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Sample records for fuzzy delphi method

  1. Pesticide applicators questionnaire content validation: A fuzzy delphi method.

    PubMed

    Manakandan, S K; Rosnah, I; Mohd Ridhuan, J; Priya, R

    2017-08-01

    The most crucial step in forming a set of survey questionnaire is deciding the appropriate items in a construct. Retaining irrelevant items and removing important items will certainly mislead the direction of a particular study. This article demonstrates Fuzzy Delphi method as one of the scientific analysis technique to consolidate consensus agreement within a panel of experts pertaining to each item's appropriateness. This method reduces the ambiguity, diversity, and discrepancy of the opinions among the experts hence enhances the quality of the selected items. The main purpose of this study was to obtain experts' consensus on the suitability of the preselected items on the questionnaire. The panel consists of sixteen experts from the Occupational and Environmental Health Unit of Ministry of Health, Vector-borne Disease Control Unit of Ministry of Health and Occupational and Safety Health Unit of both public and private universities. A set of questionnaires related to noise and chemical exposure were compiled based on the literature search. There was a total of six constructs with 60 items in which three constructs for knowledge, attitude, and practice of noise exposure and three constructs for knowledge, attitude, and practice of chemical exposure. The validation process replicated recent Fuzzy Delphi method that using a concept of Triangular Fuzzy Numbers and Defuzzification process. A 100% response rate was obtained from all the sixteen experts with an average Likert scoring of four to five. Post FDM analysis, the first prerequisite was fulfilled with a threshold value (d) ≤ 0.2, hence all the six constructs were accepted. For the second prerequisite, three items (21%) from noise-attitude construct and four items (40%) from chemical-practice construct had expert consensus lesser than 75%, which giving rise to about 12% from the total items in the questionnaire. The third prerequisite was used to rank the items within the constructs by calculating the average

  2. Determining e-Portfolio Elements in Learning Process Using Fuzzy Delphi Analysis

    ERIC Educational Resources Information Center

    Mohamad, Syamsul Nor Azlan; Embi, Mohamad Amin; Nordin, Norazah

    2015-01-01

    The present article introduces the Fuzzy Delphi method results obtained in the study on determining e-Portfolio elements in learning process for art and design context. This method bases on qualified experts that assure the validity of the collected information. In particular, the confirmation of elements is based on experts' opinion and…

  3. Application of Fuzzy Delphi in the Selection of COPD Risk Factors among Steel Industry Workers

    PubMed Central

    Ismail, Halim; Ismail, Rosnah; Ismail, Noor Hassim

    2017-01-01

    Background: The Delphi method has been widely applied in many study areas to systematically gather experts’ input on particular topic. Recently, it has become increasingly well known in health related research. This paper applied the Fuzzy Delphi method to enhance the validation of a questionnaire pertaining chronic obstructive pulmonary disease (COPD) risk factors among metal industry workers. Materials and Methods: A detailed, predefined list of possible risk factors for COPD among metal industry workers was created through a comprehensive and exhaustive review of literature from 1995 to 2015. The COPD questionnaire were distributed among people identified as occupational, environmental, and hygiene experts. Linguistic variable using Likert scale was used by the expert to indicate their expert judgment of each item. Subsequently, the linguistic variable was converted into a triangular fuzzy number. The average score of the fuzzy number will be used to determine whether the item will be removed or retained. Results: Ten experts were involved in evaluating 26 items. The experts were in agreement with most of the items, with an average fuzzy number range between 0.429 and 0.800. Two items were removed and three items were added, leaving a total 26 items selected for the COPD risk factors questionnaire. The experts were in disagreement with each other for items F10 and F11 where most of the experts claimed that the question is too subjective and based on self-perception only. Conclusion: The fuzzy Delphi method enhanced the accuracy of the questionnaire pertaining to COPD risk factors, and decreased the length of the established tools. PMID:28638424

  4. Application of Fuzzy Delphi in the Selection of COPD Risk Factors among Steel Industry Workers.

    PubMed

    Dapari, Rahmat; Ismail, Halim; Ismail, Rosnah; Ismail, Noor Hassim

    2017-01-01

    The Delphi method has been widely applied in many study areas to systematically gather experts' input on particular topic. Recently, it has become increasingly well known in health related research. This paper applied the Fuzzy Delphi method to enhance the validation of a questionnaire pertaining chronic obstructive pulmonary disease (COPD) risk factors among metal industry workers. A detailed, predefined list of possible risk factors for COPD among metal industry workers was created through a comprehensive and exhaustive review of literature from 1995 to 2015. The COPD questionnaire were distributed among people identified as occupational, environmental, and hygiene experts. Linguistic variable using Likert scale was used by the expert to indicate their expert judgment of each item. Subsequently, the linguistic variable was converted into a triangular fuzzy number. The average score of the fuzzy number will be used to determine whether the item will be removed or retained. Ten experts were involved in evaluating 26 items. The experts were in agreement with most of the items, with an average fuzzy number range between 0.429 and 0.800. Two items were removed and three items were added, leaving a total 26 items selected for the COPD risk factors questionnaire. The experts were in disagreement with each other for items F10 and F11 where most of the experts claimed that the question is too subjective and based on self-perception only. The fuzzy Delphi method enhanced the accuracy of the questionnaire pertaining to COPD risk factors, and decreased the length of the established tools.

  5. 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

  6. 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.

  7. Identifying Mental Health Elements among Technical University Students Using Fuzzy Delphi Method

    NASA Astrophysics Data System (ADS)

    Pua, P. K.; Lai, C. S.; Lee, M. F.

    2017-08-01

    Mental health is a part of our daily life that is often experienced. As a student, mental health issue often encounters a variety of difficult challenges at the higher education institution. A student with good mental health can handle and cope the normal stress of life, capable work productivity, enhance academic performance and able to make contribute to the community. However, rapidly transformation and changing of society have been impacted on students’ mental health, and it will be deteriorated and negatively impact on students if it absence of preventive controlled. This study aimed to identify the element of mental health among the technical university students. A total of 11 experts were selected to analyze the fuzziness consensus of experts. All collected data was analyzed by using the fuzzy Delphi method and the result shows that there are 4 elements of 8 elements that fulfill the requirement consensus of experts, which threshold value is equal and less than 0.2, the percentage of the expert group is more than 75%. The four elements were depression, anxiety, stress, and fear are often experienced by technical university students. In conclusion, precocious actions have to be taken by university and counseling center, parents and non-government organization in order to mitigate the mental health problem faced by students to improve the quality lifestyle students at the university.

  8. Project evaluation and selection using fuzzy Delphi method and zero - one goal programming

    NASA Astrophysics Data System (ADS)

    Alias, Suriana; Adna, Nofarziah; Arsad, Roslah; Soid, Siti Khuzaimah; Ali, Zaileha Md

    2014-12-01

    Project evaluation and selection is a factor affecting the impotence of board director in which is trying to maximize all the possible goals. Assessment of the problem occurred in organization plan is the first phase for decision making process. The company needs a group of expert to evaluate the problems. The Fuzzy Delphi Method (FDM) is a systematic procedure to evoke the group's opinion in order to get the best result to evaluate the project performance. This paper proposes an evaluation and selection of the best alternative project based on combination of FDM and Zero - One Goal Programming (ZOGP) formulation. ZOGP is used to solve the multi-criteria decision making for final decision part by using optimization software LINDO 6.1. An empirical example on an ongoing decision making project in Johor, Malaysia is implemented for case study.

  9. The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection

    NASA Astrophysics Data System (ADS)

    Tahriri, Farzad; Mousavi, Maryam; Hozhabri Haghighi, Siamak; Zawiah Md Dawal, Siti

    2014-06-01

    In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers' ranking. This is a complex process with many subjective and objective factors to consider before the benefits of supplier selection are achieved. This paper identifies six extremely critical criteria and thirteen sub-criteria based on the literature. A new methodology employing those criteria and sub-criteria is proposed for the assessment and ranking of a given set of suppliers. To handle the subjectivity of the decision maker's assessment, an integration of fuzzy Delphi with fuzzy inference system has been applied and a new ranking method is proposed for supplier selection problem. This supplier selection model enables decision makers to rank the suppliers based on three classifications including "extremely preferred", "moderately preferred", and "weakly preferred". In addition, in each classification, suppliers are put in order from highest final score to the lowest. Finally, the methodology is verified and validated through an example of a numerical test bed.

  10. 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.

