SEA) framework is proposed to obtain the uncertain responses of built-up systems, which are described as intervals with fuzzy bounds, termed as fuzzy-bounded intervals (FBIs) in this paper. Based on the level-cut technique, a first-order fuzzy interval perturbation FE/SEA (FFIPFE/SEA) and a second-order fuzzy interval perturbation FE/SEA method (SFIPFE/SEA) are developed to handle the mixed parametric uncertainties efficiently. FFIPFE/SEA approximates the response functions by the first-order Taylor series, while SFIPFE/SEA improves the accuracy by considering the second-order items of Taylor series, in which all the mixed second-order items are neglected. To further improve the accuracy, a Chebyshev fuzzy interval method (CFIM) is proposed, in which the Chebyshev polynomials is used to approximate the response functions. The FBIs are eventually reconstructed by assembling the extrema solutions at all cut levels. Numerical results on two built-up systems verify the effectiveness of the proposed methods.

Panasonic Small Cell Testing for AHPS

NASA Technical Reports Server (NTRS)

Pearson, C.; Blackmore, P.; Lain, M.; Walpole, A.; Darcy, Eric

2006-01-01

AEA selection and successful Interim Design Review for AHPS proves maturity of small cell approach for very large batteries. Cells show excellent opportunity for battery mass reduction for AHPS and other low cycle applications. Lack of cycle and extended calendar life make EOL battery performance difficult (AHPS 8 year mission). Preliminary design, AEA retained SONY 18650HC cell as baseline: a) Well characterized performance; b) Wealth of safety test data.

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

NASA Astrophysics Data System (ADS)

Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

2018-06-01

To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

Evaluation of fuzzy inference systems using fuzzy least squares

NASA Technical Reports Server (NTRS)

Barone, Joseph M.

1992-01-01

Efforts to develop evaluation methods for fuzzy inference systems which are not based on crisp, quantitative data or processes (i.e., where the phenomenon the system is built to describe or control is inherently fuzzy) are just beginning. This paper suggests that the method of fuzzy least squares can be used to perform such evaluations. Regressing the desired outputs onto the inferred outputs can provide both global and local measures of success. The global measures have some value in an absolute sense, but they are particularly useful when competing solutions (e.g., different numbers of rules, different fuzzy input partitions) are being compared. The local measure described here can be used to identify specific areas of poor fit where special measures (e.g., the use of emphatic or suppressive rules) can be applied. Several examples are discussed which illustrate the applicability of the method as an evaluation tool.

Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

PubMed

da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

2005-01-01

This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

Automatic approach to deriving fuzzy slope positions

NASA Astrophysics Data System (ADS)

Zhu, Liang-Jun; Zhu, A.-Xing; Qin, Cheng-Zhi; Liu, Jun-Zhi

2018-03-01

Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Exploring the research culture of nurses and allied health professionals (AHPs) in a research-focused and a non-research-focused healthcare organisation in the UK.

PubMed

Luckson, Manju; Duncan, Fiona; Rajai, Azita; Haigh, Carol

2018-04-01

To explore the research culture of nurses and allied health professionals (AHPs) in the UK and the influence of a dedicated research strategy and funding. It is important to understand the culture in order to effectively promote evidence-based patient care. The primary aim of this research was to explore the influence of research-focused exposure on the research culture of nurses and AHPs in the UK and to identify whether there was a difference in the research culture between a research-focused and non-research-focused clinical area (City and Riverside Hospitals). This is a unique and novel study that explored and compared the research culture stance of both AHPs and nurses. METHODS: A mixed methods design was used in this study. Tools used included the "Research Capacity and Culture tool" as an online survey, three focus group discussions and five semi-structured interviews with senior managers. Focus groups included research-naive groups from both hospitals and a research-active group from City Hospital. There were 224 responses received from 941 surveys with a 24% response rate. Descriptive statistics of the survey results indicated that there was a difference (p = .001) in the mean score of the research culture between City Hospital (5.35) and Riverside Hospital (3.90), but not between nurses and AHPs (p = .12). Qualitative data findings from the framework analysis were congruent and supported the survey results. The results provided empirical evidence to support a whole-level approach in order to improve the research culture. Both findings showed that there may not be any difference in the research culture between professional groups. Importantly, new evidence is presented to suggest that there were crucial communication issues which were hampering the research culture and there was a lack of support at the middle management level which needed to be tackled to improve the research culture of nurses and AHPs. The study highlighted the need to include a whole-level approach in organisation to improve research culture and to include communication within the Cooke's framework if evidence-based practice is to influence the quality of patient care. © 2018 John Wiley & Sons Ltd.

Tuning fuzzy PD and PI controllers using reinforcement learning.

PubMed

Boubertakh, Hamid; Tadjine, Mohamed; Glorennec, Pierre-Yves; Labiod, Salim

2010-10-01

In this paper, we propose a new auto-tuning fuzzy PD and PI controllers using reinforcement Q-learning (QL) algorithm for SISO (single-input single-output) and TITO (two-input two-output) systems. We first, investigate the design parameters and settings of a typical class of Fuzzy PD (FPD) and Fuzzy PI (FPI) controllers: zero-order Takagi-Sugeno controllers with equidistant triangular membership functions for inputs, equidistant singleton membership functions for output, Larsen's implication method, and average sum defuzzification method. Secondly, the analytical structures of these typical fuzzy PD and PI controllers are compared to their classical counterpart PD and PI controllers. Finally, the effectiveness of the proposed method is proven through simulation examples. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-objective and Perishable Fuzzy Inventory Models Having Weibull Life-time With Time Dependent Demand, Demand Dependent Production and Time Varying Holding Cost: A Possibility/Necessity Approach

NASA Astrophysics Data System (ADS)

Pathak, Savita; Mondal, Seema Sarkar

2010-10-01

A multi-objective inventory model of deteriorating item has been developed with Weibull rate of decay, time dependent demand, demand dependent production, time varying holding cost allowing shortages in fuzzy environments for non- integrated and integrated businesses. Here objective is to maximize the profit from different deteriorating items with space constraint. The impreciseness of inventory parameters and goals for non-integrated business has been expressed by linear membership functions. The compromised solutions are obtained by different fuzzy optimization methods. To incorporate the relative importance of the objectives, the different cardinal weights crisp/fuzzy have been assigned. The models are illustrated with numerical examples and results of models with crisp/fuzzy weights are compared. The result for the model assuming them to be integrated business is obtained by using Generalized Reduced Gradient Method (GRG). The fuzzy integrated model with imprecise inventory cost is formulated to optimize the possibility necessity measure of fuzzy goal of the objective function by using credibility measure of fuzzy event by taking fuzzy expectation. The results of crisp/fuzzy integrated model are illustrated with numerical examples and results are compared.

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research.

PubMed

Maruthur, Nisa M; Joy, Susan; Dolan, James; Segal, Jodi B; Shihab, Hasan M; Singh, Sonal

2013-01-01

Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences.

A hybrid learning method for constructing compact rule-based fuzzy models.

PubMed

Zhao, Wanqing; Niu, Qun; Li, Kang; Irwin, George W

2013-12-01

The Takagi–Sugeno–Kang-type rule-based fuzzy model has found many applications in different fields; a major challenge is, however, to build a compact model with optimized model parameters which leads to satisfactory model performance. To produce a compact model, most existing approaches mainly focus on selecting an appropriate number of fuzzy rules. In contrast, this paper considers not only the selection of fuzzy rules but also the structure of each rule premise and consequent, leading to the development of a novel compact rule-based fuzzy model. Here, each fuzzy rule is associated with two sets of input attributes, in which the first is used for constructing the rule premise and the other is employed in the rule consequent. A new hybrid learning method combining the modified harmony search method with a fast recursive algorithm is hereby proposed to determine the structure and the parameters for the rule premises and consequents. This is a hard mixed-integer nonlinear optimization problem, and the proposed hybrid method solves the problem by employing an embedded framework, leading to a significantly reduced number of model parameters and a small number of fuzzy rules with each being as simple as possible. Results from three examples are presented to demonstrate the compactness (in terms of the number of model parameters and the number of rules) and the performance of the fuzzy models obtained by the proposed hybrid learning method, in comparison with other techniques from the literature.

Application of fuzzy system theory in addressing the presence of uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.

In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statisticalmore » approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.« less

Competition between calcium-activated K+ channels determines cholinergic action on firing properties of basolateral amygdala projection neurons.

PubMed

Power, John M; Sah, Pankaj

2008-03-19

Acetylcholine (ACh) is an important modulator of learning, memory, and synaptic plasticity in the basolateral amygdala (BLA) and other brain regions. Activation of muscarinic acetylcholine receptors (mAChRs) suppresses a variety of potassium currents, including sI(AHP), the calcium-activated potassium conductance primarily responsible for the slow afterhyperpolarization (AHP) that follows a train of action potentials. Muscarinic stimulation also produces inositol 1,4,5-trisphosphate (IP(3)), releasing calcium from intracellular stores. Here, we show using whole-cell patch-clamp recordings and high-speed fluorescence imaging that focal application of mAChR agonists evokes large rises in cytosolic calcium in the soma and proximal dendrites in rat BLA projection neurons that are often associated with activation of an outward current that hyperpolarizes the cell. This hyperpolarization results from activation of small conductance calcium-activated potassium (SK) channels, secondary to the release of calcium from intracellular stores. Unlike bath application of cholinergic agonists, which always suppressed the AHP, focal application of ACh often evoked a paradoxical enhancement of the AHP and spike-frequency adaptation. This enhancement was correlated with amplification of the action potential-evoked calcium response and resulted from the activation of SK channels. When SK channels were blocked, cholinergic stimulation always reduced the AHP and spike-frequency adaptation. Conversely, suppression of the sI(AHP) by the beta-adrenoreceptor agonist, isoprenaline, potentiated the cholinergic enhancement of the AHP. These results suggest that competition between cholinergic suppression of the sI(AHP) and cholinergic activation of the SK channels shapes the AHP and spike-frequency adaptation.

A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

NASA Astrophysics Data System (ADS)

Tian, Wenli; Cao, Chengxuan

2017-03-01

A generalized interval fuzzy mixed integer programming model is proposed for the multimodal freight transportation problem under uncertainty, in which the optimal mode of transport and the optimal amount of each type of freight transported through each path need to be decided. For practical purposes, three mathematical methods, i.e. the interval ranking method, fuzzy linear programming method and linear weighted summation method, are applied to obtain equivalents of constraints and parameters, and then a fuzzy expected value model is presented. A heuristic algorithm based on a greedy criterion and the linear relaxation algorithm are designed to solve the model.

Green design assessment of electromechanical products based on group weighted-AHP

NASA Astrophysics Data System (ADS)

Guo, Jinwei; Zhou, MengChu; Li, Zhiwu; Xie, Huiguang

2015-11-01

Manufacturing industry is the backbone of a country's economy while environmental pollution is a serious problem that human beings must face today. The green design of electromechanical products based on enterprise information systems is an important method to solve the environmental problem. The question on how to design green products must be answered by excellent designers via both advanced design methods and effective assessment methods of electromechanical products. Making an objective and precise assessment of green design is one of the problems that must be solved when green design is conducted. An assessment method of green design on electromechanical products based on Group Weighted-AHP (Analytic Hierarchy Process) is proposed in this paper, together with the characteristics of green products. The assessment steps of green design are also established. The results are illustrated via the assessment of a refrigerator design.

Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method.

PubMed

Kessili, Abdelhak; Benmamar, Saadia

2016-01-01

The aim of this paper is to develop a methodology for the prioritization of sewer rehabilitation projects for Algiers (Algeria) sewer networks to support the National Sanitation Office in its challenge to make decisions on prioritization of sewer rehabilitation projects. The methodology applies multiple-criteria decision making. The study includes 47 projects (collectors) and 12 criteria to evaluate them. These criteria represent the different issues considered in the prioritization of the projects, which are structural, hydraulic, environmental, financial, social and technical. The analytic hierarchy process (AHP) is used to determine weights of the criteria and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) method is used to obtain the final ranking of the projects. The model was verified using the sewer data of Algiers. The results have shown that the method can be used for prioritizing sewer rehabilitation projects.

Cyclic azole-homologated peptides from Marine sponges.

PubMed

Molinski, Tadeusz F

2017-12-19

This review discusses the chemistry of cyclic azole-homologated peptides (AHPs) from the marine sponges, Theonella swinhoei, other Theonella species, Calyx spp. and Plakina jamaicensis. The origin, distribution of AHPs and molecular structure elucidations of AHPs are described followed by their biosynthesis, bioactivity, and synthetic efforts towards their total synthesis. Reports of partial and total synthesis of AHPs extend beyond peptide coupling reactions and include creative construction of the non-proteinogenic amino acid components, mainly the homologated heteroaromatic and α-keto-β-amino acids. A useful conclusion is drawn regarding AHPs: despite their rarity, exotic structures and the potent protease inhibitory properties of some members, their synthesis is under-developed and beckons solutions for outstanding problems towards their efficient assembly.

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

The implementation of hybrid clustering using fuzzy c-means and divisive algorithm for analyzing DNA human Papillomavirus cause of cervical cancer

NASA Astrophysics Data System (ADS)

Andryani, Diyah Septi; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Clustering aims to classify the different patterns into groups called clusters. In this clustering method, we use n-mers frequency to calculate the distance matrix which is considered more accurate than using the DNA alignment. The clustering results could be used to discover biologically important sub-sections and groups of genes. Many clustering methods have been developed, while hard clustering methods considered less accurate than fuzzy clustering methods, especially if it is used for outliers data. Among fuzzy clustering methods, fuzzy c-means is one the best known for its accuracy and simplicity. Fuzzy c-means clustering uses membership function variable, which refers to how likely the data could be members into a cluster. Fuzzy c-means clustering works using the principle of minimizing the objective function. Parameters of membership function in fuzzy are used as a weighting factor which is also called the fuzzier. In this study we implement hybrid clustering using fuzzy c-means and divisive algorithm which could improve the accuracy of cluster membership compare to traditional partitional approach only. In this study fuzzy c-means is used in the first step to find partition results. Furthermore divisive algorithms will run on the second step to find sub-clusters and dendogram of phylogenetic tree. To find the best number of clusters is determined using the minimum value of Davies Bouldin Index (DBI) of the cluster results. In this research, the results show that the methods introduced in this paper is better than other partitioning methods. Finally, we found 3 clusters with DBI value of 1.126628 at first step of clustering. Moreover, DBI values after implementing the second step of clustering are always producing smaller IDB values compare to the results of using first step clustering only. This condition indicates that the hybrid approach in this study produce better performance of the cluster results, in term its DBI values.

Developing cluster strategy of apples dodol SMEs by integration K-means clustering and analytical hierarchy process method

NASA Astrophysics Data System (ADS)

Mustaniroh, S. A.; Effendi, U.; Silalahi, R. L. R.; Sari, T.; Ala, M.

2018-03-01

The purposes of this research were to determine the grouping of apples dodol small and medium enterprises (SMEs) in Batu City and to determine an appropriate development strategy for each cluster. The methods used for clustering SMEs was k-means. The Analytical Hierarchy Process (AHP) approach was then applied to determine the development strategy priority for each cluster. The variables used in grouping include production capacity per month, length of operation, investment value, average sales revenue per month, amount of SMEs assets, and the number of workers. Several factors were considered in AHP include industry cluster, government, as well as related and supporting industries. Data was collected using the methods of questionaire and interviews. SMEs respondents were selected among SMEs appels dodol in Batu City using purposive sampling. The result showed that two clusters were formed from five apples dodol SMEs. The 1stcluster of apples dodol SMEs, classified as small enterprises, included SME A, SME C, and SME D. The 2ndcluster of SMEs apples dodol, classified as medium enterprises, consisted of SME B and SME E. The AHP results indicated that the priority development strategy for the 1stcluster of apples dodol SMEs was improving quality and the product standardisation, while for the 2nd cluster was increasing the marketing access.

Comparison of Multi-Criteria Decision Support Methods (AHP, TOPSIS, SAW & PROMENTHEE) for Employee Placement

NASA Astrophysics Data System (ADS)

Widianta, M. M. D.; Rizaldi, T.; Setyohadi, D. P. S.; Riskiawan, H. Y.

2018-01-01

The right decision in placing employees in an appropriate position in a company will support the quality of management and will have an impact on improving the quality of human resources of the company. Such decision-making can be assisted by an approach through the Decision Support System (DSS) to improve accuracy in the employee placement process. The purpose of this paper is to compare the four methods of Multi Criteria Decision Making (MCDM), ie Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Of Evaluations (PROMETHEE) for the application of employee placement in accordance with predetermined criteria. The ranking results and the accuracy level obtained from each method are different depending on the different scaling and weighting processes in each method.

Fuzzy-logic based strategy for validation of multiplex methods: example with qualitative GMO assays.

PubMed

Bellocchi, Gianni; Bertholet, Vincent; Hamels, Sandrine; Moens, W; Remacle, José; Van den Eede, Guy

2010-02-01

This paper illustrates the advantages that a fuzzy-based aggregation method could bring into the validation of a multiplex method for GMO detection (DualChip GMO kit, Eppendorf). Guidelines for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation statistics are available and routinely used, for in-house and inter-laboratory testing, and decision-making. Fuzzy logic allows summarising the information obtained by independent validation statistics into one synthetic indicator of overall method performance. The microarray technology, introduced for simultaneous identification of multiple GMOs, poses specific validation issues (patterns of performance for a variety of GMOs at different concentrations). A fuzzy-based indicator for overall evaluation is illustrated in this paper, and applied to validation data for different genetically modified elements. Remarks were drawn on the analytical results. The fuzzy-logic based rules were shown to be applicable to improve interpretation of results and facilitate overall evaluation of the multiplex method.

A Novel Numerical Method for Fuzzy Boundary Value Problems

NASA Astrophysics Data System (ADS)

Can, E.; Bayrak, M. A.; Hicdurmaz

2016-05-01

In the present paper, a new numerical method is proposed for solving fuzzy differential equations which are utilized for the modeling problems in science and engineering. Fuzzy approach is selected due to its important applications on processing uncertainty or subjective information for mathematical models of physical problems. A second-order fuzzy linear boundary value problem is considered in particular due to its important applications in physics. Moreover, numerical experiments are presented to show the effectiveness of the proposed numerical method on specific physical problems such as heat conduction in an infinite plate and a fin.

Development and preliminary validation of a leadership competency instrument for existing and emerging allied health professional leaders.