  11. Identifying the critical financial ratios for stocks evaluation: A fuzzy delphi approach

    NASA Astrophysics Data System (ADS)

    Mokhtar, Mazura; Shuib, Adibah; Mohamad, Daud

    2014-12-01

    Stocks evaluation has always been an interesting and challenging problem for both researchers and practitioners. Generally, the evaluation can be made based on a set of financial ratios. Nevertheless, there are a variety of financial ratios that can be considered and if all ratios in the set are placed into the evaluation process, data collection would be more difficult and time consuming. Thus, the objective of this paper is to identify the most important financial ratios upon which to focus in order to evaluate the stock's performance. For this purpose, a survey was carried out using an approach which is based on an expert judgement, namely the Fuzzy Delphi Method (FDM). The results of this study indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share and debt to equity are the most important ratios.

  12. The Delphi Method for Graduate Research

    ERIC Educational Resources Information Center

    Skulmoski, Gregory J.; Hartman, Francis T.; Krahn, Jennifer

    2007-01-01

    The Delphi method is an attractive method for graduate students completing masters and PhD level research. It is a flexible research technique that has been successfully used in our program at the University of Calgary to explore new concepts within and outside of the information systems body of knowledge. The Delphi method is an iterative process…

  13. A Multi-level Fuzzy Evaluation Method for Smart Distribution Network Based on Entropy Weight

    NASA Astrophysics Data System (ADS)

    Li, Jianfang; Song, Xiaohui; Gao, Fei; Zhang, Yu

    2017-05-01

    Smart distribution network is considered as the future trend of distribution network. In order to comprehensive evaluate smart distribution construction level and give guidance to the practice of smart distribution construction, a multi-level fuzzy evaluation method based on entropy weight is proposed. Firstly, focus on both the conventional characteristics of distribution network and new characteristics of smart distribution network such as self-healing and interaction, a multi-level evaluation index system which contains power supply capability, power quality, economy, reliability and interaction is established. Then, a combination weighting method based on Delphi method and entropy weight method is put forward, which take into account not only the importance of the evaluation index in the experts’ subjective view, but also the objective and different information from the index values. Thirdly, a multi-level evaluation method based on fuzzy theory is put forward. Lastly, an example is conducted based on the statistical data of some cites’ distribution network and the evaluation method is proved effective and rational.

  14. The Delphi Method Online: Medical Expert Consensus Via the Internet

    PubMed Central

    Cam, Kenneth M.; McKnight, Patrick E.; Doctor, Jason N.

    2002-01-01

    Delphi is an expert consensus method. The theory behind the Delphi method is that the interaction of experts may lead to a reduction in individual bias. We have developed software that carries out all aspects of the Delphi method via the Internet. The Delphi method online consists of three components: 1) authorship, 2) interactive polling, and 3) reporting/results. We hope that researchers use this tool in future medical expert systems.

  15. [Application of Delphi method in traditional Chinese medicine clinical research].

    PubMed

    Bi, Ying-fei; Mao, Jing-yuan

    2012-03-01

    In recent years, Delphi method has been widely applied in traditional Chinese medicine (TCM) clinical research. This article analyzed the present application situation of Delphi method in TCM clinical research, and discussed some problems presented in the choice of evaluation method, classification of observation indexes and selection of survey items. On the basis of present application of Delphi method, the author analyzed the method on questionnaire making, selection of experts, evaluation of observation indexes and selection of survey items. Furthermore, the author summarized the steps of application of Delphi method in TCM clinical research.

  16. Intuitionistic fuzzy analytical hierarchical processes for selecting the paradigms of mangroves in municipal wastewater treatment.

    PubMed

    Ouyang, Xiaoguang; Guo, Fen

    2018-04-01

    Municipal wastewater discharge is widespread and one of the sources of coastal eutrophication, and is especially uncontrolled in developing and undeveloped coastal regions. Mangrove forests are natural filters of pollutants in wastewater. There are three paradigms of mangroves for municipal wastewater treatment and the selection of the optimal one is a multi-criteria decision-making problem. Combining intuitionistic fuzzy theory, the Fuzzy Delphi Method and the fuzzy analytical hierarchical process (AHP), this study develops an intuitionistic fuzzy AHP (IFAHP) method. For the Fuzzy Delphi Method, the judgments of experts and representatives on criterion weights are made by linguistic variables and quantified by intuitionistic fuzzy theory, which is also used to weight the importance of experts and representatives. This process generates the entropy weights of criteria, which are combined with indices values and weights to rank the alternatives by the fuzzy AHP method. The IFAHP method was used to select the optimal paradigm of mangroves for treating municipal wastewater. The entropy weights were entrained by the valid evaluation of 64 experts and representatives via online survey. Natural mangroves were found to be the optimal paradigm for municipal wastewater treatment. By assigning different weights to the criteria, sensitivity analysis shows that natural mangroves remain to be the optimal paradigm under most scenarios. This study stresses the importance of mangroves for wastewater treatment. Decision-makers need to contemplate mangrove reforestation projects, especially where mangroves are highly deforested but wastewater discharge is uncontrolled. The IFAHP method is expected to be applied in other multi-criteria decision-making cases. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. 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)

  18. Using the Delphi expert consensus method in mental health research.

    PubMed

    Jorm, Anthony F

    2015-10-01

    The article gives an introductory overview of the use of the Delphi expert consensus method in mental health research. It explains the rationale for using the method, examines the range of uses to which it has been put in mental health research, and describes the stages of carrying out a Delphi study using examples from the literature. To ascertain the range of uses, a systematic search was carried out in PubMed. The article also examines the implications of 'wisdom of crowds' research for how to conduct Delphi studies. The Delphi method is a systematic way of determining expert consensus that is useful for answering questions that are not amenable to experimental and epidemiological methods. The validity of the approach is supported by 'wisdom of crowds' research showing that groups can make good judgements under certain conditions. In mental health research, the Delphi method has been used for making estimations where there is incomplete evidence (e.g. What is the global prevalence of dementia?), making predictions (e.g. What types of interactions with a person who is suicidal will reduce their chance of suicide?), determining collective values (e.g. What areas of research should be given greatest priority?) and defining foundational concepts (e.g. How should we define 'relapse'?). A range of experts have been used in Delphi research, including clinicians, researchers, consumers and caregivers. The Delphi method has a wide range of potential uses in mental health research. © The Royal Australian and New Zealand College of Psychiatrists 2015.

  19. 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.

  20. 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.

  1. Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

    PubMed

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

    2016-01-01

    Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. [Modified Delphi method in the constitution of school sanitation standard].

    PubMed

    Yin, Xunqiang; Liang, Ying; Tan, Hongzhuan; Gong, Wenjie; Deng, Jing; Luo, Jiayou; Di, Xiaokang; Wu, Yue

    2012-11-01

    To constitute school sanitation standard using modified Delphi method, and to explore the feasibility and the predominance of Delphi method in the constitution of school sanitation standard. Two rounds of expert consultations were adopted in this study. The data were analyzed with SPSS15.0 to screen indices of school sanitation standard. Thirty-two experts accomplished the 2 rounds of consultations. The average length of expert service was (24.69 ±8.53) years. The authority coefficient was 0.729 ±0.172. The expert positive coefficient was 94.12% (32/34) in the first round and 100% (32/32) in the second round. The harmonious coefficients of importance, feasibility and rationality in the second round were 0.493 (P<0.05), 0.527 (P<0.01), and 0.535 (P<0.01), respectively, suggesting unanimous expert opinions. According to the second round of consultation, 38 indices were included in the framework. Theoretical analysis, literature review, investigation and so on are generally used in health standard constitution currently. Delphi method is a rapid, effective and feasible method in this field.

  8. Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

    NASA Astrophysics Data System (ADS)

    Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

    2017-09-01

    Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.

  9. Using and Reporting the Delphi Method for Selecting Healthcare Quality Indicators: A Systematic Review

    PubMed Central

    Boulkedid, Rym; Abdoul, Hendy; Loustau, Marine; Sibony, Olivier; Alberti, Corinne

    2011-01-01

    Objective Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. Methodology and Main Finding Three electronic data bases were searched over a 30 years period (1978–2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. Conclusion The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys. PMID:21694759

  10. Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review.