PubMed

Ang, Hui-Gek; Koh, Jeremy Meng-Yeow; Lee, Jeffrey; Pua, Yong-Hao

2016-02-19

No instruments, to our knowledge, exist to assess leadership competency in existing and emerging allied health professional (AHP) leaders. This paper describes the development and preliminary exploration of the psychometric properties of a leadership competency instrument for existing and emerging AHP leaders and examines (i) its factor structure, (ii) its convergent validity with the Leadership Practices Inventory (LPI), and (iii) its discriminative validity in AHPs with different grades. During development, we included 25 items in the AHEAD (Aspiring leaders in Healthcare-Empowering individuals, Achieving excellence, Developing talents) instrument. A cross-sectional study was then conducted in 106 high-potential AHPs from Singapore General Hospital (34 men and 72 women) of different professional grades (49 principal-grade AHPs, 41 senior-grade AHPs, and 16 junior-grade AHPs) who completed both AHEAD and LPI instruments. Exploratory factor analysis was used to test the theoretical structure of AHEAD. Spearman correlation analysis was performed to evaluate the convergent validity of AHEAD with LPI. Using proportional odds regression models, we evaluated the association of grades of AHPs with AHEAD and LPI. To assess discriminative validity, the c-statistics - a measure of discrimination - were derived from these ordinal models. As theorized, factor analysis suggested a two-factor solution, where "skills" and "values" formed separate factors. Internal consistency of AHEAD was excellent (α-values > 0.88). Total and component AHEAD and LPI scores correlated moderately (Spearman ρ-values, 0.37 to 0.58). The c-index for discriminating between AHP grades was higher for AHEAD than for the LPI (0.76 vs. 0.65). The factorial structure of AHEAD was generally supported in our study. AHEAD showed convergent validity with the LPI and outperformed the LPI in terms of discriminative validity. These results provide initial evidence for the use of AHEAD to assess leadership competency in AHPs.

Confidence-based ensemble for GBM brain tumor segmentation

NASA Astrophysics Data System (ADS)

Huo, Jing; van Rikxoort, Eva M.; Okada, Kazunori; Kim, Hyun J.; Pope, Whitney; Goldin, Jonathan; Brown, Matthew

2011-03-01

It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy connectedness has recently been developed for computing the tumor volume that reduces the cost of manual annotation. In this study, we propose a an ensemble method that combines multiple segmentation results into a final ensemble one. The method is evaluated on a dataset of 20 cases from a multi-center pharmaceutical drug trial and compared to the fuzzy connectedness method. Three individual methods were used in the framework: fuzzy connectedness, GrowCut, and voxel classification. The combination method is a confidence map averaging (CMA) method. The CMA method shows an improved ROC curve compared to the fuzzy connectedness method (p < 0.001). The CMA ensemble result is more robust compared to the three individual methods.

The 2-Cys Peroxiredoxin Alkyl Hydroperoxide Reductase C Binds Heme and Participates in Its Intracellular Availability in Streptococcus agalactiae*

PubMed Central

Lechardeur, Delphine; Fernandez, Annabelle; Robert, Bruno; Gaudu, Philippe; Trieu-Cuot, Patrick; Lamberet, Gilles; Gruss, Alexandra

2010-01-01

Heme is a redox-reactive molecule with vital and complex roles in bacterial metabolism, survival, and virulence. However, few intracellular heme partners were identified to date and are not well conserved in bacteria. The opportunistic pathogen Streptococcus agalactiae (group B Streptococcus) is a heme auxotroph, which acquires exogenous heme to activate an aerobic respiratory chain. We identified the alkyl hydroperoxide reductase AhpC, a member of the highly conserved thiol-dependent 2-Cys peroxiredoxins, as a heme-binding protein. AhpC binds hemin with a Kd of 0.5 μm and a 1:1 stoichiometry. Mutagenesis of cysteines revealed that hemin binding is dissociable from catalytic activity and multimerization. AhpC reductase activity was unchanged upon interaction with heme in vitro and in vivo. A group B Streptococcus ahpC mutant displayed attenuation of two heme-dependent functions, respiration and activity of a heterologous catalase, suggesting a role for AhpC in heme intracellular fate. In support of this hypothesis, AhpC-bound hemin was protected from chemical degradation in vitro. Our results reveal for the first time a role for AhpC as a heme-binding protein. PMID:20332091

[Mapping environmental vulnerability from ETM + data in the Yellow River Mouth Area].

PubMed

Wang, Rui-Yan; Yu, Zhen-Wen; Xia, Yan-Ling; Wang, Xiang-Feng; Zhao, Geng-Xing; Jiang, Shu-Qian

2013-10-01

The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters. Based on that, models of correlation analysis, traditional regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the spectral reflectance and the environmental vulnerability. With this model, the environmental vulnerability distribution was retrieved in the Yellow River Mouth Area. The results showed that the correlation between the environmental vulnerability and the spring NDVI, the September NDVI and the spring brightness was better than others, so they were selected as the sensitive spectral parameters. The model precision result showed that in addition to the support vector model, the other model reached the significant level. While all the multi-variable regression was better than all one-variable regression, and the model accuracy of BP neural network was the best. This study will serve as a reliable theoretical reference for the large spatial scale environmental vulnerability estimation based on remote sensing data.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1995-01-01

Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

New Models for Forecasting Enrollments: Fuzzy Time Series and Neural Network Approaches.

ERIC Educational Resources Information Center

Song, Qiang; Chissom, Brad S.

Since university enrollment forecasting is very important, many different methods and models have been proposed by researchers. Two new methods for enrollment forecasting are introduced: (1) the fuzzy time series model; and (2) the artificial neural networks model. Fuzzy time series has been proposed to deal with forecasting problems within a…

Method and system of Jones-matrix mapping of blood plasma films with "fuzzy" analysis in differentiation of breast pathology changes

NASA Astrophysics Data System (ADS)

Zabolotna, Natalia I.; Radchenko, Kostiantyn O.; Karas, Oleksandr V.

2018-01-01

A fibroadenoma diagnosing of breast using statistical analysis (determination and analysis of statistical moments of the 1st-4th order) of the obtained polarization images of Jones matrix imaginary elements of the optically thin (attenuation coefficient τ <= 0,1 ) blood plasma films with further intellectual differentiation based on the method of "fuzzy" logic and discriminant analysis were proposed. The accuracy of the intellectual differentiation of blood plasma samples to the "norm" and "fibroadenoma" of breast was 82.7% by the method of linear discriminant analysis, and by the "fuzzy" logic method is 95.3%. The obtained results allow to confirm the potentially high level of reliability of the method of differentiation by "fuzzy" analysis.

Fuzzy control of small servo motors

NASA Technical Reports Server (NTRS)

Maor, Ron; Jani, Yashvant

1993-01-01

To explore the benefits of fuzzy logic and understand the differences between the classical control methods and fuzzy control methods, the Togai InfraLogic applications engineering staff developed and implemented a motor control system for small servo motors. The motor assembly for testing the fuzzy and conventional controllers consist of servo motor RA13M and an encoder with a range of 4096 counts. An interface card was designed and fabricated to interface the motor assembly and encoder to an IBM PC. The fuzzy logic based motor controller was developed using the TILShell and Fuzzy C Development System on an IBM PC. A Proportional-Derivative (PD) type conventional controller was also developed and implemented in the IBM PC to compare the performance with the fuzzy controller. Test cases were defined to include step inputs of 90 and 180 degrees rotation, sine and square wave profiles in 5 to 20 hertz frequency range, as well as ramp inputs. In this paper we describe our approach to develop a fuzzy as well as PH controller, provide details of hardware set-up and test cases, and discuss the performance results. In comparison, the fuzzy logic based controller handles the non-linearities of the motor assembly very well and provides excellent control over a broad range of parameters. Fuzzy technology, as indicated by our results, possesses inherent adaptive features.

Learning and Tuning of Fuzzy Rules

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1997-01-01

In this chapter, we review some of the current techniques for learning and tuning fuzzy rules. For clarity, we refer to the process of generating rules from data as the learning problem and distinguish it from tuning an already existing set of fuzzy rules. For learning, we touch on unsupervised learning techniques such as fuzzy c-means, fuzzy decision tree systems, fuzzy genetic algorithms, and linear fuzzy rules generation methods. For tuning, we discuss Jang's ANFIS architecture, Berenji-Khedkar's GARIC architecture and its extensions in GARIC-Q. We show that the hybrid techniques capable of learning and tuning fuzzy rules, such as CART-ANFIS, RNN-FLCS, and GARIC-RB, are desirable in development of a number of future intelligent systems.

Improvements to Earthquake Location with a Fuzzy Logic Approach

NASA Astrophysics Data System (ADS)

Gökalp, Hüseyin

2018-01-01

In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, Yading, E-mail: yading.yuan@mssm.edu; Chao, Ming; Sheu, Ren-Dih

Purpose: This work aims to develop a robust and efficient method to track the fuzzy borders between liver and the abutted organs where automatic liver segmentation usually suffers, and to investigate its applications in automatic liver segmentation on noncontrast-enhanced planning computed tomography (CT) images. Methods: In order to track the fuzzy liver–chestwall and liver–heart borders where oversegmentation is often found, a starting point and an ending point were first identified on the coronal view images; the fuzzy border was then determined as a geodesic curve constructed by minimizing the gradient-weighted path length between these two points near the fuzzy border.more » The minimization of path length was numerically solved by fast-marching method. The resultant fuzzy borders were incorporated into the authors’ automatic segmentation scheme, in which the liver was initially estimated by a patient-specific adaptive thresholding and then refined by a geodesic active contour model. By using planning CT images of 15 liver patients treated with stereotactic body radiation therapy, the liver contours extracted by the proposed computerized scheme were compared with those manually delineated by a radiation oncologist. Results: The proposed automatic liver segmentation method yielded an average Dice similarity coefficient of 0.930 ± 0.015, whereas it was 0.912 ± 0.020 if the fuzzy border tracking was not used. The application of fuzzy border tracking was found to significantly improve the segmentation performance. The mean liver volume obtained by the proposed method was 1727 cm{sup 3}, whereas it was 1719 cm{sup 3} for manual-outlined volumes. The computer-generated liver volumes achieved excellent agreement with manual-outlined volumes with correlation coefficient of 0.98. Conclusions: The proposed method was shown to provide accurate segmentation for liver in the planning CT images where contrast agent is not applied. The authors’ results also clearly demonstrated that the application of tracking the fuzzy borders could significantly reduce contour leakage during active contour evolution.« less

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators.

PubMed

Yin, Kedong; Yang, Benshuo; Li, Xuemei

2018-01-24

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making.

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators

PubMed Central

Yin, Kedong; Yang, Benshuo

2018-01-01

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making. PMID:29364849

Selection of a suitable method for the preparation of polymeric nanoparticles: multi-criteria decision making approach.

PubMed

Krishnamoorthy, Kannan; Mahalingam, Manikandan

2015-03-01

The present study is aimed to select the suitable method for preparation of camptothecin loaded polymeric nanoparticles by utilizing the multi-criteria decision making method. Novel approaches of drug delivery by formulation using nanotechnology are revolutionizing the future of medicine. Recent years have witnessed unprecedented growth of research and application in the area of nanotechnology. Nanoparticles have become an important area of research in the field of drug delivery because they have the ability to deliver a wide range of drug to varying areas of body. Despite of extensive research and development, polymeric nanoparticles are frequently used to improve the therapeutic effect of drugs. A number of techniques are available for the preparation of polymeric nanoparticles. The Analytical Hierarchy Process (AHP) is a method for decision making, which are derived from individual judgements for qualitative factors, using the pair-wise comparison matrix. In AHP, a decision hierarchy is constructed with a goal, criteria and alternatives. The model uses three main criteria 1) Instrument, 2) Process and Output and 3) Cost. In addition, there are eight sub-criteria's as well as eight alternatives. Pair-wise comparison matrixes are used to obtain the overall priority weight and ranking for the selection of suitable method. Nanoprecipitation technique is the most suitable method for the preparation of camptothecin loaded polymeric nanoparticles with the highest overall priority weight of 0.297 CONCLUSION: In particular, the result indicates that the priority weights obtained from AHP could be defined as a multiple output for finding out the most suitable method for preparation of camptothecin loaded polymeric nanoparticles.

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

NASA Astrophysics Data System (ADS)

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

Reliability apportionment approach for spacecraft solar array using fuzzy reasoning Petri net and fuzzy comprehensive evaluation

NASA Astrophysics Data System (ADS)

Wu, Jianing; Yan, Shaoze; Xie, Liyang; Gao, Peng

2012-07-01

The reliability apportionment of spacecraft solar array is of significant importance for spacecraft designers in the early stage of design. However, it is difficult to use the existing methods to resolve reliability apportionment problem because of the data insufficiency and the uncertainty of the relations among the components in the mechanical system. This paper proposes a new method which combines the fuzzy comprehensive evaluation with fuzzy reasoning Petri net (FRPN) to accomplish the reliability apportionment of the solar array. The proposed method extends the previous fuzzy methods and focuses on the characteristics of the subsystems and the intrinsic associations among the components. The analysis results show that the synchronization mechanism may obtain the highest reliability value and the solar panels and hinges may get the lowest reliability before design and manufacturing. Our developed method is of practical significance for the reliability apportionment of solar array where the design information has not been clearly identified, particularly in early stage of design.

A comparative approach for ranking contaminated sites based on the risk assessment paradigm using fuzzy PROMETHEE.

PubMed

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

Sodium-dependent potassium channels of a Slack-like subtype contribute to the slow afterhyperpolarization in lamprey spinal neurons

PubMed Central

Wallén, Peter; Robertson, Brita; Cangiano, Lorenzo; Löw, Peter; Bhattacharjee, Arin; Kaczmarek, Leonard K; Grillner, Sten

2007-01-01

The slow afterhyperpolarization (sAHP) following the action potential is the main determinant of spike frequency regulation. The sAHP after single action potentials in neurons of the lamprey locomotor network is largely due to calcium-dependent K+ channels (80%), activated by calcium entering the cell during the spike. The residual (20%) component becomes prominent during high level activity (50% of the sAHP). It is not Ca2+ dependent, has a reversal potential like that of potassium, and is not affected by chloride injection. It is not due to rapid activation of Na+/K+-ATPase. This non-KCa-sAHP is reduced markedly in amplitude when sodium ions are replaced by lithium ions, and is thus sodium dependent. Quinidine also blocks this sAHP component, further indicating an involvement of sodium-dependent potassium channels (KNa). Modulators tested do not influence the KNa-sAHP amplitude. Immunofluorescence labelling with an anti-Slack antibody revealed distinct immunoreactivity of medium-sized and large neurons in the grey matter of the lamprey spinal cord, suggesting the presence of a Slack-like subtype of KNa channel. The results strongly indicate that a KNa potassium current contributes importantly to the sAHP and thereby to neuronal frequency regulation during high level burst activity as during locomotion. This is, to our knowledge, the first demonstration of a functional role for the Slack gene in contributing to the slow AHP. PMID:17884929

A two-phased fuzzy decision making procedure for IT supplier selection

NASA Astrophysics Data System (ADS)

Shohaimay, Fairuz; Ramli, Nazirah; Mohamed, Siti Rosiah; Mohd, Ainun Hafizah

2013-09-01

In many studies on fuzzy decision making, linguistic terms are usually represented by corresponding fixed triangular or trapezoidal fuzzy numbers. However, the fixed fuzzy numbers used in decision making process may not explain the actual respondents' opinions. Hence, a two-phased fuzzy decision making procedure is proposed. First, triangular fuzzy numbers were built based on respondents' opinions on the appropriate range (0-100) for each seven-scale linguistic terms. Then, the fuzzy numbers were integrated into fuzzy decision making model. The applicability of the proposed method is demonstrated in a case study of supplier selection in Information Technology (IT) department. The results produced via the developed fuzzy numbers were consistent with the results obtained using fixed fuzzy numbers. However, with different set of fuzzy numbers based on respondents, there is a difference in the ranking of suppliers based on criterion X1 (background of supplier). Hopefully the proposed model which incorporates fuzzy numbers based on respondents will provide a more significant meaning towards future decision making.

Development of a model for on-line control of crystal growth by the AHP method

NASA Astrophysics Data System (ADS)

Gonik, M. A.; Lomokhova, A. V.; Gonik, M. M.; Kuliev, A. T.; Smirnov, A. D.

2007-05-01

The possibility to apply a simplified 2D model for heat transfer calculations in crystal growth by the axial heat close to phase interface (AHP) method is discussed in this paper. A comparison with global heat transfer calculations with the CGSim software was performed to confirm the accuracy of this model. The simplified model was shown to provide adequate results for the shape of the melt-crystal interface and temperature field in an opaque (Ge) and a transparent crystal (CsI:Tl). The model proposed is used for identification of the growth setup as a control object, for synthesis of a digital controller (PID controller at the present stage) and, finally, in on-line simulations of crystal growth control.

Fuzzy Markov random fields versus chains for multispectral image segmentation.

PubMed

Salzenstein, Fabien; Collet, Christophe

2006-11-01

This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data.

Learning fuzzy information in a hybrid connectionist, symbolic model

NASA Technical Reports Server (NTRS)

Romaniuk, Steve G.; Hall, Lawrence O.

1993-01-01

An instance-based learning system is presented. SC-net is a fuzzy hybrid connectionist, symbolic learning system. It remembers some examples and makes groups of examples into exemplars. All real-valued attributes are represented as fuzzy sets. The network representation and learning method is described. To illustrate this approach to learning in fuzzy domains, an example of segmenting magnetic resonance images of the brain is discussed. Clearly, the boundaries between human tissues are ill-defined or fuzzy. Example fuzzy rules for recognition are generated. Segmentations are presented that provide results that radiologists find useful.

Improving land resource evaluation using fuzzy neural network ensembles

USGS Publications Warehouse

Xue, Yue-Ju; HU, Y.-M.; Liu, S.-G.; YANG, J.-F.; CHEN, Q.-C.; BAO, S.-T.

2007-01-01

Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts' experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network (BPNN), a fuzzy radial basis function neural network (RBFNN), a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators' experiences was considerably reduced. ?? 2007 Soil Science Society of China.

A dynamic fuzzy genetic algorithm for natural image segmentation using adaptive mean shift

NASA Astrophysics Data System (ADS)

Arfan Jaffar, M.

2017-01-01

In this paper, a colour image segmentation approach based on hybridisation of adaptive mean shift (AMS), fuzzy c-mean and genetic algorithms (GAs) is presented. Image segmentation is the perceptual faction of pixels based on some likeness measure. GA with fuzzy behaviour is adapted to maximise the fuzzy separation and minimise the global compactness among the clusters or segments in spatial fuzzy c-mean (sFCM). It adds diversity to the search process to find the global optima. A simple fusion method has been used to combine the clusters to overcome the problem of over segmentation. The results show that our technique outperforms state-of-the-art methods.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

PubMed

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-12-01

Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream

PubMed Central

Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.