    PubMed

    Boulkedid, Rym; Abdoul, Hendy; Loustau, Marine; Sibony, Olivier; Alberti, Corinne

    2011-01-01

    Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. Three electronic data bases were searched over a 30 years period (1978-2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

  11. The Delphi Method in Rehabilitation Counseling Research

    ERIC Educational Resources Information Center

    Vazquez-Ramos, Robinson; Leahy, Michael; Estrada Hernandez, Noel

    2007-01-01

    Rehabilitation researchers have found in the application of the Delphi method a more sophisticated way of obtaining consensus from experts in the field on certain matters. The application of this research methodology has affected and certainly advanced the body of knowledge of the rehabilitation counseling practice. However, the rehabilitation…

  12. Development of an instructional model for higher order thinking in science among secondary school students: a fuzzy Delphi approach

    NASA Astrophysics Data System (ADS)

    Saido, G. A. M.; Siraj, S.; DeWitt, D.; Al-Amedy, O. S.

    2018-05-01

    It is important for science students to develop higher order thinking (HOT) so that they can reason like scientists in the field. In this study, a HOT instructional model for secondary school science was developed with experts. The model would focus on reflective thinking (RT) and science process skills (SPS) among Grade 7 students. The Fuzzy Delphi Method (FDM) was employed to determine consensus among a panel of 20 experts. First, semi-structured interviews were conducted among the experts to generate the elements required for the model. Then, a questionnaire was developed using a seven-point linguistic scale based on these elements. The defuzzification value was calculated for each item, and a threshold value (d) of 0.75 was used to determine consensus for the items in the questionnaire. The alpha-cut value of >0.5 was used to select the phases and sub-phases in the model. The elements in the model were ranked to identify the sub-phases which had to be emphasised for implementation in instruction. Consensus was achieved on the phases of the HOT instructional model: engagement, investigation, explanation, conclusion and reflection. An additional 24 learning activities to encourage RT skills and SPS among students were also identified to develop HOT skills in science.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. [Study on commercial specification of atractylodes based on Delphi method].

    PubMed

    Wang, Hao; Chen, Li-Xiao; Huang, Lu-Qi; Zhang, Tian-Tian; Li, Ying; Zheng, Yu-Guang

    2016-03-01

    This research adopts "Delphi method" to evaluate atractylodes traditional traits and rank correlation. By using methods of mathematical statistics the relationship of the traditional identification indicators and atractylodes goods rank correlation was analyzed, It is found that the main characteristics affectingatractylodes commodity specifications and grades of main characters wereoil points of transaction,color of transaction,color of surface,grain of transaction,texture of transaction andspoilage. The study points out that the original "seventy-six kinds of medicinal materials commodity specification standards of atractylodes differentiate commodity specification" is not in conformity with the actual market situation, we need to formulate corresponding atractylodes medicinal products specifications and grades.This study combined with experimental results "Delphi method" and the market actual situation, proposed the new draft atractylodes commodity specifications and grades, as the new atractylodes commodity specifications and grades standards. It provides a reference and theoretical basis. Copyright© by the Chinese Pharmaceutical Association.

  18. Expert Consensus on Characteristics of Wisdom: A Delphi Method Study

    ERIC Educational Resources Information Center

    Jeste, Dilip V.; Ardelt, Monika; Blazer, Dan; Kraemer, Helena C.; Vaillant, George; Meeks, Thomas W.

    2010-01-01

    Purpose: Wisdom has received increasing attention in empirical research in recent years, especially in gerontology and psychology, but consistent definitions of wisdom remain elusive. We sought to better characterize this concept via an expert consensus panel using a 2-phase Delphi method. Design and Methods: A survey questionnaire comprised 53…

  19. Creation and Delphi-method refinement of pediatric disaster triage simulations.

    PubMed

    Cicero, Mark X; Brown, Linda; Overly, Frank; Yarzebski, Jorge; Meckler, Garth; Fuchs, Susan; Tomassoni, Anthony; Aghababian, Richard; Chung, Sarita; Garrett, Andrew; Fagbuyi, Daniel; Adelgais, Kathleen; Goldman, Ran; Parker, James; Auerbach, Marc; Riera, Antonio; Cone, David; Baum, Carl R

    2014-01-01

    There is a need for rigorously designed pediatric disaster triage (PDT) training simulations for paramedics. First, we sought to design three multiple patient incidents for EMS provider training simulations. Our second objective was to determine the appropriate interventions and triage level for each victim in each of the simulations and develop evaluation instruments for each simulation. The final objective was to ensure that each simulation and evaluation tool was free of bias toward any specific PDT strategy. We created mixed-methods disaster simulation scenarios with pediatric victims: a school shooting, a school bus crash, and a multiple-victim house fire. Standardized patients, high-fidelity manikins, and low-fidelity manikins were used to portray the victims. Each simulation had similar acuity of injuries and 10 victims. Examples include children with special health-care needs, gunshot wounds, and smoke inhalation. Checklist-based evaluation tools and behaviorally anchored global assessments of function were created for each simulation. Eight physicians and paramedics from areas with differing PDT strategies were recruited as Subject Matter Experts (SMEs) for a modified Delphi iterative critique of the simulations and evaluation tools. The modified Delphi was managed with an online survey tool. The SMEs provided an expected triage category for each patient. The target for modified Delphi consensus was ≥85%. Using Likert scales and free text, the SMEs assessed the validity of the simulations, including instances of bias toward a specific PDT strategy, clarity of learning objectives, and the correlation of the evaluation tools to the learning objectives and scenarios. After two rounds of the modified Delphi, consensus for expected triage level was >85% for 28 of 30 victims, with the remaining two achieving >85% consensus after three Delphi iterations. To achieve consensus, we amended 11 instances of bias toward a specific PDT strategy and corrected 10

  20. 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.

  1. 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.

  2. 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

  3. Web-based dynamic Delphi: a new survey instrument

    NASA Astrophysics Data System (ADS)

    Yao, JingTao; Liu, Wei-Ning

    2006-04-01

    We present a mathematical model for a dynamic Delphi survey method which takes advantages of Web technology. A comparative study on the performance of the conventional Delphi method and the dynamic Delphi instrument is conducted. It is suggested that a dynamic Delphi survey may form a consensus quickly. However, the result may not be robust due to the judgement leaking issues.

  4. 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

  5. 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.

  6. 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.

  7. The use of qualitative methods to inform Delphi surveys in core outcome set development.

    PubMed

    Keeley, T; Williamson, P; Callery, P; Jones, L L; Mathers, J; Jones, J; Young, B; Calvert, M

    2016-05-04

    Core outcome sets (COS) help to minimise bias in trials and facilitate evidence synthesis. Delphi surveys are increasingly being used as part of a wider process to reach consensus about what outcomes should be included in a COS. Qualitative research can be used to inform the development of Delphi surveys. This is an advance in the field of COS development and one which is potentially valuable; however, little guidance exists for COS developers on how best to use qualitative methods and what the challenges are. This paper aims to provide early guidance on the potential role and contribution of qualitative research in this area. We hope the ideas we present will be challenged, critiqued and built upon by others exploring the role of qualitative research in COS development. This paper draws upon the experiences of using qualitative methods in the pre-Delphi stage of the development of three different COS. Using these studies as examples, we identify some of the ways that qualitative research might contribute to COS development, the challenges in using such methods and areas where future research is required. Qualitative research can help to identify what outcomes are important to stakeholders; facilitate understanding of why some outcomes may be more important than others, determine the scope of outcomes; identify appropriate language for use in the Delphi survey and inform comparisons between stakeholder data and other sources, such as systematic reviews. Developers need to consider a number of methodological points when using qualitative research: specifically, which stakeholders to involve, how to sample participants, which data collection methods are most appropriate, how to consider outcomes with stakeholders and how to analyse these data. A number of areas for future research are identified. Qualitative research has the potential to increase the research community's confidence in COS, although this will be dependent upon using rigorous and appropriate

  8. Standardizing hysteroscopy teaching: development of a curriculum using the Delphi method.

    PubMed

    Neveu, Marie-Emmanuelle; Debras, Elodie; Niro, Julien; Fernandez, Hervé; Panel, Pierre

    2017-12-01

    Hysteroscopy is performed often and in many indications but is challenging to learn. Hands-on training in live patients faces ethical, legal, and economic obstacles. Virtual reality simulation may hold promise as a hysteroscopy training tool. No validated curriculum specific in hysteroscopy exists. The aim of this study was to develop a hysteroscopy curriculum, using the Delphi method to identify skill requirements. Based on a literature review using the key words "curriculum," "simulation," and "hysteroscopy," we identified five technical and non-technical areas in which skills were required. Twenty hysteroscopy experts from different French hospital departments participated in Delphi rounds to select items in these five areas. The rounds were to be continued until 80-100% agreement was obtained for at least 60% of items. A curriculum was built based on the selected items and was evaluated in residents. From November 2014 to April 2015, 18 of 20 invited experts participated in three Delphi rounds. Of the 51 items selected during the first round, only 25 (49%) had 80-100% agreement during the second round, and a third round was therefore conducted. During this last round, 80-100% agreement was achieved for 31 (61%) items, which were used to create the curriculum. All 14 residents tested felt that a simulator training session was acceptable and helped them to improve their skills. We describe a simulation-based hysteroscopy curriculum focusing on skill requirements identified by a Delphi procedure. Its development allows standardization of training programs offered to residents.

  9. 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.

  10. 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.

  11. Algorithms for monitoring warfarin use: Results from Delphi Method.

    PubMed

    Kano, Eunice Kazue; Borges, Jessica Bassani; Scomparini, Erika Burim; Curi, Ana Paula; Ribeiro, Eliane

    2017-10-01

    Warfarin stands as the most prescribed oral anticoagulant. New oral anticoagulants have been approved recently; however, their use is limited and the reversibility techniques of the anticoagulation effect are little known. Thus, our study's purpose was to develop algorithms for therapeutic monitoring of patients taking warfarin based on the opinion of physicians who prescribe this medicine in their clinical practice. The development of the algorithm was performed in two stages, namely: (i) literature review and (ii) algorithm evaluation by physicians using a Delphi Method. Based on the articles analyzed, two algorithms were developed: "Recommendations for the use of warfarin in anticoagulation therapy" and "Recommendations for the use of warfarin in anticoagulation therapy: dose adjustment and bleeding control." Later, these algorithms were analyzed by 19 medical doctors that responded to the invitation and agreed to participate in the study. Of these, 16 responded to the first round, 11 to the second and eight to the third round. A 70% consensus or higher was reached for most issues and at least 50% for six questions. We were able to develop algorithms to monitor the use of warfarin by physicians using a Delphi Method. The proposed method is inexpensive and involves the participation of specialists, and it has proved adequate for the intended purpose. Further studies are needed to validate these algorithms, enabling them to be used in clinical practice.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. The Use of the Delphi and Other Consensus Group Methods in Medical Education Research: A Review.

    PubMed

    Humphrey-Murto, Susan; Varpio, Lara; Wood, Timothy J; Gonsalves, Carol; Ufholz, Lee-Anne; Mascioli, Kelly; Wang, Carol; Foth, Thomas

    2017-10-01

    Consensus group methods, such as the Delphi method and nominal group technique (NGT), are used to synthesize expert opinions when evidence is lacking. Despite their extensive use, these methods are inconsistently applied. Their use in medical education research has not been well studied. The authors set out to describe the use of consensus methods in medical education research and to assess the reporting quality of these methods and results. Using scoping review methods, the authors searched the Medline, Embase, PsycInfo, PubMed, Scopus, and ERIC databases for 2009-2016. Full-text articles that focused on medical education and the keywords Delphi, RAND, NGT, or other consensus group methods were included. A standardized extraction form was used to collect article demographic data and features reflecting methodological rigor. Of the articles reviewed, 257 met the inclusion criteria. The Modified Delphi (105/257; 40.8%), Delphi (91/257; 35.4%), and NGT (23/257; 8.9%) methods were most often used. The most common study purpose was curriculum development or reform (68/257; 26.5%), assessment tool development (55/257; 21.4%), and defining competencies (43/257; 16.7%). The reporting quality varied, with 70.0% (180/257) of articles reporting a literature review, 27.2% (70/257) reporting what background information was provided to participants, 66.1% (170/257) describing the number of participants, 40.1% (103/257) reporting if private decisions were collected, 37.7% (97/257) reporting if formal feedback of group ratings was shared, and 43.2% (111/257) defining consensus a priori. Consensus methods are poorly standardized and inconsistently used in medical education research. Improved criteria for reporting are needed.

  18. 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.

  19. Considerations when conducting e-Delphi research: a case study.

    PubMed

    Toronto, Coleen

    2017-06-22

    Background E-Delphi is a way to access a geographically dispersed group of experts. It is similar to other Delphi methods but conducted online. E-research methodologies, such as the e-Delphi method, have yet to undergo significant critical discussion. Aim To highlight some of the challenges nurse researchers may wish to consider when using e-Delphi in their research. Discussion This paper provides details about the author's approach to conducting an e-Delphi study in which a group of health literacy nurse experts (n=41) used an online survey platform to identify and prioritise essential health literacy competencies for registered nurses. Conclusion This paper advances methodological discourse about e-Delphi by critically assessing an e-Delphi case study. The online survey platform used in this study was advantageous for the researcher and the experts: the experts could participate at any time and place where the internet was available; the researcher could efficiently access a national group of experts, track responses and analyse data in each round. Implications for practice E-Delphi studies create opportunities for nurse researchers to conduct research nationally and internationally. Before conducting an e-Delphi study, researchers should carefully consider the design and methods for collecting data, to avoid challenges that could potentially compromise the quality of the findings. Researchers are encouraged to publish details about their approaches to e-Delphi studies, to advance the state of the science.

  20. 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.

  1. The development of ethical guidelines for nurses' collegiality using the Delphi method.

    PubMed

    Kangasniemi, Mari; Arala, Katariina; Becker, Eve; Suutarla, Anna; Haapa, Toni; Korhonen, Anne

    2017-08-01

    Nurses' collegiality is topical because patient care is complicated, requiring shared knowledge and working methods. Nurses' collaboration has been supported by a number of different working models, but there has been less focus on ethics. This study aimed to develop nurses' collegiality guidelines using the Delphi method. Two online panels of Finnish experts, with 35 and 40 members, used the four-step Delphi method in December 2013 and January 2014. They reformulated the items of nurses' collegiality identified by the literature and rated based on validity and importance. Content analysis and descriptive statistical methods were used to analyze the data, and the nurses' collegiality guidelines were formulated. Ethical considerations: Organizational approval was received, and an informed consent was obtained from all participants. Information about the voluntary nature of participation was provided. During the first Delphi panel round, a number of items were reformulated and added, resulting in 32 reformulated items. As a result of the second round, 8 of the 32 items scored an agreement rate of more than 75%, with the most rated item being collegiality means that professionals respect each other. The item with second highest rating was collegiality has a common objective: what is best for patients, followed by the third highest which was professional ethics is the basis of collegiality. Nurses' collegiality and its content are well recognized in clinical practice but seldom studied. Collegiality can be supported by guidelines, and nurses working in clinical practice, together with teachers and managers, have shared responsibilities to support and develop it. More research in different nursing environments is needed to improve understanding of the content and practice of nursing collegiality.

  2. 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.

  3. 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.

  4. [Identification of the scope of practice for dental nurses with Delphi method].

    PubMed

    Li, Yu-Hong; Lu, Yue-Cen; Huang, Yao; Ruan, Hong; Wu, Zheng-Yi

    2016-10-01

    To identify the practice scope of dental nurses under the new situations. The draft of scope of practice for dental nurses was based on theoretical analysis, literature review and consultation of advisory panel, and the final scope of practice for dental nurses was established by using the Delphi method. Statistical analysis was implemented using coefficient of variation, Kendall W with SPSS 17.0 software package. Thirty experts were consulted twice by using the Delphi method. The effective rates of two rounds of questionnaire were 100% and 73.3%, respectively. The authority coefficient was 0.837, and the P value of expert coordination coefficients W was less than 0.05. There were totally 116 suggestions from the experts, and 96 were accepted. The scope of practice for dental nurses was finally established, including 4 primary indexes and 25 secondary indexes. The scope of practice for dental nurses under the new situations is established in China through scientific methods. It is favorable for position management of dental nurses and may promote the development of nurse specialists in dental clinic.

  5. Delphi: An Overview, An Application, Some Lessons.

    ERIC Educational Resources Information Center

    Moore, Carl M.; Coke, James G.

    This paper discusses Delphi-a method of utilizing individuals' knowledge, judgment, and opinions to address complex questions and applies the method to a community planning project in Stow, Ohio. There are four phases of any Delphi: (1) exploring the subject under discussion, with each individual contributing pertinent information, (2) reaching an…

  6. 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.