2016-01-01

This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081

12 CFR 1291.3 - AHP Implementation Plan.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false AHP Implementation Plan. 1291.3 Section 1291.3 Banks and Banking FEDERAL HOUSING FINANCE AGENCY HOUSING GOALS AND MISSION FEDERAL HOME LOAN BANKS... AHP Implementation Plan without first consulting its Advisory Council. The Bank's board of directors...

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

NASA Astrophysics Data System (ADS)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

Yarn supplier selection using analytical hierarchy process (AHP) and standardized unitless rating (SUR) method on textile industry

NASA Astrophysics Data System (ADS)

Erfaisalsyah, M. H.; Mansur, A.; Khasanah, A. U.

2017-11-01

For a company which engaged in the textile field, specify the supplier of raw materials for production is one important part of supply chain management which can affect the company's business processes. This study aims to identify the best suppliers of raw material suppliers of yarn for PC. PKBI based on several criteria. In this study, the integration between the Analytical Hierarchy Process (AHP) and the Standardized Unitless Rating (SUR) are used to assess the performance of the suppliers. By using AHP, it can be known the value of the relative weighting of each criterion. While SUR shows the sequence performance value of the supplier. The result of supplier ranking calculation can be used to know the strengths and weaknesses of each supplier based on its performance criteria. From the final result, it can be known which suppliers should improve their performance in order to create long term cooperation with the company.

Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

NASA Astrophysics Data System (ADS)

Kim, Ki Wan; Lee, Won Oh; Kim, Yeong Gon; Hong, Hyung Gil; Lee, Eui Chul; Park, Kang Ryoung

2015-03-01

The classification of eye openness and closure has been researched in various fields, e.g., driver drowsiness detection, physiological status analysis, and eye fatigue measurement. For a classification with high accuracy, accurate segmentation of the eye region is required. Most previous research used the segmentation method by image binarization on the basis that the eyeball is darker than skin, but the performance of this approach is frequently affected by thick eyelashes or shadows around the eye. Thus, we propose a fuzzy-based method for classifying eye openness and closure. First, the proposed method uses I and K color information from the HSI and CMYK color spaces, respectively, for eye segmentation. Second, the eye region is binarized using the fuzzy logic system based on I and K inputs, which is less affected by eyelashes and shadows around the eye. The combined image of I and K pixels is obtained through the fuzzy logic system. Third, in order to reflect the effect by all the inference values on calculating the output score of the fuzzy system, we use the revised weighted average method, where all the rectangular regions by all the inference values are considered for calculating the output score. Fourth, the classification of eye openness or closure is successfully made by the proposed fuzzy-based method with eye images of low resolution which are captured in the environment of people watching TV at a distance. By using the fuzzy logic system, our method does not require the additional procedure of training irrespective of the chosen database. Experimental results with two databases of eye images show that our method is superior to previous approaches.

[Predicting Incidence of Hepatitis E in Chinausing Fuzzy Time Series Based on Fuzzy C-Means Clustering Analysis].

PubMed

Luo, Yi; Zhang, Tao; Li, Xiao-song

2016-05-01

To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China. Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models. The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model. The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

Should I stay or should I go? Exploring the job preferences of allied health professionals working with people with disability in rural Australia.

PubMed

Gallego, Gisselle; Dew, Angela; Lincoln, Michelle; Bundy, Anita; Chedid, Rebecca Jean; Bulkeley, Kim; Brentnall, Jennie; Veitch, Craig

2015-06-30

The uneven distribution of allied health professionals (AHPs) in rural and remote Australia and other countries is well documented. In Australia, like elsewhere, service delivery to rural and remote communities is complicated because relatively small numbers of clients are dispersed over large geographic areas. This uneven distribution of AHPs impacts significantly on the provision of services particularly in areas of special need such as mental health, aged care and disability services. This study aimed to determine the relative importance that AHPs (physiotherapists, occupational therapists, speech pathologists and psychologists - "therapists") living in a rural area of Australia and working with people with disability, place on different job characteristics and how these may affect their retention. A cross-sectional survey was conducted using an online questionnaire distributed to AHPs working with people with disability in a rural area of Australia over a 3-month period. Information was sought about various aspects of the AHPs' current job, and their workforce preferences were explored using a best-worst scaling discrete choice experiment (BWSDCE). Conditional logistic and latent class regression models were used to determine AHPs' relative preferences for six different job attributes. One hundred ninety-nine AHPs completed the survey; response rate was 51 %. Of those, 165 completed the BWSDCE task. For this group of AHPs, "high autonomy of practice" is the most valued attribute level, followed by "travel BWSDCE arrangements: one or less nights away per month", "travel arrangements: two or three nights away per month" and "adequate access to professional development". On the other hand, the least valued attribute levels were "travel arrangements: four or more nights per month", "limited autonomy of practice" and "minimal access to professional development". Except for "some job flexibility", all other attributes had a statistical influence on AHPs' job preference. Preferences differed according to age, marital status and having dependent children. This study allowed the identification of factors that contribute to AHPs' employment decisions about staying and working in a rural area. This information can improve job designs in rural areas to increase retention.

Voltage-clamp analysis of the potentiation of the slow Ca2+-activated K+ current in hippocampal pyramidal neurons.

PubMed

Borde, M; Bonansco, C; Fernández de Sevilla, D; Le Ray, D; Buño, W

2000-01-01

Exploring the principles that govern activity-dependent changes in excitability is an essential step to understand the function of the nervous system, because they act as a general postsynaptic control mechanism that modulates the flow of synaptic signals. We show an activity-dependent potentiation of the slow Ca2+-activated K+ current (sl(AHP)) which induces sustained decreases in the excitability in CA1 pyramidal neurons. We analyzed the sl(AHP) using the slice technique and voltage-clamp recordings with sharp or patch-electrodes. Using sharp electrodes-repeated activation with depolarizing pulses evoked a prolonged (8-min) potentiation of the amplitude (171%) and duration (208%) of the sl(AHP). Using patch electrodes, early after entering the whole-cell configuration (<20 min), responses were as those reported above. However, although the sl(AHP) remained unchanged, its potentiation was markedly reduced in later recordings, suggesting that the underlying mechanisms were rapidly eliminated by intracellular dialysis. Inhibition of L-type Ca2+ current by nifedipine (20 microM) markedly reduced the sl(AHP) (79%) and its potentiation (55%). Ryanodine (20 microM) that blocks the release of intracellular Ca2+ also reduced sl(AHP) (29%) and its potentiation (25%). The potentiation of the sl(AHP) induced a marked and prolonged (>50%; approximately equals 8 min) decrease in excitability. The results suggest that sl(AHP) is potentiated as a result of an increased intracellular Ca2+ concentration ([Ca2+]i) following activation of voltage-gated L-type Ca2+ channels, aided by the subsequent release of Ca2+ from intracellular stores. Another possibility is that repeated activation increases the Ca2+-binding capacity of the channels mediating the sl(AHP). This potentiation of the sl(AHP) could be relevant in hippocampal physiology, because the changes in excitability it causes may regulate the induction threshold of the long-term potentiation of synaptic efficacy. Moreover, the potentiation would act as a protective mechanism by reducing excitability and preventing the accumulation of intracellular Ca2+ to toxic levels when intense synaptic activation occurs.

Mining Building Energy Management System Data Using Fuzzy Anomaly Detection and Linguistic Descriptions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dumidu Wijayasekara; Ondrej Linda; Milos Manic

Building Energy Management Systems (BEMSs) are essential components of modern buildings that utilize digital control technologies to minimize energy consumption while maintaining high levels of occupant comfort. However, BEMSs can only achieve these energy savings when properly tuned and controlled. Since indoor environment is dependent on uncertain criteria such as weather, occupancy, and thermal state, performance of BEMS can be sub-optimal at times. Unfortunately, the complexity of BEMS control mechanism, the large amount of data available and inter-relations between the data can make identifying these sub-optimal behaviors difficult. This paper proposes a novel Fuzzy Anomaly Detection and Linguistic Description (Fuzzy-ADLD)more » based method for improving the understandability of BEMS behavior for improved state-awareness. The presented method is composed of two main parts: 1) detection of anomalous BEMS behavior and 2) linguistic representation of BEMS behavior. The first part utilizes modified nearest neighbor clustering algorithm and fuzzy logic rule extraction technique to build a model of normal BEMS behavior. The second part of the presented method computes the most relevant linguistic description of the identified anomalies. The presented Fuzzy-ADLD method was applied to real-world BEMS system and compared against a traditional alarm based BEMS. In six different scenarios, the Fuzzy-ADLD method identified anomalous behavior either as fast as or faster (an hour or more), that the alarm based BEMS. In addition, the Fuzzy-ADLD method identified cases that were missed by the alarm based system, demonstrating potential for increased state-awareness of abnormal building behavior.« less

Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization.

PubMed

Juang, Chia-Feng; Hsu, Chia-Hung

2009-12-01

This paper proposes a new reinforcement-learning method using online rule generation and Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy controller is based on an interval type-2 fuzzy system (IT2FS). The antecedent part in the designed IT2FS uses interval type-2 fuzzy sets to improve controller robustness to noise. There are initially no fuzzy rules in the IT2FS. The ORGQACO concurrently designs both the structure and parameters of an IT2FS. We propose an online interval type-2 rule generation method for the evolution of system structure and flexible partitioning of the input space. Consequent part parameters in an IT2FS are designed using Q -values and the reinforcement local-global ant colony optimization algorithm. This algorithm selects the consequent part from a set of candidate actions according to ant pheromone trails and Q-values, both of which are updated using reinforcement signals. The ORGQACO design method is applied to the following three control problems: 1) truck-backing control; 2) magnetic-levitation control; and 3) chaotic-system control. The ORGQACO is compared with other reinforcement-learning methods to verify its efficiency and effectiveness. Comparisons with type-1 fuzzy systems verify the noise robustness property of using an IT2FS.

Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

NASA Astrophysics Data System (ADS)

Pourghasemi, Hamid Reza; Rossi, Mauro

2017-10-01

Landslides are identified as one of the most important natural hazards in many areas throughout the world. The essential purpose of this study is to compare general linear model (GLM), general additive model (GAM), multivariate adaptive regression spline (MARS), and modified analytical hierarchy process (M-AHP) models and assessment of their performances for landslide susceptibility modeling in the west of Mazandaran Province, Iran. First, landslides were identified by interpreting aerial photographs, and extensive field works. In total, 153 landslides were identified in the study area. Among these, 105 landslides were randomly selected as training data (i.e. used in the models training) and the remaining 48 (30 %) cases were used for the validation (i.e. used in the models validation). Afterward, based on a deep literature review on 220 scientific papers (period between 2005 and 2012), eleven conditioning factors including lithology, land use, distance from rivers, distance from roads, distance from faults, slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, and profile curvature were selected. The Certainty Factor (CF) model was used for managing uncertainty in rule-based systems and evaluation of the correlation between the dependent (landslides) and independent variables. Finally, the landslide susceptibility zonation was produced using GLM, GAM, MARS, and M-AHP models. For evaluation of the models, the area under the curve (AUC) method was used and both success and prediction rate curves were calculated. The evaluation of models for GLM, GAM, and MARS showed 90.50, 88.90, and 82.10 % for training data and 77.52, 70.49, and 78.17 % for validation data, respectively. Furthermore, The AUC value of the produced landslide susceptibility map using M-AHP showed a training value of 77.82 % and validation value of 82.77 % accuracy. Based on the overall assessments, the proposed approaches showed reasonable results for landslide susceptibility mapping in the study area. Moreover, results obtained showed that the M-AHP model performed slightly better than the MARS, GLM, and GAM models in prediction. These algorithms can be very useful for landslide susceptibility and hazard mapping and land use planning in regional scale.

Selection of a Suitable Method for the Preparation of Polymeric Nanoparticles: Multi-Criteria Decision Making Approach

PubMed Central

Krishnamoorthy, Kannan; Mahalingam, Manikandan

2015-01-01

Purpose: The present study is aimed to select the suitable method for preparation of camptothecin loaded polymeric nanoparticles by utilizing the multi-criteria decision making method. Novel approaches of drug delivery by formulation using nanotechnology are revolutionizing the future of medicine. Recent years have witnessed unprecedented growth of research and application in the area of nanotechnology. Nanoparticles have become an important area of research in the field of drug delivery because they have the ability to deliver a wide range of drug to varying areas of body. Methods: Despite of extensive research and development, polymeric nanoparticles are frequently used to improve the therapeutic effect of drugs. A number of techniques are available for the preparation of polymeric nanoparticles. The Analytical Hierarchy Process (AHP) is a method for decision making, which are derived from individual judgements for qualitative factors, using the pair-wise comparison matrix. In AHP, a decision hierarchy is constructed with a goal, criteria and alternatives. Results: The model uses three main criteria 1) Instrument, 2) Process and Output and 3) Cost. In addition, there are eight sub-criteria’s as well as eight alternatives. Pair-wise comparison matrixes are used to obtain the overall priority weight and ranking for the selection of suitable method. Nanoprecipitation technique is the most suitable method for the preparation of camptothecin loaded polymeric nanoparticles with the highest overall priority weight of 0.297 Conclusion: In particular, the result indicates that the priority weights obtained from AHP could be defined as a multiple output for finding out the most suitable method for preparation of camptothecin loaded polymeric nanoparticles. PMID:25789220

A GIS-based model of potential groundwater yield zonation for a sandstone aquifer in the Juye Coalfield, Shangdong, China

NASA Astrophysics Data System (ADS)

Yin, Huiyong; Shi, Yongli; Niu, Huigong; Xie, Daolei; Wei, Jiuchuan; Lefticariu, Liliana; Xu, Shuanxiang

2018-02-01

Resolving the potential groundwater yield zonation of sandstone aquifers occurring at depths of several hundred meters has been an important and challenging objective of the hydrogeological research focused on preventing flood hazards in coal mines. Using accessible geological exploration data we put forward a method of predicting the spatial distribution of groundwater storage potential in sandstone aquifers from Permian-age coal deposits in Juye Coalfield, Shangdong, China. A Geological, Tectonic and Lithological Composition Index (GTLCI) model was created using the following parameters: sandstone depth and thickness, faults length density (FaLD), faults density (FaD), fault frequency density (FaFD), fault scale density (FaSD), variation coefficient of the slope (VCS) of the coal seam, intensity index of folds in horizontal direction (IIFoH), and lithological composition index (LCI). Each of these factors was subsequently divided into 5 classes. The analytic hierarchy process (AHP) and trapezoidal fuzzy number (TFN) method was applied to calculate the weight of the conditioning factor and their respective sub-classes. Groundwater yield potential contour map, which was initially constructed using the GTLCI values revealed four groundwater abundance zones. The map was further refined by taking into account hydrogeologic data collected during mining activities. The GTLCI model predictive success rate of 80% was explained by the limited number of boreholes available for validation. It is considered that the GTLCI model is effective at predicting zonation of groundwater yield in the sandstone aquifers from Permian- age coal deposits in Juye Coalfield, China.

Optimization methods for activities selection problems

NASA Astrophysics Data System (ADS)

Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

2017-08-01

Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

NASA Astrophysics Data System (ADS)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

Some Muirhead Mean Operators for Intuitionistic Fuzzy Numbers and Their Applications to Group Decision Making.

PubMed

Liu, Peide; Li, Dengfeng

2017-01-01

Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. Besides, it is a universal operator since it can contain other general operators by assigning some special parameter values. However, the MM can only process the crisp numbers. Inspired by the MM' advantages, the aim of this paper is to extend MM to process the intuitionistic fuzzy numbers (IFNs) and then to solve the multi-attribute group decision making (MAGDM) problems. Firstly, we develop some intuitionistic fuzzy Muirhead mean (IFMM) operators by extending MM to intuitionistic fuzzy information. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present two new methods to deal with MAGDM problems with the intuitionistic fuzzy information based on the proposed MM operators. Finally, we verify the validity and reliability of our methods by using an application example, and analyze the advantages of our methods by comparing with other existing methods.

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

Fuzzy observer-based control for maximum power-point tracking of a photovoltaic system

NASA Astrophysics Data System (ADS)

Allouche, M.; Dahech, K.; Chaabane, M.; Mehdi, D.

2018-04-01

This paper presents a novel fuzzy control design method for maximum power-point tracking (MPPT) via a Takagi and Sugeno (TS) fuzzy model-based approach. A knowledge-dynamic model of the PV system is first developed leading to a TS representation by a simple convex polytopic transformation. Then, based on this exact fuzzy representation, a H∞ observer-based fuzzy controller is proposed to achieve MPPT even when we consider varying climatic conditions. A specified TS reference model is designed to generate the optimum trajectory which must be tracked to ensure maximum power operation. The controller and observer gains are obtained in a one-step procedure by solving a set of linear matrix inequalities (LMIs). The proposed method has been compared with some classical MPPT techniques taking into account convergence speed and tracking accuracy. Finally, various simulation and experimental tests have been carried out to illustrate the effectiveness of the proposed TS fuzzy MPPT strategy.

Evaluation about the performance of E-government based on interval-valued intuitionistic fuzzy set.

PubMed

Zhang, Shuai; Yu, Dejian; Wang, Yan; Zhang, Wenyu

2014-01-01

The evaluation is an important approach to promote the development of the E-Government. Since the rapid development of E-Government in the world, the E-Government performance evaluation has become a hot issue in the academia. In this paper, we develop a new evaluation method for the development of the E-Government based on the interval-valued intuitionistic fuzzy set which is a powerful technique in expressing the uncertainty of the real situation. First, we extend the geometric Heronian mean (GHM) operator to interval-valued intuitionistic fuzzy environment and proposed the interval-valued intuitionistic fuzzy GHM (IIFGHM) operator. Then, we investigate the relationships between the IIFGHM operator and some existing ones, such as generalized interval-valued intuitionistic fuzzy HM (GIIFHM) and interval-valued intuitionistic fuzzy weighted Bonferoni mean operator. Furthermore, we validate the effectiveness of the proposed method using a real case about the E-Government evaluation in Hangzhou City, China.