  7. Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi

    PubMed Central

    Li, Chuan; Li, Lin; Zhang, Jie; Alexov, Emil

    2012-01-01

    The Gauss-Seidel method is a standard iterative numerical method widely used to solve a system of equations and, in general, is more efficient comparing to other iterative methods, such as the Jacobi method. However, standard implementation of the Gauss-Seidel method restricts its utilization in parallel computing due to its requirement of using updated neighboring values (i.e., in current iteration) as soon as they are available. Here we report an efficient and exact (not requiring assumptions) method to parallelize iterations and to reduce the computational time as a linear/nearly linear function of the number of CPUs. In contrast to other existing solutions, our method does not require any assumptions and is equally applicable for solving linear and nonlinear equations. This approach is implemented in the DelPhi program, which is a finite difference Poisson-Boltzmann equation solver to model electrostatics in molecular biology. This development makes the iterative procedure on obtaining the electrostatic potential distribution in the parallelized DelPhi several folds faster than that in the serial code. Further we demonstrate the advantages of the new parallelized DelPhi by computing the electrostatic potential and the corresponding energies of large supramolecular structures. PMID:22674480

  8. Classification of Children Intelligence with Fuzzy Logic Method

    NASA Astrophysics Data System (ADS)

    Syahminan; ika Hidayati, Permata

    2018-04-01

    Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

  9. Using the Delphi method to develop nursing-sensitive quality indicators for the NICU.

    PubMed

    Chen, Lin; Huang, Li-Hua; Xing, Mei-Yuan; Feng, Zhi-Xian; Shao, Le-Wen; Zhang, Mei-Yun; Shao, Rong-Ya

    2017-02-01

    To develop nursing-sensitive quality indicators consistent with current medical practices in Chinese neonatal intensive care units. The development of nursing-sensitive quality indicators has become a top priority in nursing management. To the best of our knowledge, there has been no objective, scientific and sensitive evaluation of the quality of neonatal intensive care unit nursing in China. A modified Delphi technique was used to seek opinions from experts about what should be used and prioritised as indicators of quality care in neonatal intensive care unit nursing. Based on a literature review, we identified 21 indicators of nursing-sensitive quality in the neonatal intensive care unit. Our group of 11 consultants chose 13 indicators to be discussed using the Delphi method. In October and November 2014, 39 neonatal intensive care unit experts in 18 tertiary hospitals spread across six provinces participated in two rounds of Delphi panels. Of the 13 indicators discussed, 11 were identified as indicators of nursing-sensitive quality in the neonatal intensive care unit: rate of nosocomial infections, rate of accidental endotracheal extubation, rate of errors in medication administration, rate of treatment for pain, rate of peripheral venous extravasation, rate of compliance with handwashing techniques, incidence of pressure ulcers, incidence of noise, the bed-to-care ratio, the proportion of nurses with greater than five years neonatal intensive care unit experience and incidence of retinopathy. The 11 neonatal intensive care unit nursing-sensitive indicators identified by the Delphi method integrated with basic Chinese practices provide a basis for nursing management and the monitoring of nursing quality. This study identified nursing-sensitive quality indicators for neonatal intensive care unit care that are suitable for current clinical practice in China. © 2016 John Wiley & Sons Ltd.

  10. 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.

  11. Development of a nationwide consensus syllabus of palliative medicine for undergraduate medical education in Japan: a modified Delphi method.

    PubMed

    Kizawa, Yoshiyuki; Tsuneto, Satoru; Tamba, Kaichiro; Takamiya, Yusuke; Morita, Tatsuya; Bito, Seiji; Otaki, Junji

    2012-07-01

    There is currently no consensus syllabus of palliative medicine for undergraduate medical education in Japan, although the Cancer Control Act proposed in 2007 covers the dissemination of palliative care. To develop a nationwide consensus syllabus of palliative medicine for undergraduate medical education in Japan using a modified Delphi method. We adopted the following three-step method: (1) a workshop to produce the draft syllabus; (2) a survey-based provisional syllabus; (3) Delphi rounds and a panel meeting (modified Delphi method) to produce the working syllabus. Educators in charge of palliative medicine from 63% of the medical schools in Japan collaborated to develop a survey-based provisional syllabus before the Delphi rounds. A panel of 32 people was then formed for the modified Delphi rounds comprising 28 educators and experts in palliative medicine, one cancer survivor, one bereaved family member, and two medical students. The final consensus syllabus consists of 115 learning objectives across seven sections as follows: basic principles; disease process and comprehensive assessment; symptom management; psychosocial care; cultural, religious, and spiritual issues; ethical issues; and legal frameworks. Learning objectives were categorized as essential or desirable (essential: 66; desirable: 49). A consensus syllabus of palliative medicine for undergraduate medical education was developed using a clear and innovative methodology. The final consensus syllabus will be made available for further dissemination of palliative care education throughout the country.

  12. 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.

  13. High dimensional model representation method for fuzzy structural dynamics

    NASA Astrophysics Data System (ADS)

    Adhikari, S.; Chowdhury, R.; Friswell, M. I.

    2011-03-01

    Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

  14. 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.

  15. Use of the Delphi method in resolving complex water resources issues

    USGS Publications Warehouse

    Taylor, J.G.; Ryder, S.D.

    2003-01-01

    The tri-state river basins, shared by Georgia, Alabama, and Florida, are being modeled by the U.S. Fish and Wildlife Service and the U.S. Army Corps of Engineers to help facilitate agreement in an acrimonious water dispute among these different state governments. Modeling of such basin reservoir operations requires parallel understanding of several river system components: hydropower production, flood control, municipal and industrial water use, navigation, and reservoir fisheries requirements. The Delphi method, using repetitive surveying of experts, was applied to determine fisheries' water and lake-level requirements on 25 reservoirs in these interstate basins. The Delphi technique allowed the needs and requirements of fish populations to be brought into the modeling effort on equal footing with other water supply and demand components. When the subject matter is concisely defined and limited, this technique can rapidly assess expert opinion on any natural resource issue, and even move expert opinion toward greater agreement.

  16. Defining the role of a forensic hospital registered nurse using the Delphi method.

    PubMed

    Newman, Claire; Patterson, Karen; Eason, Michelle; Short, Ben

    2016-11-01

    A Delphi survey was undertaken to refine the position description of a registered nurse working in a forensic hospital, in New South Wales, Australia. Prior to commencing operation in 2008, position descriptions were developed from a review of legislation, as well as policies and procedures used by existing forensic mental health services in Australia. With an established workforce and an evolving model of care, a review of the initial registered nurse position description was required. An online Delphi survey was undertaken. Eight executive (88.9%) and 12 (58.3%) senior nursing staff participated in the first survey round. A total of four survey rounds were completed. At the final round, there was consensus (70%) that the revised position description was either very or somewhat suitable. There were a total of nine statements, from 31 originally produced in round 1, that did not reach consensus. The Delphi survey enabled a process for refining the Forensic Hospital registered nurse position description. Methods that facilitate executive and senior nursing staff consensus in the development and review of position descriptions should be considered in nursing management. © 2016 John Wiley & Sons Ltd.

  17. The use of advanced web-based survey design in Delphi research.

    PubMed

    Helms, Christopher; Gardner, Anne; McInnes, Elizabeth

    2017-12-01

    A discussion of the application of metadata, paradata and embedded data in web-based survey research, using two completed Delphi surveys as examples. Metadata, paradata and embedded data use in web-based Delphi surveys has not been described in the literature. The rapid evolution and widespread use of online survey methods imply that paper-based Delphi methods will likely become obsolete. Commercially available web-based survey tools offer a convenient and affordable means of conducting Delphi research. Researchers and ethics committees may be unaware of the benefits and risks of using metadata in web-based surveys. Discussion paper. Two web-based, three-round Delphi surveys were conducted sequentially between August 2014 - January 2015 and April - May 2016. Their aims were to validate the Australian nurse practitioner metaspecialties and their respective clinical practice standards. Our discussion paper is supported by researcher experience and data obtained from conducting both web-based Delphi surveys. Researchers and ethics committees should consider the benefits and risks of metadata use in web-based survey methods. Web-based Delphi research using paradata and embedded data may introduce efficiencies that improve individual participant survey experiences and reduce attrition across iterations. Use of embedded data allows the efficient conduct of multiple simultaneous Delphi surveys across a shorter timeframe than traditional survey methods. The use of metadata, paradata and embedded data appears to improve response rates, identify bias and give possible explanation for apparent outlier responses, providing an efficient method of conducting web-based Delphi surveys. © 2017 John Wiley & Sons Ltd.

  18. Terminating Sequential Delphi Survey Data Collection

    ERIC Educational Resources Information Center

    Kalaian, Sema A.; Kasim, Rafa M.