Assessing the service quality of Iran military hospitals: Joint Commission International standards and Analytic Hierarchy Process (AHP) technique

PubMed Central

Bahadori, Mohammadkarim; Ravangard, Ramin; Yaghoubi, Maryam; Alimohammadzadeh, Khalil

2014-01-01

Background: Military hospitals are responsible for preserving, restoring and improving the health of not only armed forces, but also other people. According to the military organizations strategy, which is being a leader and pioneer in all areas, providing quality health services is one of the main goals of the military health care organizations. This study was aimed to evaluate the service quality of selected military hospitals in Iran based on the Joint Commission International (JCI) standards and comparing these hospitals with each other and ranking them using the analytic hierarchy process (AHP) technique in 2013. Materials and Methods: This was a cross-sectional and descriptive study conducted on five military hospitals, selected using the purposive sampling method, in 2013. Required data collected using checklists of accreditation standards and nominal group technique. AHP technique was used for prioritizing. Furthermore, Expert Choice 11.0 was used to analyze the collected data. Results: Among JCI standards, the standards of access to care and continuity of care (weight = 0.122), quality improvement and patient safety (weight = 0.121) and leadership and management (weight = 0.117) had the greatest importance, respectively. Furthermore, in the overall ranking, BGT (weight = 0.369), IHM (0.238), SAU (0.202), IHK (weight = 0.125) and SAB (weight = 0.066) ranked first to fifth, respectively. Conclusion: AHP is an appropriate technique for measuring the overall performance of hospitals and their quality of services. It is a holistic approach that takes all hospital processes into consideration. The results of the present study can be used to improve hospitals performance through identifying areas, which are in need of focus for quality improvement and selecting strategies to improve service quality. PMID:25250364

Breast mass segmentation in mammograms combining fuzzy c-means and active contours

NASA Astrophysics Data System (ADS)

Hmida, Marwa; Hamrouni, Kamel; Solaiman, Basel; Boussetta, Sana

2018-04-01

Segmentation of breast masses in mammograms is a challenging issue due to the nature of mammography and the characteristics of masses. In fact, mammographic images are poor in contrast and breast masses have various shapes and densities with fuzzy and ill-defined borders. In this paper, we propose a method based on a modified Chan-Vese active contour model for mass segmentation in mammograms. We conduct the experiment on mass Regions of Interest (ROI) extracted from the MIAS database. The proposed method consists of mainly three stages: Firstly, the ROI is preprocessed to enhance the contrast. Next, two fuzzy membership maps are generated from the preprocessed ROI based on fuzzy C-Means algorithm. These fuzzy membership maps are finally used to modify the energy of the Chan-Vese model and to perform the final segmentation. Experimental results indicate that the proposed method yields good mass segmentation results.

Research on the selection of innovation compound using Possibility Construction Space Theory and fuzzy pattern recognition

NASA Astrophysics Data System (ADS)

Xie, Songhua; Li, Dehua; Nie, Hui

2009-10-01

There are a large number of fuzzy concepts and fuzzy phenomena in traditional Chinese medicine, which have led to great difficulties for study of traditional Chinese medicine. In this paper, the mathematical methods are used to quantify fuzzy concepts of drugs and prescription. We put forward the process of innovation formulations and selection method in Chinese medicine based on the Possibility Construction Space Theory (PCST) and fuzzy pattern recognition. Experimental results show that the method of selecting medicines from a number of characteristics of traditional Chinese medicine is consistent with the basic theory of traditional Chinese medicine. The results also reflect the integrated effects of the innovation compound. Through the use of the innovation formulations system, we expect to provide software tools for developing new traditional Chinese medicine and to inspire traditional Chinese medicine researchers to develop novel drugs.

A Fuzzy Reasoning Design for Fault Detection and Diagnosis of a Computer-Controlled System

PubMed Central

Ting, Y.; Lu, W.B.; Chen, C.H.; Wang, G.K.

2008-01-01

A Fuzzy Reasoning and Verification Petri Nets (FRVPNs) model is established for an error detection and diagnosis mechanism (EDDM) applied to a complex fault-tolerant PC-controlled system. The inference accuracy can be improved through the hierarchical design of a two-level fuzzy rule decision tree (FRDT) and a Petri nets (PNs) technique to transform the fuzzy rule into the FRVPNs model. Several simulation examples of the assumed failure events were carried out by using the FRVPNs and the Mamdani fuzzy method with MATLAB tools. The reasoning performance of the developed FRVPNs was verified by comparing the inference outcome to that of the Mamdani method. Both methods result in the same conclusions. Thus, the present study demonstratrates that the proposed FRVPNs model is able to achieve the purpose of reasoning, and furthermore, determining of the failure event of the monitored application program. PMID:19255619

Learning and tuning fuzzy logic controllers through reinforcements.

PubMed

Berenji, H R; Khedkar, P

1992-01-01

A method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. It is shown that: the generalized approximate-reasoning-based intelligent control (GARIC) architecture learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Refining Linear Fuzzy Rules by Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil

1996-01-01

Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.

An improved advertising CTR prediction approach based on the fuzzy deep neural network

PubMed Central

Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise. PMID:29727443

An improved advertising CTR prediction approach based on the fuzzy deep neural network.

PubMed

Jiang, Zilong; Gao, Shu; Li, Mingjiang

2018-01-01

Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (FGBRBM) is first applied to input raw data from advertising datasets. Next, fuzzy restricted Boltzmann machine (FRBM) is used to construct the fuzzy deep belief network (FDBN) with the unsupervised method layer by layer. Finally, fuzzy logistic regression (FLR) is utilized for modeling the CTR. The experimental results show that the proposed FDNN model outperforms several baseline models in terms of both data representation capability and robustness in advertising click log datasets with noise.

Fuzzy risk analysis of a modern γ-ray industrial irradiator.

PubMed

Castiglia, F; Giardina, M

2011-06-01

Fuzzy fault tree analyses were used to investigate accident scenarios that involve radiological exposure to operators working in industrial γ-ray irradiation facilities. The HEART method, a first generation human reliability analysis method, was used to evaluate the probability of adverse human error in these analyses. This technique was modified on the basis of fuzzy set theory to more directly take into account the uncertainties in the error-promoting factors on which the methodology is based. Moreover, with regard to some identified accident scenarios, fuzzy radiological exposure risk, expressed in terms of potential annual death, was evaluated. The calculated fuzzy risks for the examined plant were determined to be well below the reference risk suggested by International Commission on Radiological Protection.

Risk prioritisation using the analytic hierarchy process

NASA Astrophysics Data System (ADS)

Sum, Rabihah Md.

2015-12-01

This study demonstrated how to use the Analytic Hierarchy Process (AHP) to prioritise risks of an insurance company. AHP is a technique to structure complex problems by arranging elements of the problems in a hierarchy, assigning numerical values to subjective judgements on the relative importance of the elements and synthesizing the judgements to determine which elements have the highest priority. The study is motivated by wide application of AHP as a prioritisation technique in complex problems. It aims to show AHP is able to minimise some limitations of risk assessment technique using likelihood and impact. The study shows AHP is able to provide consistency check on subjective judgements, organise a large number of risks into a structured framework, assist risk managers to make explicit risk trade-offs, and provide an easy to understand and systematic risk assessment process.

Evaluation of Wheel Loaders in Open Pit Marble Quarrying by Using the AHP and Topsis Approaches / Ocena pracy ładowarki na podwoziu kołowym w odkrywkowej kopalni marmuru w oparciu o metody AHP i topsis

NASA Astrophysics Data System (ADS)

Kun, Mete; Topaloǧlu, Şeyda; Malli, Tahir

2013-03-01

The marble mining in Turkey has been rising since the early 80's. In relation to that, the marble income has become noticeably bigger than those of other mining sectors. In recent years, marble and natural stone export composes half of the total mine export with a value of two billion dollars. This rapid development observed in marble operation has increased the importance of mining economics, income-expenditure balance and cost analysis. The most important cost elements observed in marble quarrying are machinery and equipment, labor costs and geological structures of the field. The aim of this study is to is to propose a multi-criteria decision making (MCDM) approach to evaluate the wheel loader alternatives and select the best loader under multiple criteria. A two-step methodology based on two MCDM methods, which are namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation procedure. More precisely, AHP is applied to determine the relative weights of evaluation criteria and TOPSIS is applied to rank the wheel loader alternatives. The proposed approach also provides a relatively simple and very well suited decision making tool for this type of decision making problems.

Efficient enzymatic synthesis and dual-colour fluorescent labelling of DNA probes using long chain azido-dUTP and BCN dyes

PubMed Central

Ren, Xiaomei; El-Sagheer, Afaf H.; Brown, Tom

2016-01-01

A sterically undemanding azide analogue of dTTP (AHP dUTP) with an alkyl chain and ethynyl attachment to the nucleobase was designed and incorporated into DNA by primer extension, reverse transcription and polymerase chain reaction (PCR). An azide-modified 523 bp PCR amplicon with all 335 thymidines replaced by AHP dU was shown to be a perfect copy of the template from which it was amplified. Replacement of thymidine with AHP dU increases duplex stability, accounting in part for the high incorporation efficiency of the azide-modified triphosphate. Single-stranded azide-labelled DNA was conveniently prepared from PCR products by λ-exonuclease digestion and streptavidin magnetic bead isolation. Efficient fluorescent labelling of single and double-stranded DNA was carried out using dyes functionalized with bicyclo[6.1.0]non-4-yne (BCN) via the strain-promoted alkyne-azide cycloaddition (SPAAC) reaction. This revealed that the degree of labelling must be carefully controlled to achieve optimum fluorescence and avoid fluorescence quenching. Dual-coloured probes were obtained in a single tube fluorescent labelling reaction; and varying the ratios of the two dyes provides a simple method to prepare DNA probes with unique fluorescent signatures. AHP dUTP is a versatile clickable nucleotide with potentially wide applications in biology and nanotechnology including single molecule studies and synthesis of modified aptamer libraries via SELEX. PMID:26819406

Characterization of phenotypic and genotypic drug resistance patterns of Mycobacterium tuberculosis isolates from a city in Mexico.

PubMed

Flores-Treviño, Samantha; Morfín-Otero, Rayo; Rodríguez-Noriega, Eduardo; González-Díaz, Esteban; Pérez-Gómez, Héctor Raúl; Mendoza-Olazarán, Soraya; Balderas-Rentería, Isaías; González, Gloria María; Garza-González, Elvira

2015-03-01

The emergence of multidrug-resistant (MDR) Mycobacterium tuberculosis strains has become a worldwide health care problem, making treatment of tuberculosis difficult. The aim of this study was to determine phenotypic resistance and gene mutations associated with MDR of clinical isolates of Mycobacterium tuberculosis from Guadalajara, Mexico. One hundred and five isolates were subjected to drug susceptibility testing to first line drugs using the proportion and Mycobacteria Growth Indicator Tube (MGIT) methods. Genes associated with isoniazid (inhA, katG, ahpC) and rifampicin (rpoB) resistance were analyzed by either pyrosequencing or PCR-RFLP. Resistance to any drug was detected in 48.6% of isolates, of which 40% were isoniazid-resistant, 20% were rifampicin-resistant and 19% were MDR. Drug-resistant isolates had the following frequency of mutations in rpoB (48%), katG (14%), inhA (26%), ahpC (26%). Susceptible isolates also had a mutation in ahpC (29%). This is the first analysis of mutations associated with MDR of M. tuberculosis in Guadalajara. Commonly reported mutations worldwide were found in rpoB, katG and inhA genes. Substitution C to T in position -15 of the ahpC gene may possibly be a polymorphism. Copyright © 2013 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

An architecture for designing fuzzy logic controllers using neural networks

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

Fuzzy mobile-robot positioning in intelligent spaces using wireless sensor networks.

PubMed

Herrero, David; Martínez, Humberto

2011-01-01

This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using wireless sensor networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and unreliable. The proposed method makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the proposed approach is compared with a probabilistic technique showing that the fuzzy approach is able to handle highly uncertain situations that are difficult to manage by well-known localization methods.

Comparative Ploidy Proteomics of Candida albicans Biofilms Unraveled the Role of the AHP1 Gene in the Biofilm Persistence Against Amphotericin B*

PubMed Central

Zeng, Guisheng; Qingsong, Lin; Kwang, Lim Teck; Tong, Cao; Chan, Fong Yee; Wang, Yue; Seneviratne, Chaminda Jayampath

2016-01-01

Candida albicans is a major fungal pathogen causing lethal infections in immunocompromised patients. C. albicans forms antifungal tolerant biofilms contributing significantly to therapeutic failure. The recently established haploid C. albicans biofilm model provides a new toolbox to uncover the mechanism governing the higher antifungal tolerance of biofilms. Here, we comprehensively examined the proteomics and antifungal susceptibility of standard diploid (SC5314 and BWP17) and stable haploid (GZY792 and GZY803) strains of C. albicans biofilms. Subsequent downstream analyses identified alkyl hydroperoxide reductase 1 (AHP1) as a critical determinant of C. albicans biofilm's tolerance of amphotericin B. At 32 μg/ml of amphotericin B, GZY803 haploid biofilms showed 0.1% of persister population as compared with 1% of the diploid biofilms. AHP1 expression was found to be lower in GZY803 biofilms, and AHP1 overexpression in GZY803 restored the percentage of persister population. Consistently, deleting AHP1 in the diploid strain BWP17 caused a similar increase in amphotericin B susceptibility. AHP1 expression was also positively correlated with the antioxidant potential. Furthermore, C. albicans ira2Δ/Δ biofilms were susceptible to amphotericin B and had a diminished antioxidant capacity. Interestingly, AHP1 overexpression in the ira2Δ/Δ strain restored the antioxidant potential and enhanced the persister population against amphotericin B, and shutting down the AHP1 expression in ira2Δ/Δ biofilms reversed the effect. In conclusion, we provide evidence that the AHP1 gene critically determines the amphotericin B tolerance of C. albicans biofilms possibly by maintaining the persisters' antioxidant capacity. This finding will open up new avenues for developing therapies targeting the persister population of C. albicans biofilms. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD004274. PMID:27644984

The afterhyperpolarizing potential following a train of action potentials is suppressed in an acute epilepsy model in the rat Cornu Ammonis 1 area.

PubMed

Kernig, K; Kirschstein, T; Würdemann, T; Rohde, M; Köhling, R

2012-01-10

In hippocampal Cornu Ammonis 1 (CA1) neurons, a prolonged depolarization evokes a train of action potentials followed by a prominent afterhyperpolarizing potential (AHP), which critically dampens neuronal excitability. Because it is not known whether epileptiform activity alters the AHP and whether any alteration of the AHP is independent of inhibition, we acutely induced epileptiform activity by bath application of the GABA(A) receptor blocker gabazine (5 μM) in the rat hippocampal slice preparation and studied its impact on the AHP using intracellular recordings. Following 10 min of gabazine wash-in, slices started to develop spontaneous epileptiform discharges. This disinhibition was accompanied by a significant shift of the resting membrane potential of CA1 neurons to more depolarized values. Prolonged depolarizations (600 ms) elicited a train of action potentials, the number of which was not different between baseline and gabazine treatment. However, the AHP following the train of action potentials was significantly reduced after 20 min of gabazine treatment. When the induction of epileptiform activity was prevented by co-application of 6-cyano-7-nitroquinoxaline-2,3-dione disodium (CNQX, 10 μM) and D-(-)-2-amino-5-phosphonopentanoic acid (D-AP5, 50 μM) to block α-amino-3-hydroxy-5-methylisoxazolepropionate (AMPA) and N-methyl-d-aspartate (NMDA) receptors, respectively, the AHP was preserved despite of GABA(A) receptor inhibition suggesting that the epileptiform activity was required to suppress the AHP. Moreover, the AHP was also preserved when the slices were treated with the protein kinase blockers H-9 (100 μM) and H-89 (1 μM). These results demonstrate that the AHP following a train of action potentials is rapidly suppressed by acutely induced epileptiform activity due to a phosphorylation process-presumably involving protein kinase A. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Development and validation of the short-form Adolescent Health Promotion Scale.

PubMed

Chen, Mei-Yen; Lai, Li-Ju; Chen, Hsiu-Chih; Gaete, Jorge

2014-10-26

Health-promoting lifestyle choices of adolescents are closely related to current and subsequent health status. However, parsimonious yet reliable and valid screening tools are scarce. The original 40-item adolescent health promotion (AHP) scale was developed by our research team and has been applied to measure adolescent health-promoting behaviors worldwide. The aim of our study was to examine the psychometric properties of a newly developed short-form version of the AHP (AHP-SF) including tests of its reliability and validity. The study was conducted in nine middle and high schools in southern Taiwan. Participants were 814 adolescents randomly divided into two subgroups with equal size and homogeneity of baseline characteristics. The first subsample (calibration sample) was used to modify and shorten the factorial model while the second subsample (validation sample) was utilized to validate the result obtained from the first one. The psychometric testing of the AHP-SF included internal reliability of McDonald's omega and Cronbach's alpha, convergent validity, discriminant validity, and construct validity with confirmatory factor analysis (CFA). The results of the CFA supported a six-factor model and 21 items were retained in the AHP-SF with acceptable model fit. For the discriminant validity test, results indicated that adolescents with lower AHP-SF scores were more likely to be overweight or obese, skip breakfast, and spend more time watching TV and playing computer games. The AHP-SF also showed excellent internal consistency with a McDonald's omega of 0.904 (Cronbach's alpha 0.905) in the calibration group. The current findings suggest that the AHP-SF is a valid and reliable instrument for the evaluation of adolescent health-promoting behaviors. Primary health care providers and clinicians can use the AHP-SF to assess these behaviors and evaluate the outcome of health promotion programs in the adolescent population.

Comparative Ploidy Proteomics of Candida albicans Biofilms Unraveled the Role of the AHP1 Gene in the Biofilm Persistence Against Amphotericin B.

PubMed

Truong, Thuyen; Zeng, Guisheng; Qingsong, Lin; Kwang, Lim Teck; Tong, Cao; Chan, Fong Yee; Wang, Yue; Seneviratne, Chaminda Jayampath

2016-11-01

Candida albicans is a major fungal pathogen causing lethal infections in immunocompromised patients. C. albicans forms antifungal tolerant biofilms contributing significantly to therapeutic failure. The recently established haploid C. albicans biofilm model provides a new toolbox to uncover the mechanism governing the higher antifungal tolerance of biofilms. Here, we comprehensively examined the proteomics and antifungal susceptibility of standard diploid (SC5314 and BWP17) and stable haploid (GZY792 and GZY803) strains of C. albicans biofilms. Subsequent downstream analyses identified alkyl hydroperoxide reductase 1 (AHP1) as a critical determinant of C. albicans biofilm's tolerance of amphotericin B. At 32 μg/ml of amphotericin B, GZY803 haploid biofilms showed 0.1% of persister population as compared with 1% of the diploid biofilms. AHP1 expression was found to be lower in GZY803 biofilms, and AHP1 overexpression in GZY803 restored the percentage of persister population. Consistently, deleting AHP1 in the diploid strain BWP17 caused a similar increase in amphotericin B susceptibility. AHP1 expression was also positively correlated with the antioxidant potential. Furthermore, C. albicans ira2Δ/Δ biofilms were susceptible to amphotericin B and had a diminished antioxidant capacity. Interestingly, AHP1 overexpression in the ira2Δ/Δ strain restored the antioxidant potential and enhanced the persister population against amphotericin B, and shutting down the AHP1 expression in ira2Δ/Δ biofilms reversed the effect. In conclusion, we provide evidence that the AHP1 gene critically determines the amphotericin B tolerance of C. albicans biofilms possibly by maintaining the persisters' antioxidant capacity. This finding will open up new avenues for developing therapies targeting the persister population of C. albicans biofilms. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD004274. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Construction of an evaluation and selection system of emergency treatment technology based on dynamic fuzzy GRA method for phenol spill

NASA Astrophysics Data System (ADS)

Zhao, Jingjing; Yu, Lean; Li, Lian

2017-05-01

There is often a great deal of complexity, fuzziness and uncertainties of the chemical contingency spills. In order to obtain the optimum emergency disposal technology schemes as soon as the chemical pollution accident occurs, the technique evaluation system was developed based on dynamic fuzzy GRA method, and the feasibility of the proposed methods has been tested by using a emergency phenol spill accidence occurred in highway.

A Comparison of Fuzzy Models in Similarity Assessment of Misregistered Area Class Maps

NASA Astrophysics Data System (ADS)

Brown, Scott

Spatial uncertainty refers to unknown error and vagueness in geographic data. It is relevant to land change and urban growth modelers, soil and biome scientists, geological surveyors and others, who must assess thematic maps for similarity, or categorical agreement. In this paper I build upon prior map comparison research, testing the effectiveness of similarity measures on misregistered data. Though several methods compare uncertain thematic maps, few methods have been tested on misregistration. My objective is to test five map comparison methods for sensitivity to misregistration, including sub-pixel errors in both position and rotation. Methods included four fuzzy categorical models: fuzzy kappa's model, fuzzy inference, cell aggregation, and the epsilon band. The fifth method used conventional crisp classification. I applied these methods to a case study map and simulated data in two sets: a test set with misregistration error, and a control set with equivalent uniform random error. For all five methods, I used raw accuracy or the kappa statistic to measure similarity. Rough-set epsilon bands report the most similarity increase in test maps relative to control data. Conversely, the fuzzy inference model reports a decrease in test map similarity.

Optimization Of Mean-Semivariance-Skewness Portfolio Selection Model In Fuzzy Random Environment

NASA Astrophysics Data System (ADS)

Chatterjee, Amitava; Bhattacharyya, Rupak; Mukherjee, Supratim; Kar, Samarjit

2010-10-01

The purpose of the paper is to construct a mean-semivariance-skewness portfolio selection model in fuzzy random environment. The objective is to maximize the skewness with predefined maximum risk tolerance and minimum expected return. Here the security returns in the objectives and constraints are assumed to be fuzzy random variables in nature and then the vagueness of the fuzzy random variables in the objectives and constraints are transformed into fuzzy variables which are similar to trapezoidal numbers. The newly formed fuzzy model is then converted into a deterministic optimization model. The feasibility and effectiveness of the proposed method is verified by numerical example extracted from Bombay Stock Exchange (BSE). The exact parameters of fuzzy membership function and probability density function are obtained through fuzzy random simulating the past dates.

A Z-number-based decision making procedure with ranking fuzzy numbers method

NASA Astrophysics Data System (ADS)

Mohamad, Daud; Shaharani, Saidatull Akma; Kamis, Nor Hanimah

2014-12-01

The theory of fuzzy set has been in the limelight of various applications in decision making problems due to its usefulness in portraying human perception and subjectivity. Generally, the evaluation in the decision making process is represented in the form of linguistic terms and the calculation is performed using fuzzy numbers. In 2011, Zadeh has extended this concept by presenting the idea of Z-number, a 2-tuple fuzzy numbers that describes the restriction and the reliability of the evaluation. The element of reliability in the evaluation is essential as it will affect the final result. Since this concept can still be considered as new, available methods that incorporate reliability for solving decision making problems is still scarce. In this paper, a decision making procedure based on Z-numbers is proposed. Due to the limitation of its basic properties, Z-numbers will be first transformed to fuzzy numbers for simpler calculations. A method of ranking fuzzy number is later used to prioritize the alternatives. A risk analysis problem is presented to illustrate the effectiveness of this proposed procedure.

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

PubMed

Deng, Xinyang; Jiang, Wen

2017-09-12

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method

PubMed Central

Deng, Xinyang

2017-01-01

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model. PMID:28895905

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

NASA Astrophysics Data System (ADS)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

AHP for Risk Management Based on Expected Utility Theory

NASA Astrophysics Data System (ADS)

Azuma, Rumiko; Miyagi, Hayao

This paper presents a model of decision-making considering the risk assessment. The conventional evaluation in AHP is considered to be a kind of utility. When dealing with the risk, however, it is necessary to consider the probability of damage. In order to take risk into decision-making problem, we construct AHP based on expected utility. The risk is considered as a related element of criterion rather than criterion itself. The expected utility is integrated, considering that satisfaction is positive utility and damage by risk is negative utility. Then, evaluation in AHP is executed using the expected utility.

Efficiency Improvement of Action Acquisition in Two-Link Robot Arm Using Fuzzy ART with Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kotani, Naoki; Taniguchi, Kenji

An efficient learning method using Fuzzy ART with Genetic Algorithm is proposed. The proposed method reduces the number of trials by using a policy acquired in other tasks because a reinforcement learning needs a lot of the number of trials until an agent acquires appropriate actions. Fuzzy ART is an incremental unsupervised learning algorithm in responce to arbitrary sequences of analog or binary input vectors. Our proposed method gives a policy by crossover or mutation when an agent observes unknown states. Selection controls the category proliferation problem of Fuzzy ART. The effectiveness of the proposed method was verified with the simulation of the reaching problem for the two-link robot arm. The proposed method achieves a reduction of both the number of trials and the number of states.

Systems of fuzzy equations in structural mechanics

NASA Astrophysics Data System (ADS)

Skalna, Iwona; Rama Rao, M. V.; Pownuk, Andrzej

2008-08-01

Systems of linear and nonlinear equations with fuzzy parameters are relevant to many practical problems arising in structure mechanics, electrical engineering, finance, economics and physics. In this paper three methods for solving such equations are discussed: method for outer interval solution of systems of linear equations depending linearly on interval parameters, fuzzy finite element method proposed by Rama Rao and sensitivity analysis method. The performance and advantages of presented methods are described with illustrative examples. Extended version of the present paper can be downloaded from the web page of the UTEP [I. Skalna, M.V. Rama Rao, A. Pownuk, Systems of fuzzy equations in structural mechanics, The University of Texas at El Paso, Department of Mathematical Sciences Research Reports Series, , Texas Research Report No. 2007-01, 2007].

Solving Fuzzy Fractional Differential Equations Using Zadeh's Extension Principle

PubMed Central

Ahmad, M. Z.; Hasan, M. K.; Abbasbandy, S.

2013-01-01

We study a fuzzy fractional differential equation (FFDE) and present its solution using Zadeh's extension principle. The proposed study extends the case of fuzzy differential equations of integer order. We also propose a numerical method to approximate the solution of FFDEs. To solve nonlinear problems, the proposed numerical method is then incorporated into an unconstrained optimisation technique. Several numerical examples are provided. PMID:24082853

Fuzzy Structures Analysis of Aircraft Panels in NASTRAN

NASA Technical Reports Server (NTRS)

Sparrow, Victor W.; Buehrle, Ralph D.

2001-01-01

This paper concerns an application of the fuzzy structures analysis (FSA) procedures of Soize to prototypical aerospace panels in MSC/NASTRAN, a large commercial finite element program. A brief introduction to the FSA procedures is first provided. The implementation of the FSA methods is then disclosed, and the method is validated by comparison to published results for the forced vibrations of a fuzzy beam. The results of the new implementation show excellent agreement to the benchmark results. The ongoing effort at NASA Langley and Penn State to apply these fuzzy structures analysis procedures to real aircraft panels is then described.

12 CFR 1291.2 - Required annual AHP contributions; allocation of contributions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Required annual AHP contributions; allocation of contributions. 1291.2 Section 1291.2 Banks and Banking FEDERAL HOUSING FINANCE AGENCY HOUSING GOALS AND MISSION FEDERAL HOME LOAN BANKS' AFFORDABLE HOUSING PROGRAM § 1291.2 Required annual AHP contributions; allocation of contributions. (a) Annual...

A New Fuzzy-Evidential Controller for Stabilization of the Planar Inverted Pendulum System

PubMed Central

Tang, Yongchuan; Zhou, Deyun

2016-01-01

In order to realize the stability control of the planar inverted pendulum system, which is a typical multi-variable and strong coupling system, a new fuzzy-evidential controller based on fuzzy inference and evidential reasoning is proposed. Firstly, for each axis, a fuzzy nine-point controller for the rod and a fuzzy nine-point controller for the cart are designed. Then, in order to coordinate these two controllers of each axis, a fuzzy-evidential coordinator is proposed. In this new fuzzy-evidential controller, the empirical knowledge for stabilization of the planar inverted pendulum system is expressed by fuzzy rules, while the coordinator of different control variables in each axis is built incorporated with the dynamic basic probability assignment (BPA) in the frame of fuzzy inference. The fuzzy-evidential coordinator makes the output of the control variable smoother, and the control effect of the new controller is better compared with some other work. The experiment in MATLAB shows the effectiveness and merit of the proposed method. PMID:27482707

A New Fuzzy-Evidential Controller for Stabilization of the Planar Inverted Pendulum System.

PubMed

Tang, Yongchuan; Zhou, Deyun; Jiang, Wen

2016-01-01

In order to realize the stability control of the planar inverted pendulum system, which is a typical multi-variable and strong coupling system, a new fuzzy-evidential controller based on fuzzy inference and evidential reasoning is proposed. Firstly, for each axis, a fuzzy nine-point controller for the rod and a fuzzy nine-point controller for the cart are designed. Then, in order to coordinate these two controllers of each axis, a fuzzy-evidential coordinator is proposed. In this new fuzzy-evidential controller, the empirical knowledge for stabilization of the planar inverted pendulum system is expressed by fuzzy rules, while the coordinator of different control variables in each axis is built incorporated with the dynamic basic probability assignment (BPA) in the frame of fuzzy inference. The fuzzy-evidential coordinator makes the output of the control variable smoother, and the control effect of the new controller is better compared with some other work. The experiment in MATLAB shows the effectiveness and merit of the proposed method.

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

PubMed

Kim, J; Kasabov, N

1999-11-01

This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.

Kv7/KCNQ/M and HCN/h, but not KCa2/SK channels, contribute to the somatic medium after-hyperpolarization and excitability control in CA1 hippocampal pyramidal cells

PubMed Central

Gu, Ning; Vervaeke, Koen; Hu, Hua; Storm, Johan F

2005-01-01

In hippocampal pyramidal cells, a single action potential (AP) or a burst of APs is followed by a medium afterhyperpolarization (mAHP, lasting ∼0.1 s). The currents underlying the mAHP are considered to regulate excitability and cause early spike frequency adaptation, thus dampening the response to sustained excitatory input relative to responses to abrupt excitation. The mAHP was originally suggested to be primarily caused by M-channels (at depolarized potentials) and h-channels (at more negative potentials), but not SK channels. In recent reports, however, the mAHP was suggested to be generated mainly by SK channels or only by h-channels. We have now re-examined the mechanisms underlying the mAHP and early spike frequency adaptation in CA1 pyramidal cells by using sharp electrode and whole-cell recording in rat hippocampal slices. The specific M-channel blocker XE991 (10 μm) suppressed the mAHP following 1–5 APs evoked by current injection at −60 mV. XE991 also enhanced the excitability of the cell, i.e. increased the number of APs evoked by a constant depolarizing current pulse, reduced their rate of adaptation, enhanced the afterdepolarization and promoted bursting. Conversely, the M-channel opener retigabine reduced excitability. The h-channel blocker ZD7288 (4-ethylphenylamino-1,2-dimethyl-6-methylaminopyrimidinium chloride; 10 μm) fully suppressed the mAHP at −80 mV, but had little effect at −60 mV, whereas XE991 did not measurably affect the mAHP at −80 mV. Likewise, ZD7288 had little or no effect on excitability or adaptation during current pulses injected from −60 mV, but changed the initial discharge during depolarizing pulses injected from −80 mV. In contrast to previous reports, we found that blockade of Ca2+-activated K+ channels of the SK/KCa type by apamin (100–400 nm) failed to affect the mAHP or adaptation. A computational model of a CA1 pyramidal cell predicted that M- and h-channels will generate mAHPs in a voltage-dependent manner, as indicated by the experiments. We conclude that M- and h-channels generate the somatic mAHP in hippocampal pyramidal cells, with little or no net contribution from SK channels. PMID:15890705

HbAHP-25, an In-Silico Designed Peptide, Inhibits HIV-1 Entry by Blocking gp120 Binding to CD4 Receptor.

PubMed

Bashir, Tahir; Patgaonkar, Mandar; Kumar, Selvaa C; Pasi, Achhelal; Reddy, Kudumula Venkata Rami

2015-01-01

Human Immunodeficiency Virus (HIV-1) poses a serious threat to the developing world and sexual transmission continues to be the major source of new infections. Therefore, the development of molecules, which prevent new HIV-1 infections, is highly warranted. In the present study, a panel of human hemoglobin (Hb)-α subunit derived peptides and their analogues, with an ability to bind gp120, were designed in-silico and their anti-HIV-1 activity was evaluated. Of these peptides, HbAHP-25, an analogue of Hb-α derived peptide, demonstrated significant anti-HIV-1 activity. HbAHP-25 was found to be active against CCR5-tropic HIV-1 strains (ADA5 and BaL) and CXCR4-tropic HIV-1 strains (IIIB and NL4-3). Surface plasmon resonance (SPR) and ELISA revealed direct interaction between HbAHP-25 and HIV-1 envelope protein, gp120. The peptide prevented binding of CD4 to gp120 and blocked subsequent steps leading to entry and/or fusion or both. Anti-HIV activity of HbAHP-25 appeared to be specific as it failed to inhibit the entry of HIV-1 pseudotyped virus (HIV-1 VSV). Further, HbAHP-25 was found to be non-cytotoxic to TZM-bl cells, VK2/E6E7 cells, CEM-GFP cells and PBMCs, even at higher concentrations. Moreover, HbAHP-25 retained its anti-HIV activity in presence of seminal plasma and vaginal fluid. In brief, the study identified HbAHP-25, a novel anti-HIV peptide, which directly interacts with gp120 and thus has a potential to inhibit early stages of HIV-1 infection.

HbAHP-25, an In-Silico Designed Peptide, Inhibits HIV-1 Entry by Blocking gp120 Binding to CD4 Receptor

PubMed Central

Bashir, Tahir; Patgaonkar, Mandar; Kumar C, Selvaa; Pasi, Achhelal; Reddy, Kudumula Venkata Rami

2015-01-01

Human Immunodeficiency Virus (HIV-1) poses a serious threat to the developing world and sexual transmission continues to be the major source of new infections. Therefore, the development of molecules, which prevent new HIV-1 infections, is highly warranted. In the present study, a panel of human hemoglobin (Hb)-α subunit derived peptides and their analogues, with an ability to bind gp120, were designed in-silico and their anti-HIV-1 activity was evaluated. Of these peptides, HbAHP-25, an analogue of Hb-α derived peptide, demonstrated significant anti-HIV-1 activity. HbAHP-25 was found to be active against CCR5-tropic HIV-1 strains (ADA5 and BaL) and CXCR4-tropic HIV-1 strains (IIIB and NL4-3). Surface plasmon resonance (SPR) and ELISA revealed direct interaction between HbAHP-25 and HIV-1 envelope protein, gp120. The peptide prevented binding of CD4 to gp120 and blocked subsequent steps leading to entry and/or fusion or both. Anti-HIV activity of HbAHP-25 appeared to be specific as it failed to inhibit the entry of HIV-1 pseudotyped virus (HIV-1 VSV). Further, HbAHP-25 was found to be non-cytotoxic to TZM-bl cells, VK2/E6E7 cells, CEM-GFP cells and PBMCs, even at higher concentrations. Moreover, HbAHP-25 retained its anti-HIV activity in presence of seminal plasma and vaginal fluid. In brief, the study identified HbAHP-25, a novel anti-HIV peptide, which directly interacts with gp120 and thus has a potential to inhibit early stages of HIV-1 infection. PMID:25915507

A mathematical programming method for formulating a fuzzy regression model based on distance criterion.

PubMed

Chen, Liang-Hsuan; Hsueh, Chan-Ching

2007-06-01

Fuzzy regression models are useful to investigate the relationship between explanatory and response variables with fuzzy observations. Different from previous studies, this correspondence proposes a mathematical programming method to construct a fuzzy regression model based on a distance criterion. The objective of the mathematical programming is to minimize the sum of distances between the estimated and observed responses on the X axis, such that the fuzzy regression model constructed has the minimal total estimation error in distance. Only several alpha-cuts of fuzzy observations are needed as inputs to the mathematical programming model; therefore, the applications are not restricted to triangular fuzzy numbers. Three examples, adopted in the previous studies, and a larger example, modified from the crisp case, are used to illustrate the performance of the proposed approach. The results indicate that the proposed model has better performance than those in the previous studies based on either distance criterion or Kim and Bishu's criterion. In addition, the efficiency and effectiveness for solving the larger example by the proposed model are also satisfactory.

Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations.

PubMed

Tang, Ming; Liao, Huchang; Li, Zongmin; Xu, Zeshui

2018-04-13

Because the natural disaster system is a very comprehensive and large system, the disaster reduction scheme must rely on risk analysis. Experts' knowledge and experiences play a critical role in disaster risk assessment. The hesitant fuzzy linguistic preference relation is an effective tool to express experts' preference information when comparing pairwise alternatives. Owing to the lack of knowledge or a heavy workload, information may be missed in the hesitant fuzzy linguistic preference relation. Thus, an incomplete hesitant fuzzy linguistic preference relation is constructed. In this paper, we firstly discuss some properties of the additive consistent hesitant fuzzy linguistic preference relation. Next, the incomplete hesitant fuzzy linguistic preference relation, the normalized hesitant fuzzy linguistic preference relation, and the acceptable hesitant fuzzy linguistic preference relation are defined. Afterwards, three procedures to estimate the missing information are proposed. The first one deals with the situation in which there are only n-1 known judgments involving all the alternatives; the second one is used to estimate the missing information of the hesitant fuzzy linguistic preference relation with more known judgments; while the third procedure is used to deal with ignorance situations in which there is at least one alternative with totally missing information. Furthermore, an algorithm for group decision making with incomplete hesitant fuzzy linguistic preference relations is given. Finally, we illustrate our model with a case study about flood disaster risk evaluation. A comparative analysis is presented to testify the advantage of our method.