    2012-01-01

    The Delphi survey technique is an iterative mail or electronic (e-mail or web-based) survey method used to obtain agreement or consensus among a group of experts in a specific field on a particular issue through a well-designed and systematic multiple sequential rounds of survey administrations. Each of the multiple rounds of the Delphi survey…

  19. Fuzzy set methods for object recognition in space applications

    NASA Technical Reports Server (NTRS)

    Keller, James M.

    1992-01-01

    Progress on the following tasks is reported: feature calculation; membership calculation; clustering methods (including initial experiments on pose estimation); and acquisition of images (including camera calibration information for digitization of model). The report consists of 'stand alone' sections, describing the activities in each task. We would like to highlight the fact that during this quarter, we believe that we have made a major breakthrough in the area of fuzzy clustering. We have discovered a method to remove the probabilistic constraints that the sum of the memberships across all classes must add up to 1 (as in the fuzzy c-means). A paper, describing this approach, is included.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. Aquifer water abundance evaluation using a fuzzy- comprehensive weighting method

    NASA Astrophysics Data System (ADS)

    Wei, Z.

    2016-08-01

    Aquifer water abundance evaluation is a highly relevant issue that has been researched for many years. Despite prior research, problems with the conventional evaluation method remain. This paper establishes an aquifer water abundance evaluation method that combines fuzzy evaluation with a comprehensive weighting method to overcome both the subjectivity and lack of conformity in determining weight by pure data analysis alone. First, this paper introduces the principle of a fuzzy-comprehensive weighting method. Second, the example of well field no. 3 (of a coalfield) is used to illustrate the method's process. The evaluation results show that this method is can more suitably meet the real requirements of aquifer water abundance assessment, leading to more precise and accurate evaluations. Ultimately, this paper provides a new method for aquifer water abundance evaluation.

  7. 75 FR 16513 - Delphi Packard Electrical/Electronic Architecture, a Subsidiary of Delphi Corporation, Including...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-01

    .../Electronic Architecture, a Subsidiary of Delphi Corporation, Including On-Site Leased Workers From Bartech... Assistance on December 8th, 2009, applicable to workers of Delphi Packard Electrical/Electronic Architecture... location of Delphi Packard Electrical/Electronic Architecture, a subsidiary of Delphi Corporation. The...

  8. 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.

  9. Idea Generation and Exploration: Benefits and Limitations of the Policy Delphi Research Method

    ERIC Educational Resources Information Center

    Franklin, Kathy K.; Hart, Jan K.

    2007-01-01

    Researchers use the policy Delphi method to explore a complex topic with little historical context that requires expert opinion to fully understand underlying issues. The benefit of this research technique is the use of experts who have more timely information than can be gleamed from extant literature. Additionally, those experts place…

  10. 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

  11. Youth injury prevention in Canada: use of the Delphi method to develop recommendations.

    PubMed

    Pike, Ian; Piedt, Shannon; Davison, Colleen M; Russell, Kelly; Macpherson, Alison K; Pickett, William

    2015-12-22

    The Health Behaviour in School-aged Children Survey is one of very few cross-national health surveys that includes information on injury occurrence and prevention within adolescent populations. A collaboration to develop a Canadian youth injury report using these data resulted in, Injury among Young Canadians: A national study of contextual determinants. The objective of this study was to develop specific evidence-based, policy-oriented recommendations arising from the national report, using a modified-Delphi process with a panel of expert stakeholders. Eight injury prevention experts and a 3-person youth advisory team associated with a Canadian injury prevention organization (Parachute Canada) reviewed, edited and commented on report recommendations through a three-stage iterative modified-Delphi process. From an initial list of 27 draft recommendations, the modified-Delphi process resulted in a final list of 19 specific recommendations, worded to resonate with the group(s) responsible to lead or take the recommended action. Two recommendations were rated as "extremely important" or "very important" by 100 % of the expert panel, two were deleted, a further two recommendations were deleted but the content included as text in the report, and four were merged with other existing recommendations. The modified-Delphi process was an appropriate method to achieve agreement on 19 specific evidence-based, policy-oriented recommendations to complement the national youth injury report. In providing their input, it is noted that the injury stakeholders each acted as individual experts, unattached to any organizational position or policy. These recommendations will require multidisciplinary collaborations in order to support the proposed policy development, additional research, programming and clear decision-making for youth injury prevention.

  12. Application of the Delphi technique in healthcare maintenance.

    PubMed

    Njuangang, Stanley; Liyanage, Champika; Akintoye, Akintola

    2017-10-09

    Purpose The purpose of this paper is to examine the research design, issues and considerations in the application of the Delphi technique to identify, refine and rate the critical success factors and performance measures in maintenance-associated infections. Design/methodology/approach In-depth literature review through the application of open and axial coding were applied to formulate the interview and research questions. These were used to conduct an exploratory case study of two healthcare maintenance managers, randomly selected from two National Health Service Foundation Trusts in England. The results of exploratory case study provided the rationale for the application of the Delphi technique in this research. The different processes in the application of the Delphi technique in healthcare research are examined thoroughly. Findings This research demonstrates the need to apply and integrate different research methods to enhance the validity of the Delphi technique. The rationale for the application of the Delphi technique in this research is because some healthcare maintenance managers lack knowledge about basic infection control (IC) principles to make hospitals safe for patient care. The result of first round of the Delphi exercise is a useful contribution in its own rights. It identified a number of salient issues and differences in the opinions of the Delphi participants, noticeably between healthcare maintenance managers and members of the infection control team. It also resulted in useful suggestions and comments to improve the quality and presentation of the second- and third-round Delphi instruments. Practical implications This research provides a research methodology that can be adopted by researchers investigating new and emerging issues in the healthcare sector. As this research demonstrates, the Delphi technique is relevant in soliciting expert knowledge and opinion to identify performance measures to control maintenance-associated infections in

  13. 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.

  14. 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.

  15. Identifying research priorities for public health research to address health inequalities: use of Delphi-like survey methods.

    PubMed

    Turner, S; Ollerhead, E; Cook, A

    2017-10-09

    In the funding of health research and public health research it is vital that research questions posed are important and that funded research meets a research need or a gap in evidence. Many methods are used in the identification of research priorities, however, these can be resource intensive, costly and logistically challenging. Identifying such research priorities can be particularly challenging for complex public health problems as there is a need to consult a number of experts across disciplines and with a range of expertise. This study investigated the use of Delphi-like survey methods in identifying important research priorities relating to health inequalities and framing tractable research questions for topic areas identified. The study was conducted in two phases, both using Delphi-like survey methods. Firstly, public health professionals with an interest in health inequalities were asked to identify research priorities. Secondly academic researchers were asked to frame tractable research questions relating to the priorities identified. These research priorities identified using Delphi-like survey methods were subsequently compared to those identified using different methods. A total of 52 public health professionals and 21 academics across the United Kingdom agreed to take part. The response rates were high, from public health professionals across three survey rounds (69%, 50% and 40%) and from academics across one round (52%), indicating that participants were receptive to the method and motivated to respond. The themes identified as encompassing the most important research priorities were mental health, healthy environment and health behaviours. Within these themes, the topic areas that emerged most strongly included community interventions for prevention of mental health problems and the food and alcohol environment. Some responses received from academic researchers were (as requested) in the form of tractable research questions, whereas others

  16. [Development of HIV infection risk assessment tool for men who have sex with men based on Delphi method].

    PubMed

    Li, L L; Jiang, Z; Song, W L; Ding, Y Y; Xu, J; He, N

    2017-10-10

    Objective: To develop a HIV infection risk assessment tool for men who have sex with men (MSM) based on Delphi method. Methods: After an exhaustive literature review, we used Delphi method to determine the specific items and relative risk scores of the assessment tool through two rounds of specialist consultation and overall consideration of the opinions and suggestions of 17 specialists. Results: The positivity coefficient through first and second round specialist consultation was 100.0 % and 94.1 % , respectively. The mean of authority coefficients ( Cr ) was 0.86. Kendall's W coefficient of the specialist consultation was 0.55 for the first round consultation (χ(2)=84.426, P <0.001) and 0.46 for the second round consultation (χ(2)=65.734, P <0.001), respectively, suggesting that the specialists had similar opinions. The final HIV infection risk assessment tool for MSM has 8 items. Conclusions: The HIV infection risk assessment tool for MSM, developed under the Delphi method, can be used in the evaluation of HIV infection risk in MSM and individualized prevention and intervention. However, the reliability and validity of this risk assessment tool need to be further evaluated.