Performance Optimization of Irreversible Air Heat Pumps Considering Size Effect

NASA Astrophysics Data System (ADS)

Bi, Yuehong; Chen, Lingen; Ding, Zemin; Sun, Fengrui

2018-06-01

Considering the size of an irreversible air heat pump (AHP), heating load density (HLD) is taken as thermodynamic optimization objective by using finite-time thermodynamics. Based on an irreversible AHP with infinite reservoir thermal-capacitance rate model, the expression of HLD of AHP is put forward. The HLD optimization processes are studied analytically and numerically, which consist of two aspects: (1) to choose pressure ratio; (2) to distribute heat-exchanger inventory. Heat reservoir temperatures, heat transfer performance of heat exchangers as well as irreversibility during compression and expansion processes are important factors influencing on the performance of an irreversible AHP, which are characterized with temperature ratio, heat exchanger inventory as well as isentropic efficiencies, respectively. Those impacts of parameters on the maximum HLD are thoroughly studied. The research results show that HLD optimization can make the size of the AHP system smaller and improve the compactness of system.

Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

PubMed

Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

2014-01-01

The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

Health state evaluation of shield tunnel SHM using fuzzy cluster method

NASA Astrophysics Data System (ADS)

Zhou, Fa; Zhang, Wei; Sun, Ke; Shi, Bin

2015-04-01

Shield tunnel SHM is in the path of rapid development currently while massive monitoring data processing and quantitative health grading remain a real challenge, since multiple sensors belonging to different types are employed in SHM system. This paper addressed the fuzzy cluster method based on fuzzy equivalence relationship for the health evaluation of shield tunnel SHM. The method was optimized by exporting the FSV map to automatically generate the threshold value. A new holistic health score(HHS) was proposed and its effectiveness was validated by conducting a pilot test. A case study on Nanjing Yangtze River Tunnel was presented to apply this method. Three types of indicators, namely soil pressure, pore pressure and steel strain, were used to develop the evaluation set U. The clustering results were verified by analyzing the engineering geological conditions; the applicability and validity of the proposed method was also demonstrated. Besides, the advantage of multi-factor evaluation over single-factor model was discussed by using the proposed HHS. This investigation indicated the fuzzy cluster method and HHS is capable of characterizing the fuzziness of tunnel health, and it is beneficial to clarify the tunnel health evaluation uncertainties.

Development of fuzzy multi-criteria approach to prioritize locations of treated wastewater use considering climate change scenarios.

PubMed

Chung, Eun-Sung; Kim, Yeonjoo

2014-12-15

This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fuzzy object models for newborn brain MR image segmentation

NASA Astrophysics Data System (ADS)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

A method and implementation for incorporating heuristic knowledge into a state estimator through the use of a fuzzy model

NASA Astrophysics Data System (ADS)

Swanson, Steven Roy

The objective of the dissertation is to improve state estimation performance, as compared to a Kalman filter, when non-constant, or changing, biases exist in the measurement data. The state estimation performance increase will come from the use of a fuzzy model to determine the position and velocity gains of a state estimator. A method is proposed for incorporating heuristic knowledge into a state estimator through the use of a fuzzy model. This method consists of using a fuzzy model to determine the gains of the state estimator, converting the heuristic knowledge into the fuzzy model, and then optimizing the fuzzy model with a genetic algorithm. This method is applied to the problem of state estimation of a cascaded global positioning system (GPS)/inertial reference unit (IRU) navigation system. The GPS position data contains two major sources for position bias. The first bias is due to satellite errors and the second is due to the time delay or lag from when the GPS position is calculated until it is used in the state estimator. When a change in the bias of the measurement data occurs, a state estimator will converge on the new measurement data solution. This will introduce errors into a Kalman filter's estimated state velocities, which in turn will cause a position overshoot as it converges. By using a fuzzy model to determine the gains of a state estimator, the velocity errors and their associated deficiencies can be reduced.

Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Cheng, Junsheng

2017-02-01

To timely detect the incipient failure of rolling bearing and find out the accurate fault location, a novel rolling bearing fault diagnosis method is proposed based on the composite multiscale fuzzy entropy (CMFE) and ensemble support vector machines (ESVMs). Fuzzy entropy (FuzzyEn), as an improvement of sample entropy (SampEn), is a new nonlinear method for measuring the complexity of time series. Since FuzzyEn (or SampEn) in single scale can not reflect the complexity effectively, multiscale fuzzy entropy (MFE) is developed by defining the FuzzyEns of coarse-grained time series, which represents the system dynamics in different scales. However, the MFE values will be affected by the data length, especially when the data are not long enough. By combining information of multiple coarse-grained time series in the same scale, the CMFE algorithm is proposed in this paper to enhance MFE, as well as FuzzyEn. Compared with MFE, with the increasing of scale factor, CMFE obtains much more stable and consistent values for a short-term time series. In this paper CMFE is employed to measure the complexity of vibration signals of rolling bearings and is applied to extract the nonlinear features hidden in the vibration signals. Also the physically meanings of CMFE being suitable for rolling bearing fault diagnosis are explored. Based on these, to fulfill an automatic fault diagnosis, the ensemble SVMs based multi-classifier is constructed for the intelligent classification of fault features. Finally, the proposed fault diagnosis method of rolling bearing is applied to experimental data analysis and the results indicate that the proposed method could effectively distinguish different fault categories and severities of rolling bearings.

Design of sewage treatment system by applying fuzzy adaptive PID controller

NASA Astrophysics Data System (ADS)

Jin, Liang-Ping; Li, Hong-Chan

2013-03-01

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

NASA Astrophysics Data System (ADS)

Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

Estimation of power lithium-ion battery SOC based on fuzzy optimal decision

NASA Astrophysics Data System (ADS)

He, Dongmei; Hou, Enguang; Qiao, Xin; Liu, Guangmin

2018-06-01

In order to improve vehicle performance and safety, need to accurately estimate the power lithium battery state of charge (SOC), analyzing the common SOC estimation methods, according to the characteristics open circuit voltage and Kalman filter algorithm, using T - S fuzzy model, established a lithium battery SOC estimation method based on the fuzzy optimal decision. Simulation results show that the battery model accuracy can be improved.

A prototype Knowledge-Based System to Aid Space System Restoration Management.

DTIC Science & Technology

1986-12-01

Systems. ......... 122 Appendix B: Computation of Weights With AHP . . .. 132 Appendix C: ART Code .. ............... 138 Appendix D: Test Outputs...45 5.1 Earth Coverage With Geosynchronous Satellites 49 5.2 Space System Configurations ... ........... . 50 5.3 AHP Hierarchy...67 5.4 AHP Hierarchy With Weights .... ............ 68 6.1 TALK Schema Structure ..... .............. 75 6.2 ART Code for TALK Satellite C

Responses to Gamma-Aminobutyric Acid of Rat Visual Cortical Neurons in Tissue Slices

DTIC Science & Technology

1986-04-01

depolarizing afterpotentials ( DAPs ; Figure 3). The afterhyperpolarization (AHP) was defined as the hyperpolarization that follow one or more orthodromic...action potentials or action potentials elicited during a depolarizing current pulse (Figure 3). DAPs and AHPs were measured from the RMP. The term...inhibitory postsynaptic potential, DAP = depolarizing afterpotential, AHP= afterhyperpolarization. Dashed lines indicate the RMP. Asterisks indicate

The Salmonella typhimurium AhpC Polypeptide Is Not Essential for Virulence in BALB/c Mice but Is Recognized as an Antigen during Infection

PubMed Central

Taylor, Patrick D.; Inchley, Christopher J.; Gallagher, Maurice P.

1998-01-01

The OxyR regulon is known to mediate protection against oxidizing agents in Salmonella typhimurium. We reported previously that ahp, one of the OxyR-regulated loci, is induced during macrophage interaction (K. P. Francis, P. D. Taylor, C. J. Inchley, and M. P. Gallagher, J. Bacteriol. 179:4046–4048, 1997). We now report on the effects of disrupting ahp or oxyR on virulence in a BALB/c mouse model. Surprisingly, insertion of a Mudlux derivative within ahpC was found to result in attenuation, while irreversible inactivation of the locus through insertion of a cml cassette did not. An SL1344 derivative carrying an oxyR::kan disruption was also found to be as virulent as the parental strain. Moreover, both cell-mediated and humoral responses to AhpC were found to develop during the course of infection, probably through T-helper-cell (type I) activation. These results indicate that, although not essential for virulence, AhpC is expressed by S. typhimurium during infection of BALB/c mice and constitutes a target for the immune system. PMID:9632587

Musculoskeletal pain symptoms among allied health professions' students: Prevalence rates and associated factors.

PubMed

Almhdawi, Khader A; Mathiowetz, Virgil; Al-Hourani, Zeid; Khader, Yousef; Kanaan, Saddam F; Alhasan, Mustafa

2017-11-06

Very few articles, comprehensively, investigated musculoskeletal pain symptoms (MPS) among wide variety of allied health professions (AHP) students. This study aimed to investigate the prevalence of MPS and their associated factors among different AHP majors' students. A cross-sectional design was conducted. A sample of AHP students from nine majors (n= 838, Mean age = 21.3 years) completed a validated structured self-administrated questionnaires including Nordic Musculoskeletal Questionnaire, Depression Anxiety Stress Scale (DASS 21), and specific questions regarding demographics and life style. MPS prevalence rate were compared between males and females and between majors. Logistic regression was conducted to identify predictors of MPS. MPS in neck, lower back, and shoulder 12-month were the most prevalent (67.1%, and 61.4%, 58.8% respectively). MPS prevalence was significantly higher in females and statistically different among majors. MPS were significantly associated with increased clinical training load, mental stress symptoms, and smartphone average use time. MPS in AHP students are prevalent and statistically higher among females. Students are advised to adhere to different conservative precautions and follow prevention programs. Future studies are needed to assess actual mechanisms causing MPS among AHP students and designing effective prevention programs specific to AHP students.

Enhanced enzymatic hydrolysis and ethanol production from cashew apple bagasse pretreated with alkaline hydrogen peroxide.

PubMed

da Costa, Jessyca Aline; Marques, José Edvan; Gonçalves, Luciana Rocha Barros; Rocha, Maria Valderez Ponte

2015-03-01

The effect of combinations and ratios between different enzymes has been investigated in order to assess the optimal conditions for hydrolysis of cashew apple bagasse pretreated with alkaline hydrogen peroxide (the solids named CAB-AHP). The separate hydrolysis and fermentation (SHF) and simultaneous saccharification and fermentation (SSF) processes were evaluated in the ethanol production. The enzymatic hydrolysis conducted with cellulase complex and β-glucosidase in a ratio of 0.61:0.39, enzyme loading of 30FPU/g(CAB-AHP) and 66CBU/g(CAB-AHP), respectively, using 4% cellulose from CAB-AHP, turned out to be the most effective conditions, with glucose and xylose yields of 511.68 mg/g(CAB-AHP) and 237.8 mg/g(CAB-AHP), respectively. Fermentation of the pure hydrolysate by Kluyveromyces marxianus ATCC 36907 led to an ethanol yield of 61.8kg/ton(CAB), corresponding to 15 g/L ethanol and productivity of 3.75 g/( Lh). The ethanol production obtained for SSF process using K. marxianus ATCC 36907 was 18 g/L corresponding to 80% yield and 74.2kg/ton(CAB). Copyright © 2014 Elsevier Ltd. All rights reserved.

Cutting Force Predication Based on Integration of Symmetric Fuzzy Number and Finite Element Method

PubMed Central

Wang, Zhanli; Hu, Yanjuan; Wang, Yao; Dong, Chao; Pang, Zaixiang

2014-01-01

In the process of turning, pointing at the uncertain phenomenon of cutting which is caused by the disturbance of random factors, for determining the uncertain scope of cutting force, the integrated symmetric fuzzy number and the finite element method (FEM) are used in the prediction of cutting force. The method used symmetric fuzzy number to establish fuzzy function between cutting force and three factors and obtained the uncertain interval of cutting force by linear programming. At the same time, the change curve of cutting force with time was directly simulated by using thermal-mechanical coupling FEM; also the nonuniform stress field and temperature distribution of workpiece, tool, and chip under the action of thermal-mechanical coupling were simulated. The experimental result shows that the method is effective for the uncertain prediction of cutting force. PMID:24790556

A role for TREK1 in generating the slow afterhyperpolarization in developing starburst amacrine cells.

PubMed

Ford, Kevin J; Arroyo, David A; Kay, Jeremy N; Lloyd, Eric E; Bryan, Robert M; Sanes, Joshua R; Feller, Marla B

2013-05-01

Slow afterhyperpolarizations (sAHPs) play an important role in establishing the firing pattern of neurons that in turn influence network activity. sAHPs are mediated by calcium-activated potassium channels. However, the molecular identity of these channels and the mechanism linking calcium entry to their activation are still unknown. Here we present several lines of evidence suggesting that the sAHPs in developing starburst amacrine cells (SACs) are mediated by two-pore potassium channels. First, we use whole cell and perforated patch voltage clamp recordings to characterize the sAHP conductance under different pharmacological conditions. We find that this conductance was calcium dependent, reversed at EK, blocked by barium, insensitive to apamin and TEA, and activated by arachidonic acid. In addition, pharmacological inhibition of calcium-activated phosphodiesterase reduced the sAHP. Second, we performed gene profiling on isolated SACs and found that they showed strong preferential expression of the two-pore channel gene kcnk2 that encodes TREK1. Third, we demonstrated that TREK1 knockout animals exhibited an altered frequency of retinal waves, a frequency that is set by the sAHPs in SACs. With these results, we propose a model in which depolarization-induced decreases in cAMP lead to disinhibition of the two-pore potassium channels and in which the kinetics of this biochemical pathway dictate the slow activation and deactivation of the sAHP conductance. Our model offers a novel pathway for the activation of a conductance that is physiologically important.

QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm.

PubMed

Bao, Ying; Lei, Weimin; Zhang, Wei; Zhan, Yuzhuo

2016-01-01

At present, to realize or improve the quality of experience (QoE) is a major goal for network media transmission service, and QoE evaluation is the basis for adjusting the transmission control mechanism. Therefore, a kind of QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm is proposed in this paper, which is concentrated on service score calculation at the server side. The server side collects network transmission quality of service (QoS) parameter, node location data, and user expectation value from client feedback information. Then it manages the historical data in database through the "big data" process mode, and predicts user score according to heuristic rules. On this basis, it completes fuzzy clustering analysis, and generates service QoE score and management message, which will be finally fed back to clients. Besides, this paper mainly discussed service evaluation generative rules, heuristic evaluation rules and fuzzy clustering analysis methods, and presents service-based QoE evaluation processes. The simulation experiments have verified the effectiveness of QoE collaborative evaluation method based on fuzzy clustering heuristic rules.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

PubMed Central

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Determination System Of Food Vouchers For the Poor Based On Fuzzy C-Means Method

NASA Astrophysics Data System (ADS)

Anamisa, D. R.; Yusuf, M.; Syakur, M. A.

2018-01-01

Food vouchers are government programs to tackle the poverty of rural communities. This program aims to help the poor group in getting enough food and nutrients from carbohydrates. There are several factors that influence to receive the food voucher, such as: job, monthly income, Taxes, electricity bill, size of house, number of family member, education certificate and amount of rice consumption every week. In the execution for the distribution of vouchers is often a lot of problems, such as: the distribution of food vouchers has been misdirected and someone who receives is still subjective. Some of the solutions to decision making have not been done. The research aims to calculating the change of each partition matrix and each cluster using Fuzzy C-Means method. Hopefully this research makes contribution by providing higher result using Fuzzy C-Means comparing to other method for this case study. In this research, decision making is done by using Fuzzy C-Means method. The Fuzzy C-Means method is a clustering method that has an organized and scattered cluster structure with regular patterns on two-dimensional datasets. Furthermore, Fuzzy C-Means method used for calculates the change of each partition matrix. Each cluster will be sorted by the proximity of the data element to the centroid of the cluster to get the ranking. Various trials were conducted for grouping and ranking of proposed data that received food vouchers based on the quota of each village. This testing by Fuzzy C-Means method, is developed and abled for determining the recipient of the food voucher with satisfaction results. Fulfillment of the recipient of the food voucher is 80% to 90% and this testing using data of 115 Family Card from 6 Villages. The quality of success affected, has been using the number of iteration factors is 20 and the number of clusters is 3

a New Model for Fuzzy Personalized Route Planning Using Fuzzy Linguistic Preference Relation

NASA Astrophysics Data System (ADS)

Nadi, S.; Houshyaripour, A. H.

2017-09-01

This paper proposes a new model for personalized route planning under uncertain condition. Personalized routing, involves different sources of uncertainty. These uncertainties can be raised from user's ambiguity about their preferences, imprecise criteria values and modelling process. The proposed model uses Fuzzy Linguistic Preference Relation Analytical Hierarchical Process (FLPRAHP) to analyse user's preferences under uncertainty. Routing is a multi-criteria task especially in transportation networks, where the users wish to optimize their routes based on different criteria. However, due to the lake of knowledge about the preferences of different users and uncertainties available in the criteria values, we propose a new personalized fuzzy routing method based on the fuzzy ranking using center of gravity. The model employed FLPRAHP method to aggregate uncertain criteria values regarding uncertain user's preferences while improve consistency with least possible comparisons. An illustrative example presents the effectiveness and capability of the proposed model to calculate best personalize route under fuzziness and uncertainty.

Evaluation about the Performance of E-Government Based on Interval-Valued Intuitionistic Fuzzy Set

PubMed Central

Zhang, Shuai; Wang, Yan

2014-01-01

The evaluation is an important approach to promote the development of the E-Government. Since the rapid development of E-Government in the world, the E-Government performance evaluation has become a hot issue in the academia. In this paper, we develop a new evaluation method for the development of the E-Government based on the interval-valued intuitionistic fuzzy set which is a powerful technique in expressing the uncertainty of the real situation. First, we extend the geometric Heronian mean (GHM) operator to interval-valued intuitionistic fuzzy environment and proposed the interval-valued intuitionistic fuzzy GHM (IIFGHM) operator. Then, we investigate the relationships between the IIFGHM operator and some existing ones, such as generalized interval-valued intuitionistic fuzzy HM (GIIFHM) and interval-valued intuitionistic fuzzy weighted Bonferoni mean operator. Furthermore, we validate the effectiveness of the proposed method using a real case about the E-Government evaluation in Hangzhou City, China. PMID:24707196

The weakest t-norm based intuitionistic fuzzy fault-tree analysis to evaluate system reliability.