  17. A modified Delphi method toward multidisciplinary consensus on functional convalescence recommendations after abdominal surgery.

    PubMed

    van Vliet, Daphne C R; van der Meij, Eva; Bouwsma, Esther V A; Vonk Noordegraaf, Antonie; van den Heuvel, Baukje; Meijerink, Wilhelmus J H J; van Baal, W Marchien; Huirne, Judith A F; Anema, Johannes R

    2016-12-01

    Evidence-based information on the resumption of daily activities following uncomplicated abdominal surgery is scarce and not yet standardized in medical guidelines. As a consequence, convalescence recommendations are generally not provided after surgery, leading to patients' insecurity, needlessly delayed recovery and prolonged sick leave. The aim of this study was to generate consensus-based multidisciplinary convalescence recommendations, including advice on return to work, applicable for both patients and physicians. Using a modified Delphi method among a multidisciplinary panel of 13 experts consisting of surgeons, occupational physicians and general practitioners, detailed recommendations were developed for graded resumption of 34 activities after uncomplicated laparoscopic cholecystectomy, laparoscopic and open appendectomy, laparoscopic and open colectomy and laparoscopic and open inguinal hernia repair. A sample of occupational physicians, general practitioners and surgeons assessed the recommendations on feasibility in daily practice. The response of this group of care providers was discussed with the experts in the final Delphi questionnaire round. Out of initially 56 activities, the expert panel selected 34 relevant activities for which convalescence recommendations were developed. After four Delphi rounds, consensus was reached for all of the 34 activities for all the surgical procedures. A sample of occupational physicians, general practitioners and surgeons regarded the recommendations as feasible in daily practice. Multidisciplinary convalescence recommendations regarding uncomplicated laparoscopic cholecystectomy, appendectomy (laparoscopic, open), colectomy (laparoscopic, open) and inguinal hernia repair (laparoscopic, open) were developed by a modified Delphi procedure. Further research is required to evaluate whether these recommendations are realistic and effective in daily practice.

  18. Cost estimation: An expert-opinion approach. [cost analysis of research projects using the Delphi method (forecasting)

    NASA Technical Reports Server (NTRS)

    Buffalano, C.; Fogleman, S.; Gielecki, M.

    1976-01-01

    A methodology is outlined which can be used to estimate the costs of research and development projects. The approach uses the Delphi technique a method developed by the Rand Corporation for systematically eliciting and evaluating group judgments in an objective manner. The use of the Delphi allows for the integration of expert opinion into the cost-estimating process in a consistent and rigorous fashion. This approach can also signal potential cost-problem areas. This result can be a useful tool in planning additional cost analysis or in estimating contingency funds. A Monte Carlo approach is also examined.

  19. 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

  20. 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.

  1. 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.

  2. 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%.

  3. Comparing Management Models of Secondary Schools in Tamaulipas, Mexico: An Exploration with a Delphi Method

    ERIC Educational Resources Information Center

    Navarro-Leal, Marco Aurelio; Garcia, Concepcion Nino; Saldivar, Luisa Caballero

    2012-01-01

    For a preliminary exploration of management models between two secondary schools, a Delphi method was used in order to identify and focus relevant topics for a larger research. A first approximation with this method proved to be a heuristic tool to focus and define some categories and guidelines of enquiry. It was found that in both of the schools…

  4. Development of the Assessment Items of Debris Flow Using the Delphi Method

    NASA Astrophysics Data System (ADS)

    Byun, Yosep; Seong, Joohyun; Kim, Mingi; Park, Kyunghan; Yoon, Hyungkoo

    2016-04-01

    In recent years in Korea, Typhoon and the localized extreme rainfall caused by the abnormal climate has increased. Accordingly, debris flow is becoming one of the most dangerous natural disaster. This study aimed to develop the assessment items which can be used for conducting damage investigation of debris flow. Delphi method was applied to classify the realms of assessment items. As a result, 29 assessment items which can be classified into 6 groups were determined.

  5. 75 FR 28655 - Delphi Packard Electrical/Electronic Architecture, a Subsidiary of Delphi Corporation, Including...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-21

    .../Electronic Architecture, a Subsidiary of Delphi Corporation, Including On-Site Leased Workers From Bartech... Assistance on December 8, 2009, applicable to workers of Delphi Packard Electrical/Electronic Architecture, a.../Electronic Architecture, a subsidiary of Delphi Corporation, including on-site leased [[Page 28656

  6. [Construction of a physiological aging scale for healthy people based on a modified Delphi method].

    PubMed

    Long, Yao; Zhou, Xuan; Deng, Pengfei; Liao, Xiong; Wu, Lei; Zhou, Jianming; Huang, Helang

    2016-04-01

    To build a physiological aging scale for healthy people.
 We collected age-related physiologic items through literature screening and expert interview. Two rounds of Delphi were implemented. The importance, feasibility and the degree of authority for the physiological index system were graded. Using analytic hierarchy process, we determined the weight of dimensions and items.
 Using Delphy mothod, 17 physiological and other professional experts offered the results as follow: coefficient of expert authorities Cr was 0.86±0.03, coordination coefficients for the first and second round were 0.264(χ2=229.691, P<0.001) and 0.293(χ2=228.474,P<0.001), respectively. The consistency was good. The aging scale for healthy people included 3 dimensions, namely physical form, feeling movement and functional status. Each dimension had 8 items. The weight coefficients for the 3 dimensions were 0.54, 0.16, and 0.30, respectively. The Cronbach's α coefficient of the scale was 0.893, the reliability was 0.796, and the variance of the common factor was 58.17%.
 The improved Delphi method or physiological aging scale is satisfied, which can provide reference for the evaluation of aging.

  7. Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.

    PubMed

    Ren, Peijia; Xu, Zeshui; Hao, Zhinan

    2017-09-01

    Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.

  8. An automatic iterative decision-making method for intuitionistic fuzzy linguistic preference relations

    NASA Astrophysics Data System (ADS)

    Pei, Lidan; Jin, Feifei; Ni, Zhiwei; Chen, Huayou; Tao, Zhifu

    2017-10-01

    As a new preference structure, the intuitionistic fuzzy linguistic preference relation (IFLPR) was recently introduced to efficiently deal with situations in which the membership and non-membership are represented as linguistic terms. In this paper, we study the issues of additive consistency and the derivation of the intuitionistic fuzzy weight vector of an IFLPR. First, the new concepts of order consistency, additive consistency and weak transitivity for IFLPRs are introduced, and followed by a discussion of the characterisation about additive consistent IFLPRs. Then, a parameterised transformation approach is investigated to convert the normalised intuitionistic fuzzy weight vector into additive consistent IFLPRs. After that, a linear optimisation model is established to derive the normalised intuitionistic fuzzy weights for IFLPRs, and a consistency index is defined to measure the deviation degree between an IFLPR and its additive consistent IFLPR. Furthermore, we develop an automatic iterative decision-making method to improve the IFLPRs with unacceptable additive consistency until the adjusted IFLPRs are acceptable additive consistent, and it helps the decision-maker to obtain the reasonable and reliable decision-making results. Finally, an illustrative example is provided to demonstrate the validity and applicability of the proposed method.

  9. Reference Materials in LIS Instruction: A Delphi Study

    ERIC Educational Resources Information Center

    Rabina, Debbie

    2013-01-01

    This paper presents the results of a Delphi study conducted over a two-month period in 2011. The purpose of the study was to identify reference sources that should be covered in basic reference courses taught in LIS programs in the United States. The Delphi method was selected for its appropriateness in soliciting expert opinions and assessing the…

  10. How to use the nominal group and Delphi techniques.

    PubMed

    McMillan, Sara S; King, Michelle; Tully, Mary P

    2016-06-01

    Introduction The Nominal Group Technique (NGT) and Delphi Technique are consensus methods used in research that is directed at problem-solving, idea-generation, or determining priorities. While consensus methods are commonly used in health services literature, few studies in pharmacy practice use these methods. This paper provides an overview of the NGT and Delphi technique, including the steps involved and the types of research questions best suited to each method, with examples from the pharmacy literature. Methodology The NGT entails face-to-face discussion in small groups, and provides a prompt result for researchers. The classic NGT involves four key stages: silent generation, round robin, clarification and voting (ranking). Variations have occurred in relation to generating ideas, and how 'consensus' is obtained from participants. The Delphi technique uses a multistage self-completed questionnaire with individual feedback, to determine consensus from a larger group of 'experts.' Questionnaires have been mailed, or more recently, e-mailed to participants. When to use The NGT has been used to explore consumer and stakeholder views, while the Delphi technique is commonly used to develop guidelines with health professionals. Method choice is influenced by various factors, including the research question, the perception of consensus required, and associated practicalities such as time and geography. Limitations The NGT requires participants to personally attend a meeting. This may prove difficult to organise and geography may limit attendance. The Delphi technique can take weeks or months to conclude, especially if multiple rounds are required, and may be complex for lay people to complete.