PubMed

Kumar, Mohit; Yadav, Shiv Prasad

2012-07-01

In this paper, a new approach of intuitionistic fuzzy fault-tree analysis is proposed to evaluate system reliability and to find the most critical system component that affects the system reliability. Here weakest t-norm based intuitionistic fuzzy fault tree analysis is presented to calculate fault interval of system components from integrating expert's knowledge and experience in terms of providing the possibility of failure of bottom events. It applies fault-tree analysis, α-cut of intuitionistic fuzzy set and T(ω) (the weakest t-norm) based arithmetic operations on triangular intuitionistic fuzzy sets to obtain fault interval and reliability interval of the system. This paper also modifies Tanaka et al.'s fuzzy fault-tree definition. In numerical verification, a malfunction of weapon system "automatic gun" is presented as a numerical example. The result of the proposed method is compared with the listing approaches of reliability analysis methods. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Fuzzy MCDM Technique for Planning the Environment Watershed

NASA Astrophysics Data System (ADS)

Chen, Yi-Chun; Lien, Hui-Pang; Tzeng, Gwo-Hshiung; Yang, Lung-Shih; Yen, Leon

In the real word, the decision making problems are very vague and uncertain in a number of ways. The most criteria have interdependent and interactive features so they cannot be evaluated by conventional measures method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environmentwatershed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception. A questionnaire was used to find out from three related groups comprising fifteen experts. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. Incorporated the decision makers’ attitude towards preference, overall performance value of each alternative can be obtained based on the concept of Fuzzy Multiple Criteria Decision Making (FMCDM). This research also gives an example of evaluating consisting of five alternatives, solicited from a environmentwatershed plan works in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach.

Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

PubMed

Wang, B H; Lim, J W; Lim, J S

2016-08-30

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

Learning and tuning fuzzy logic controllers through reinforcements

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1992-01-01

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

NASA Astrophysics Data System (ADS)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

Site selection for managed aquifer recharge using fuzzy rules: integrating geographical information system (GIS) tools and multi-criteria decision making

NASA Astrophysics Data System (ADS)

Malekmohammadi, Bahram; Ramezani Mehrian, Majid; Jafari, Hamid Reza

2012-11-01

One of the most important water-resources management strategies for arid lands is managed aquifer recharge (MAR). In establishing a MAR scheme, site selection is the prime prerequisite that can be assisted by geographic information system (GIS) tools. One of the most important uncertainties in the site-selection process using GIS is finite ranges or intervals resulting from data classification. In order to reduce these uncertainties, a novel method has been developed involving the integration of multi-criteria decision making (MCDM), GIS, and a fuzzy inference system (FIS). The Shemil-Ashkara plain in the Hormozgan Province of Iran was selected as the case study; slope, geology, groundwater depth, potential for runoff, land use, and groundwater electrical conductivity have been considered as site-selection factors. By defining fuzzy membership functions for the input layers and the output layer, and by constructing fuzzy rules, a FIS has been developed. Comparison of the results produced by the proposed method and the traditional simple additive weighted (SAW) method shows that the proposed method yields more precise results. In conclusion, fuzzy-set theory can be an effective method to overcome associated uncertainties in classification of geographic information data.

Factors affecting retention of allied health professionals working with people with disability in rural New South Wales, Australia: discrete choice experiment questionnaire development.

PubMed

Gallego, Gisselle; Dew, Angela; Bulkeley, Kim; Veitch, Craig; Lincoln, Michelle; Bundy, Anita; Brentnall, Jennie

2015-04-21

This paper describes the development of a discrete choice experiment (DCE) questionnaire to identify the factors (attributes) that allied health professionals (AHPs) working with people with disability identify as important to encouraging them to remain practising in rural areas. Focus groups and semi-structured interviews were conducted with 97 purposively selected service providers working with people with disability in rural New South Wales, Australia. Focus groups and interviews were digitally recorded, transcribed, and analysed using a modified grounded theory approach involving thematic analysis and constant comparison. Six attributes that may influence AHPs working with people with disability in rural areas to continue to do so were inductively identified: travel arrangements, work flexibility, professional support, professional development, remuneration, and autonomy of practice. The qualitative research information was combined with a policy review to define these retention factors and ensure that they are amenable to policy changes. The use of various qualitative research methods allowed the development of a policy-relevant DCE questionnaire that was grounded in the experience of the target population (AHPs).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Szoka de Valladares, M.R.; Mack, S.

The DOE Hydrogen Program needs to develop criteria as part of a systematic evaluation process for proposal identification, evaluation and selection. The H Scan component of this process provides a framework in which a project proposer can fully describe their candidate technology system and its components. The H Scan complements traditional methods of capturing cost and technical information. It consists of a special set of survey forms designed to elicit information so expert reviewers can assess the proposal relative to DOE specified selection criteria. The Analytic Hierarchy Process (AHP) component of the decision process assembles the management defined evaluation andmore » selection criteria into a coherent multi-level decision construct by which projects can be evaluated in pair-wise comparisons. The AHP model will reflect management`s objectives and it will assist in the ranking of individual projects based on the extent to which each contributes to management`s objectives. This paper contains a detailed description of the products and activities associated with the planning and evaluation process: The objectives or criteria; the H Scan; and The Analytic Hierarchy Process (AHP).« less

Fuzzy rule-based image segmentation in dynamic MR images of the liver

NASA Astrophysics Data System (ADS)

Kobashi, Syoji; Hata, Yutaka; Tokimoto, Yasuhiro; Ishikawa, Makato

2000-06-01

This paper presents a fuzzy rule-based region growing method for segmenting two-dimensional (2-D) and three-dimensional (3- D) magnetic resonance (MR) images. The method is an extension of the conventional region growing method. The proposed method evaluates the growing criteria by using fuzzy inference techniques. The use of the fuzzy if-then rules is appropriate for describing the knowledge of the legions on the MR images. To evaluate the performance of the proposed method, it was applied to artificially generated images. In comparison with the conventional method, the proposed method shows high robustness for noisy images. The method then applied for segmenting the dynamic MR images of the liver. The dynamic MR imaging has been used for diagnosis of hepatocellular carcinoma (HCC), portal hypertension, and so on. Segmenting the liver, portal vein (PV), and inferior vena cava (IVC) can give useful description for the diagnosis, and is a basis work of a pres-surgery planning system and a virtual endoscope. To apply the proposed method, fuzzy if-then rules are derived from the time-density curve of ROIs. In the experimental results, the 2-D reconstructed and 3-D rendered images of the segmented liver, PV, and IVC are shown. The evaluation by a physician shows that the generated images are comparable to the hepatic anatomy, and they would be useful to understanding, diagnosis, and pre-surgery planning.

What role can the rural pipeline play in the recruitment and retention of rural allied health professionals?

PubMed

Durey, Angela; Haigh, Margaret; Katzenellenbogen, Judith M

2015-01-01

People living in rural areas have poorer health than their urban counterparts with higher morbidity and mortality rates and lower life expectancy. Challenges attracting health professionals to work in rural locations in Australia and elsewhere have been well- documented. In response, the idea of a rural pipeline emerged in the medical literature as a career pathway for doctors, conceptualised as a career continuum starting at school and ending in a committed, appropriately trained and supported rural doctor. This article draws on the literature to consider how the concept of a rural pipeline can be used to enhance recruitment and retention of allied health professionals (AHPs) in Australia. The complexity of the issue is taken into account, acknowledging the diverse professional, organisational and social needs within and between AHPs and their different career pathways. With this in mind, the rural pipeline is adapted and extended to focus on AHPs who enter at any stage of their career to work in rural areas. Barriers to recruitment and retention require multifaceted strategies to encourage and support AHPs at various stages along the pipeline to enter, and remain in, rural practice. Findings from the literature identify discrete themes within and between AHPs about factors influencing their rural recruitment and retention choices and include career stage at entry to rural practice, age, gender, social context, professional support, organisational environment and public-private practice mix in service delivery. These findings underscored the development of an extended rural pipeline adapted to specifically target AHPs. This flexible framework of entry to rural practice can be applied at any stage of their career and includes suggestions of strategies to support retention. Evidence from studies of rural AHPs suggests a flexible approach to recruitment and retention is needed that takes into account the complexity of the issue. The extended rural pipeline adapted to AHPs avoids a one-size-fits-all approach. Instead, it offers a more nuanced approach that addresses the diversity within and between professions and reflects the different stages at which AHPs enter rural practice that can inform recruitment and retention strategies that better meet their needs.

Fuzzy logic-based flight control system design

NASA Astrophysics Data System (ADS)

Nho, Kyungmoon

The application of fuzzy logic to aircraft motion control is studied in this dissertation. The self-tuning fuzzy techniques are developed by changing input scaling factors to obtain a robust fuzzy controller over a wide range of operating conditions and nonlinearities for a nonlinear aircraft model. It is demonstrated that the properly adjusted input scaling factors can meet the required performance and robustness in a fuzzy controller. For a simple demonstration of the easy design and control capability of a fuzzy controller, a proportional-derivative (PD) fuzzy control system is compared to the conventional controller for a simple dynamical system. This thesis also describes the design principles and stability analysis of fuzzy control systems by considering the key features of a fuzzy control system including the fuzzification, rule-base and defuzzification. The wing-rock motion of slender delta wings, a linear aircraft model and the six degree of freedom nonlinear aircraft dynamics are considered to illustrate several self-tuning methods employing change in input scaling factors. Finally, this dissertation is concluded with numerical simulation of glide-slope capture in windshear demonstrating the robustness of the fuzzy logic based flight control system.

Competitive Facility Location with Fuzzy Random Demands

NASA Astrophysics Data System (ADS)

Uno, Takeshi; Katagiri, Hideki; Kato, Kosuke

2010-10-01

This paper proposes a new location problem of competitive facilities, e.g. shops, with uncertainty and vagueness including demands for the facilities in a plane. By representing the demands for facilities as fuzzy random variables, the location problem can be formulated as a fuzzy random programming problem. For solving the fuzzy random programming problem, first the α-level sets for fuzzy numbers are used for transforming it to a stochastic programming problem, and secondly, by using their expectations and variances, it can be reformulated to a deterministic programming problem. After showing that one of their optimal solutions can be found by solving 0-1 programming problems, their solution method is proposed by improving the tabu search algorithm with strategic oscillation. The efficiency of the proposed method is shown by applying it to numerical examples of the facility location problems.

Modelling of the automatic stabilization system of the aircraft course by a fuzzy logic method

NASA Astrophysics Data System (ADS)

Mamonova, T.; Syryamkin, V.; Vasilyeva, T.

2016-04-01

The problem of the present paper concerns the development of a fuzzy model of the system of an aircraft course stabilization. In this work modelling of the aircraft course stabilization system with the application of fuzzy logic is specified. Thus the authors have used the data taken for an ordinary passenger plane. As a result of the study the stabilization system models were realised in the environment of Matlab package Simulink on the basis of the PID-regulator and fuzzy logic. The authors of the paper have shown that the use of the method of artificial intelligence allows reducing the time of regulation to 1, which is 50 times faster than the time when standard receptions of the management theory are used. This fact demonstrates a positive influence of the use of fuzzy regulation.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Evaluation of infectious diseases and clinical microbiology specialists' preferences for hand hygiene: analysis using the multi-attribute utility theory and the analytic hierarchy process methods.

PubMed

Suner, Aslı; Oruc, Ozlem Ege; Buke, Cagri; Ozkaya, Hacer Deniz; Kitapcioglu, Gul

2017-08-31

Hand hygiene is one of the most effective attempts to control nosocomial infections, and it is an important measure to avoid the transmission of pathogens. However, the compliance of healthcare workers (HCWs) with hand washing is still poor worldwide. Herein, we aimed to determine the best hand hygiene preference of the infectious diseases and clinical microbiology (IDCM) specialists to prevent transmission of microorganisms from one patient to another. Expert opinions regarding the criteria that influence the best hand hygiene preference were collected through a questionnaire via face-to-face interviews. Afterwards, these opinions were examined with two widely used multi-criteria decision analysis (MCDA) methods, the Multi-Attribute Utility Theory (MAUT) and the Analytic Hierarchy Process (AHP). A total of 15 IDCM specialist opinions were collected from diverse private and public hospitals located in İzmir, Turkey. The mean age of the participants was 49.73 ± 8.46, and the mean experience year of the participants in their fields was 17.67 ± 11.98. The findings that we obtained through two distinct decision making methods, the MAUT and the AHP, suggest that alcohol-based antiseptic solution (ABAS) has the highest utility (0.86) and priority (0.69) among the experts' choices. In conclusion, the MAUT and the AHP, decision models developed here indicate that rubbing the hands with ABAS is the most favorable choice for IDCM specialists to prevent nosocomial infection.

An efficient computer based wavelets approximation method to solve Fuzzy boundary value differential equations

NASA Astrophysics Data System (ADS)

Alam Khan, Najeeb; Razzaq, Oyoon Abdul

2016-03-01

In the present work a wavelets approximation method is employed to solve fuzzy boundary value differential equations (FBVDEs). Essentially, a truncated Legendre wavelets series together with the Legendre wavelets operational matrix of derivative are utilized to convert FB- VDE into a simple computational problem by reducing it into a system of fuzzy algebraic linear equations. The capability of scheme is investigated on second order FB- VDE considered under generalized H-differentiability. Solutions are represented graphically showing competency and accuracy of this method.

Study on evaluation of construction reliability for engineering project based on fuzzy language operator

NASA Astrophysics Data System (ADS)

Shi, Yu-Fang; Ma, Yi-Yi; Song, Ping-Ping

2018-03-01

System Reliability Theory is a research hotspot of management science and system engineering in recent years, and construction reliability is useful for quantitative evaluation of project management level. According to reliability theory and target system of engineering project management, the defination of construction reliability appears. Based on fuzzy mathematics theory and language operator, value space of construction reliability is divided into seven fuzzy subsets and correspondingly, seven membership function and fuzzy evaluation intervals are got with the operation of language operator, which provides the basis of corresponding method and parameter for the evaluation of construction reliability. This method is proved to be scientific and reasonable for construction condition and an useful attempt for theory and method research of engineering project system reliability.

Research on water shortage risks and countermeasures in North China

NASA Astrophysics Data System (ADS)

Cheng, Yuxiang; Fang, Wenxuan; Wu, Ziqin

2017-05-01

In the paper, a grey forecasting model and a population growth model are established for forecasting water resources supply and demand situation in the region, and evaluating the scarcity of water resources thereof in order to solve the problem of water shortage in North China. A concrete plan for alleviating water resources pressure is proposed with AHP as basis, thereby discussing the feasibility of the plan. Firstly, water resources supply and demand in the future 15 years are predicted. There are four sources for the demand of water resources mainly: industry, agriculture, ecology and resident living. Main supply sources include surface water and underground water resources. A grey forecasting method is adopted for predicting in the paper aiming at water resources demands since industrial, agricultural and ecological water consumption data have excessive decision factors and the correlation is relatively fuzzy. Since residents' water consumption is determined by per capita water consumption and local population, a logistic growth model is adopted to forecast the population. The grey forecasting method is used for predicting per capita water consumption, and total water demand can be obtained finally. International calculation standards are adopted as reference aiming at water supply. The grey forecasting method is adopted for forecasting surface water quantity and underground water quantity, and water resources supply is obtained finally. Per capita water availability in the region is calculated by comparing the water resources supply and demand. Results show that per capita water availability in the region is only 283 cubic meters this year, people live in serious water shortage region, who will suffer from water shortage state for long time. Then, sensitivity analysis is applied for model test. The test result is excellent, and the prediction results are more accurate. In the paper, the following measures are proposed for improving water resources condition in the region according to prediction results, such as construction of reservoirs, sewage treatment, water diversion project and other measures. A detailed water supply plan is formulated. Water supply weights of all measures are determined according to the AHP model. Solution is sought after original models are improved. Results show that water resources quantity per capita will be up to 2170 cubic meters or so this year, people suffer from moderate water shortage in the region, which can meet people's life needs and economic development needs basically. In addition, water resources quantity per capita is increased year by year, and it can reach mild water shortage level after 2030. In a word, local water resources dilemma can be effectively solved by the plan actually, and thoughts can be provided for decision makers.

Fuzzy difference-of-Gaussian-based iris recognition method for noisy iris images

NASA Astrophysics Data System (ADS)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Moon, Kiyoung

2010-06-01

Iris recognition is used for information security with a high confidence level because it shows outstanding recognition accuracy by using human iris patterns with high degrees of freedom. However, iris recognition accuracy can be reduced by noisy iris images with optical and motion blurring. We propose a new iris recognition method based on the fuzzy difference-of-Gaussian (DOG) for noisy iris images. This study is novel in three ways compared to previous works: (1) The proposed method extracts iris feature values using the DOG method, which is robust to local variations of illumination and shows fine texture information, including various frequency components. (2) When determining iris binary codes, image noises that cause the quantization error of the feature values are reduced with the fuzzy membership function. (3) The optimal parameters of the DOG filter and the fuzzy membership function are determined in terms of iris recognition accuracy. Experimental results showed that the performance of the proposed method was better than that of previous methods for noisy iris images.

An approach to solve replacement problems under intuitionistic fuzzy nature

NASA Astrophysics Data System (ADS)

Balaganesan, M.; Ganesan, K.

2018-04-01

Due to impreciseness to solve the day to day problems the researchers use fuzzy sets in their discussions of the replacement problems. The aim of this paper is to solve the replacement theory problems with triangular intuitionistic fuzzy numbers. An effective methodology based on fuzziness index and location index is proposed to determine the optimal solution of the replacement problem. A numerical example is illustrated to validate the proposed method.

Neuro-fuzzy controller to navigate an unmanned vehicle.

PubMed

Selma, Boumediene; Chouraqui, Samira

2013-12-01

A Neuro-fuzzy control method for an Unmanned Vehicle (UV) simulation is described. The objective is guiding an autonomous vehicle to a desired destination along a desired path in an environment characterized by a terrain and a set of distinct objects, such as obstacles like donkey traffic lights and cars circulating in the trajectory. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Fuzzy Logic Controller can very well describe the desired system behavior with simple "if-then" relations owing the designer to derive "if-then" rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). In this paper, an artificial neural network fuzzy inference system (ANFIS) controller is described and implemented to navigate the autonomous vehicle. Results show several improvements in the control system adjusted by neuro-fuzzy techniques in comparison to the previous methods like Artificial Neural Network (ANN).

Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

NASA Astrophysics Data System (ADS)

Sdao, F.; Lioi, D. S.; Pascale, S.; Caniani, D.; Mancini, I. M.

2013-02-01

The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the determination of the landslide susceptibility map.

Epistemic uncertainty propagation in energy flows between structural vibrating systems

NASA Astrophysics Data System (ADS)

Xu, Menghui; Du, Xiaoping; Qiu, Zhiping; Wang, Chong

2016-03-01

A dimension-wise method for predicting fuzzy energy flows between structural vibrating systems coupled by joints with epistemic uncertainties is established. Based on its Legendre polynomial approximation at α=0, both the minimum and maximum point vectors of the energy flow of interest are calculated dimension by dimension within the space spanned by the interval parameters determined by fuzzy those at α=0 and the resulted interval bounds are used to assemble the concerned fuzzy energy flows. Besides the proposed method, vertex method as well as two current methods is also applied. Comparisons among results by different methods are accomplished by two numerical examples and the accuracy of all methods is simultaneously verified by Monte Carlo simulation.

Fuzzy Set Methods for Object Recognition in Space Applications

NASA Technical Reports Server (NTRS)

Keller, James M. (Editor)

1992-01-01

Progress on the following four tasks is described: (1) fuzzy set based decision methodologies; (2) membership calculation; (3) clustering methods (including derivation of pose estimation parameters), and (4) acquisition of images and testing of algorithms.

Definition of zones with different levels of productivity within an agricultural field using fuzzy modeling

USDA-ARS?s Scientific Manuscript database

Zoning of agricultural fields is an important task for utilization of precision farming technology. One method for the definition of zones with different levels of productivity is based on fuzzy indicator model. Fuzzy indicator model for identification of zones with different levels of productivit...

Hesitant triangular fuzzy information aggregation operators based on Bonferroni means and their application to multiple attribute decision making.

PubMed

Wang, Chunyong; Li, Qingguo; Zhou, Xiaoqiang; Yang, Tian

2014-01-01

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

Fuzzy model-based fault detection and diagnosis for a pilot heat exchanger

NASA Astrophysics Data System (ADS)

Habbi, Hacene; Kidouche, Madjid; Kinnaert, Michel; Zelmat, Mimoun

2011-04-01

This article addresses the design and real-time implementation of a fuzzy model-based fault detection and diagnosis (FDD) system for a pilot co-current heat exchanger. The design method is based on a three-step procedure which involves the identification of data-driven fuzzy rule-based models, the design of a fuzzy residual generator and the evaluation of the residuals for fault diagnosis using statistical tests. The fuzzy FDD mechanism has been implemented and validated on the real co-current heat exchanger, and has been proven to be efficient in detecting and isolating process, sensor and actuator faults.

Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making

PubMed Central

Zhou, Xiaoqiang; Yang, Tian

2014-01-01

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness. PMID:25140338

Refining fuzzy logic controllers with machine learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1994-01-01

In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.

Evaluation of Goal Programming for the Optimal Assignment of Inspectors to Construction Projects

DTIC Science & Technology

1988-09-01

Inputs ..... .............. 90 Equation Coefficients . ....... .. 90 Weights, Priorities and the AHP . . 91 Right-Hand Side Values ........ .. 91...the AHP Hierarchy with k Levels . . 36 3. Sample Matrix for Pairwise Comparison ........ .. 37 4. Assignment of I and p for Example Problem...Weights for Example Problem ... 61 3. AHP Weights and Coefficient ci, Values. ........ 63 vii AFIT/GEM/LSM/88S-16 Abstract The purpose of this study was

Targeted delivery using peptide-functionalised gold nanoparticles to white adipose tissues of obese rats

NASA Astrophysics Data System (ADS)

Thovhogi, Ntevheleni; Sibuyi, Nicole; Meyer, Mervin; Onani, Martin; Madiehe, Abram

2015-02-01

Obesity is a complex metabolic disease of excessive fat accumulation. It is a worldwide epidemic affecting billions of people. Current pharmacological treatment of obesity remains limited and ineffective due to systemic drug toxicity and undesirable side effects. The current epidemic raises a serious need for development of safer drugs to treat obesity. Nanotechnology-based drug delivery system for administering pharmaceutical compound to achieve therapeutic effects is currently an exciting field in cancer treatment. Drug delivery involves either modification of drug release profile, absorption, distribution and/or elimination, for the benefit of improving drug efficacy and safety. Therefore, nanotechnology holds promise in the treatment of diseases including obesity. Gold nanoparticles (GNPs) functionalised with different biomolecules have been successfully used as drug delivery, labelling and imaging tools in biomedical research. In this study, the binding-specificity and targeting ability of adipose homing peptide (AHP)-functionalised GNPs (AHP-GNPs) were evaluated using flow cytometry and inductively coupled plasma-optical emission spectroscopy. Caco-2 cells and rats fed either chow or a high-fat diet were treated with either unfunctionalised GNPs or AHP-GNPs. Cellular uptake of GNPs was detected in cells treated with AHP-GNPs and not those treated with GNPs alone. Binding of AHP to cells was both temperature- and concentration-dependent. Compared to rats treated with GNPs alone, treatment of obese rats with AHP-GNPs resulted in the targeted delivery of the GNPs to the white adipose tissue (WAT). This paper reports the successful targeting of AHP-functionalised GNPs to WAT of obese rats.

Healthcare students' perceptions about their role, confidence and competence to deliver brief public health interventions and advice.

PubMed

McLean, Sionnadh; Charlesworth, Laura; May, Stephen; Pollard, Nick

2018-05-24

Public health improvement has long been an important focus for the United Kingdom Department of Health. The Allied Health Professions (AHP) Federation has 84,000 members, such a large number of AHP professionals should play a role in public health initiatives, but it is not clear if they or the AHP students who will be the future healthcare workforce feel themselves equipped to do so. Our aim was to understand the perceptions of AHP students about their role in delivering public health advice. AHP students were recruited in one teaching university from different departments. Participants were final year AHP students who had completed all clinical placements related to their course. All students were emailed an invitation to participate, and those interested were asked to contact the researchers to participate in one of several focus groups. Data were recorded, transcribed, and analysed using framework analysis by two independent researchers. Nineteen students were recruited and participated in four focus groups. The main themes produced by the data analysis were: understanding of public health issues, perceptions of their role in this, challenges and opportunities to develop a public health role, and preparation for a public health role. AHP students felt that they had a role in public health advice-giving, but barriers to providing this advice included their own lack of confidence and knowledge, time, and the environment of the clinical placement. They considered that there should be more teaching on public health issues, and that these should feature in both the curriculum and on clinical placement.

Risk analysis with a fuzzy-logic approach of a complex installation

NASA Astrophysics Data System (ADS)

Peikert, Tim; Garbe, Heyno; Potthast, Stefan

2016-09-01

This paper introduces a procedural method based on fuzzy logic to analyze systematic the risk of an electronic system in an intentional electromagnetic environment (IEME). The method analyzes the susceptibility of a complex electronic installation with respect to intentional electromagnetic interference (IEMI). It combines the advantages of well-known techniques as fault tree analysis (FTA), electromagnetic topology (EMT) and Bayesian networks (BN) and extends the techniques with an approach to handle uncertainty. This approach uses fuzzy sets, membership functions and fuzzy logic to handle the uncertainty with probability functions and linguistic terms. The linguistic terms add to the risk analysis the knowledge from experts of the investigated system or environment.

Using an innovative criteria weighting tool for stakeholders involvement to rank MSW facility sites with the AHP.

PubMed

De Feo, Giovanni; De Gisi, Sabino

2010-11-01

The main aim of this study was to verify the efficacy of using an innovative criteria weighting tool (the "priority scale") for stakeholders involvement to rank a list of suitable municipal solid waste (MSW) facility sites with the multi-criteria decision-making (MCDM) technique known as analytic hierarchy process (AHP). One of the main objectives of the study was to verify the behaviour of the "priority scale" with both technical and non-technical decision-makers. All over the world, the siting of MSW treatment or disposal plants is a complex process involving politicians, technicians as well as citizens, where stakeholders who are not effectively involved strongly oppose (or even obstruct) the realization of new facilities. In this study, in order to pursue both the technical (select the best site) and social aims (all the stakeholders have to give their aware contribution), the use of the "priority scale" is suggested as a tool to easily collect non-contradictory criteria preferences by the various decision-makers. Every decision-maker filled in "priority scale", which was subsequently uploaded in the AHP tool in order to indirectly calculate the individual priority of alternatives given by each stakeholder (not using group aggregation techniques). The proposed method was applied to the siting of a composting plant in an area suffering from a serious MSW emergency, which has lasted for over 15 years, in the Campania Region, in Southern Italy. The best site (the "first choice") was taken as the one that appeared the most times at the first place of each decision-maker ranking list. The involved technical and non-technical decision-makers showed the same behaviour in (indirectly) selecting the best site as well as in terms of the most appraised criteria ("absence of areas of the highest value for natural habitats and species of plants and animals"). Moreover, they showed the same AHP inconsistency ratio as well as the same behaviour in comparison with a "balanced decision-maker" (who assigns identical weights to all the considered criteria). Therefore, the proposed criteria weighting tool could be widely as well as easily used for stakeholders involvement to rank MSW facility sites (or other kinds of alternatives) with the AHP or with other MCDM techniques, taking or not into consideration group aggregation methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Study on application of adaptive fuzzy control and neural network in the automatic leveling system

NASA Astrophysics Data System (ADS)

Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

2015-04-01

This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

Fuzzy-probabilistic model for risk assessment of radioactive material railway transportation.

PubMed

Avramenko, M; Bolyatko, V; Kosterev, V

2005-01-01

Transportation of radioactive materials is obviously accompanied by a certain risk. A model for risk assessment of emergency situations and terrorist attacks may be useful for choosing possible routes and for comparing the various defence strategies. In particular, risk assessment is crucial for safe transportation of excess weapons-grade plutonium arising from the removal of plutonium from military employment. A fuzzy-probabilistic model for risk assessment of railway transportation has been developed taking into account the different natures of risk-affecting parameters (probabilistic and not probabilistic but fuzzy). Fuzzy set theory methods as well as standard methods of probability theory have been used for quantitative risk assessment. Information-preserving transformations are applied to realise the correct aggregation of probabilistic and fuzzy parameters. Estimations have also been made of the inhalation doses resulting from possible accidents during plutonium transportation. The obtained data show the scale of possible consequences that may arise from plutonium transportation accidents.

Cost-Sharing of Ecological Construction Based on Trapezoidal Intuitionistic Fuzzy Cooperative Games.

PubMed

Liu, Jiacai; Zhao, Wenjian

2016-11-08

There exist some fuzziness and uncertainty in the process of ecological construction. The aim of this paper is to develop a direct and an effective simplified method for obtaining the cost-sharing scheme when some interested parties form a cooperative coalition to improve the ecological environment of Min River together. Firstly, we propose the solution concept of the least square prenucleolus of cooperative games with coalition values expressed by trapezoidal intuitionistic fuzzy numbers. Then, based on the square of the distance in the numerical value between two trapezoidal intuitionistic fuzzy numbers, we establish a corresponding quadratic programming model to obtain the least square prenucleolus, which can effectively avoid the information distortion and uncertainty enlargement brought about by the subtraction of trapezoidal intuitionistic fuzzy numbers. Finally, we give a numerical example about the cost-sharing of ecological construction in Fujian Province in China to show the validity, applicability, and advantages of the proposed model and method.

Development and Validation of Questionnaires Exploring Health Care Professionals' Intention to Use Wiki-Based Reminders to Promote Best Practices in Trauma

PubMed Central

Gagnon, Susie; Gagnon, Marie-Pierre; Turcotte, Stéphane; Lapointe, Jean; Fleet, Richard; Côté, Mario; Beaupré, Pierre; Le Sage, Natalie; Émond, Marcel; Légaré, France

2014-01-01

Background Little is known about factors influencing professionals’ use of wikis. Objective We developed and validated two questionnaires to assess health care professionals’ intention to use wiki-based reminders for the management of trauma patients. Methods We developed questionnaires for emergency physicians (EPs) and allied health professions (AHPs) based on the Theory of Planned Behavior and adapted them to the salient beliefs of each, identified in an earlier study. Items measured demographics and direct and indirect theoretical constructs. We piloted the questionnaires with 2 focus groups (5 EPs and 5 AHPs) to identify problems of wording and length. Based on feedback, we adjusted the wording and combined certain items. A new convenience sample of 25 EPs and 26 AHPs then performed a test-retest of the questionnaires at a 2-week interval. We assessed internal consistency using Cronbach alpha coefficients and temporal stability of items with an agreement intraclass correlation coefficient (ICC). Results Five EPs and 5 AHPs (3 nurses, 1 respiratory therapist, and 1 pharmacist) formed 2 focus groups; 25 EPs and 26 AHPs (12 nurses, 7 respiratory therapists, and 7 pharmacists) completed the test and retest. The EP questionnaire test-retest scores for consistency (Cronbach alpha) and stability (ICC) were intention (test: Cronbach alpha=.94; retest: Cronbach alpha=.98; ICC=.89), attitude (.74, .72, .70), subjective norm (.79, .78, .75), perceived behavioral control (.67, .65, .66), attitudinal beliefs (.94, .86, .60), normative beliefs (.83, .87, .79), and control beliefs barriers (.58, .67, .78) and facilitators (.97, .85, .30). The AHP questionnaire scores for consistency and stability were: intention (test Cronbach alpha=.69, retest Cronbach alpha=.81, ICC=.48), attitude (.85, .87, .83), subjective norm (.47, .82, .62), perceived behavioral control (.55, .62, .60), attitudinal beliefs (.92, .91, .82), normative beliefs (.85, .90, .74), and control beliefs barriers (.58, .55, .66) and facilitators (.72, .94, –.05). To improve the psychometric properties of both questionnaires, we reformulated poorly consistent or unstable items. Conclusions Our new theory-based questionnaires to measure health care professionals’ intention to use wiki-based reminders have adequate validity and reliability for use in large surveys. In the long run, they can be used to develop a theory-based implementation intervention for a wiki promoting best practices in trauma care. PMID:25281856

Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

PubMed

Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

2017-04-01

We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its capability to capture the nonlinearities of the model better. Copyright © 2017 Elsevier B.V. All rights reserved.

Fuzzy physical programming for Space Manoeuvre Vehicles trajectory optimization based on hp-adaptive pseudospectral method

NASA Astrophysics Data System (ADS)

Chai, Runqi; Savvaris, Al; Tsourdos, Antonios

2016-06-01

In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

NASA Astrophysics Data System (ADS)

Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

2017-08-01

Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

Hesitant fuzzy linguistic multicriteria decision-making method based on generalized prioritized aggregation operator.

PubMed

Wu, Jia-ting; Wang, Jian-qiang; Wang, Jing; Zhang, Hong-yu; Chen, Xiao-hong

2014-01-01

Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

Method study on fuzzy-PID adaptive control of electric-hydraulic hitch system

NASA Astrophysics Data System (ADS)

Li, Mingsheng; Wang, Liubu; Liu, Jian; Ye, Jin

2017-03-01

In this paper, fuzzy-PID adaptive control method is applied to the control of tractor electric-hydraulic hitch system. According to the characteristics of the system, a fuzzy-PID adaptive controller is designed and the electric-hydraulic hitch system model is established. Traction control and position control performance simulation are carried out with the common PID control method. A field test rig was set up to test the electric-hydraulic hitch system. The test results showed that, after the fuzzy-PID adaptive control is adopted, when the tillage depth steps from 0.1m to 0.3m, the system transition process time is 4s, without overshoot, and when the tractive force steps from 3000N to 7000N, the system transition process time is 5s, the system overshoot is 25%.

High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

2008-02-01

Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

A Different Web-Based Geocoding Service Using Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Pahlavani, P.; Abbaspour, R. A.; Zare Zadiny, A.

2015-12-01

Geocoding - the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.

A Comparison of the Analytic Hierarchy Process and the Geometric Mean Procedure for Ratio Scaling

DTIC Science & Technology

1987-12-01

hierarchy process ( AHP ) has attracted much attention, having been successfully applied in such diverse areas as marketing (Wind & Saaty, 1980...political science (Saaty & Bennett, 1977), and the measurement of subjective probabilities (Yager, 1979). However, the AHP has had its share of criticism...of Williams and Crawford, shows the percentage of cases (matrices) in which the GM procedure outperformed the AHP . A In the "almost consistent case

The Gap in Operation and Maintenance of the Afghan National Security Forces Infrastructure

DTIC Science & Technology

2013-05-22

organizations. They include the Afghan Border Police ( ABP ), the Afghan Uniform Police (AUP), the Afghan Highway Police (AHP), and the Criminal...other elements under the ANP include the Afghan Border Police ( ABP ), the Afghan Uniformed Police (AUP), the Afghan Highway Police (AHP) and the...delineates the authorized personnel and equipment for the army. The ANP tashkil delineates the authorized personnel and equipment for the AUP, ABP , AHP, and

Decomposition of Fuzzy Soft Sets with Finite Value Spaces

PubMed Central

Jun, Young Bae

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter. PMID:24558342

Decomposition of fuzzy soft sets with finite value spaces.

PubMed

Feng, Feng; Fujita, Hamido; Jun, Young Bae; Khan, Madad

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter.

Programmable fuzzy associative memory processor

NASA Astrophysics Data System (ADS)

Shao, Lan; Liu, Liren; Li, Guoqiang

1996-02-01

An optical system based on the method of spatial area-coding and multiple image scheme is proposed for fuzzy associative memory processing. Fuzzy maximum operation is accomplished by a ferroelectric liquid crystal PROM instead of a computer-based approach. A relative subsethood is introduced here to be used as a criterion for the recall evaluation.

Application of Fuzzy Reasoning for Filtering and Enhancement of Ultrasonic Images

NASA Technical Reports Server (NTRS)

Sacha, J. P.; Cios, K. J.; Roth, D. J.; Berke, L.; Vary, A.

1994-01-01

This paper presents a new type of an adaptive fuzzy operator for detection of isolated abnormalities, and enhancement of raw ultrasonic images. Fuzzy sets used in decision rules are defined for each image based on empirical statistics of the color intensities. Examples of the method are also presented in the paper.