  11. 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.

  12. 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.

  13. Key Features of Academic Detailing: Development of an Expert Consensus Using the Delphi Method

    PubMed Central

    Yeh, James S.; Van Hoof, Thomas J.; Fischer, Michael A.

    2016-01-01

    Background Academic detailing is an outreach education technique that combines the direct social marketing traditionally used by pharmaceutical representatives with unbiased content summarizing the best evidence for a given clinical issue. Academic detailing is conducted with clinicians to encourage evidence-based practice in order to improve the quality of care and patient outcomes. The adoption of academic detailing has increased substantially since the original studies in the 1980s. However, the lack of standard agreement on its implementation makes the evaluation of academic detailing outcomes challenging. Objective To identify consensus on the key elements of academic detailing among a group of experts with varying experiences in academic detailing. Methods This study is based on an online survey of 20 experts with experience in academic detailing. We used the Delphi process, an iterative and systematic method of developing consensus within a group. We conducted 3 rounds of online surveys, which addressed 72 individual items derived from a previous literature review of 5 features of academic detailing, including (1) content, (2) communication process, (3) clinicians targeted, (4) change agents delivering intervention, and (5) context for intervention. Nonrespondents were removed from later rounds of the surveys. For most questions, a 4-point ordinal scale was used for responses. We defined consensus agreement as 70% of respondents for a single rating category or 80% for dichotomized ratings. Results The overall survey response rate was 95% (54 of 57 surveys) and nearly 92% consensus agreement on the survey items (66 of 72 items) by the end of the Delphi exercise. The experts' responses suggested that (1) focused clinician education offering support for clinical decision-making is a key component of academic detailing, (2) detailing messages need to be tailored and provide feasible strategies and solutions to challenging cases, and (3) academic detailers need

  14. Exploration to Identify Professional Dispositions of School Librarians: A Delphi Study

    ERIC Educational Resources Information Center

    Bush, Gail; Jones, Jami L.

    2010-01-01

    This article reports the findings of an exploratory study to identify professional dispositions of school librarians. The authors employed the Delphi method, a qualitative research method that emphasizes expert knowledge and consensus within a particular field. The Delphi panel consisted of members of the editorial boards of nationally recognized…

  15. Expert Consensus for Discharge Referral Decisions Using Online Delphi

    PubMed Central

    Bowles, Kathy H.; Holmes, John H.; Naylor, Mary D.; Liberatore, Matthew; Nydick, Robert

    2003-01-01

    This paper describes the results of using a modified Delphi approach designed to achieve consensus from eight discharge planning experts regarding the decision to refer hospitalized older adults for post-discharge follow-up. Experts reviewed 150 cases using an online website designed to facilitate their interaction and efforts to reach agreement on the need for a referral for post-discharge care and the appropriate site for such care. In contrast to an average of eight weeks to complete just 50 cases using the traditional mail method, the first online Delphi round for 150 cases were completed in six weeks. Data provided by experts suggest that online Delphi is a time efficient and acceptable methodology for reaching group consensus. Other benefits include instant access to Delphi decision results, live knowledge of the time requirements and progress of each expert, and cost savings in postage, paper, copying, and storage of paper documents. This online Delphi methodology is highly recommended. PMID:14728143

  16. 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.

  17. Deterministic and fuzzy-based methods to evaluate community resilience

    NASA Astrophysics Data System (ADS)

    Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

    2018-04-01

    Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

  18. 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.

  19. 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.

  20. Designing Excellence and Quality Model for Training Centers of Primary Health Care: A Delphi Method Study.

    PubMed

    Tabrizi, Jafar-Sadegh; Farahbakhsh, Mostafa; Shahgoli, Javad; Rahbar, Mohammad Reza; Naghavi-Behzad, Mohammad; Ahadi, Hamid-Reza; Azami-Aghdash, Saber

    2015-10-01

    Excellence and quality models are comprehensive methods for improving the quality of healthcare. The aim of this study was to design excellence and quality model for training centers of primary health care using Delphi method. In this study, Delphi method was used. First, comprehensive information were collected using literature review. In extracted references, 39 models were identified from 34 countries and related sub-criteria and standards were extracted from 34 models (from primary 39 models). Then primary pattern including 8 criteria, 55 sub-criteria, and 236 standards was developed as a Delphi questionnaire and evaluated in four stages by 9 specialists of health care system in Tabriz and 50 specialists from all around the country. Designed primary model (8 criteria, 55 sub-criteria, and 236 standards) were concluded with 8 criteria, 45 sub-criteria, and 192 standards after 4 stages of evaluations by specialists. Major criteria of the model are leadership, strategic and operational planning, resource management, information analysis, human resources management, process management, costumer results, and functional results, where the top score was assigned as 1000 by specialists. Functional results had the maximum score of 195 whereas planning had the minimum score of 60. Furthermore the most and the least sub-criteria was for leadership with 10 sub-criteria and strategic planning with 3 sub-criteria, respectively. The model that introduced in this research has been designed following 34 reference models of the world. This model could provide a proper frame for managers of health system in improving quality.

  1. A Combination of Extended Fuzzy AHP and Fuzzy GRA for Government E-Tendering in Hybrid Fuzzy Environment

    PubMed Central

    Wang, Yan; Xi, Chengyu; Zhang, Shuai; Yu, Dejian; Zhang, Wenyu; Li, Yong

    2014-01-01

    The recent government tendering process being conducted in an electronic way is becoming an inevitable affair for numerous governmental agencies to further exploit the superiorities of conventional tendering. Thus, developing an effective web-based bid evaluation methodology so as to realize an efficient and effective government E-tendering (GeT) system is imperative. This paper firstly investigates the potentiality of employing fuzzy analytic hierarchy process (AHP) along with fuzzy gray relational analysis (GRA) for optimal selection of candidate tenderers in GeT process with consideration of a hybrid fuzzy environment with incomplete weight information. We proposed a novel hybrid fuzzy AHP-GRA (HFAHP-GRA) method that combines an extended fuzzy AHP with a modified fuzzy GRA. The extended fuzzy AHP which combines typical AHP with interval AHP is proposed to obtain the exact weight information, and the modified fuzzy GRA is applied to aggregate different types of evaluation information so as to identify the optimal candidate tenderers. Finally, a prototype system is built and validated with an illustrative example for GeT to confirm the feasibility of our approach. PMID:25057506

  2. A combination of extended fuzzy AHP and fuzzy GRA for government E-tendering in hybrid fuzzy environment.

    PubMed

    Wang, Yan; Xi, Chengyu; Zhang, Shuai; Yu, Dejian; Zhang, Wenyu; Li, Yong

    2014-01-01

    The recent government tendering process being conducted in an electronic way is becoming an inevitable affair for numerous governmental agencies to further exploit the superiorities of conventional tendering. Thus, developing an effective web-based bid evaluation methodology so as to realize an efficient and effective government E-tendering (GeT) system is imperative. This paper firstly investigates the potentiality of employing fuzzy analytic hierarchy process (AHP) along with fuzzy gray relational analysis (GRA) for optimal selection of candidate tenderers in GeT process with consideration of a hybrid fuzzy environment with incomplete weight information. We proposed a novel hybrid fuzzy AHP-GRA (HFAHP-GRA) method that combines an extended fuzzy AHP with a modified fuzzy GRA. The extended fuzzy AHP which combines typical AHP with interval AHP is proposed to obtain the exact weight information, and the modified fuzzy GRA is applied to aggregate different types of evaluation information so as to identify the optimal candidate tenderers. Finally, a prototype system is built and validated with an illustrative example for GeT to confirm the feasibility of our approach.

  3. 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.

  4. A review on classification methods for solving fully fuzzy linear systems

    NASA Astrophysics Data System (ADS)

    Daud, Wan Suhana Wan; Ahmad, Nazihah; Aziz, Khairu Azlan Abd

    2015-12-01

    Fully Fuzzy Linear System (FFLS) exists when there are fuzzy numbers on both sides of the linear systems. This system is quite significant today since most of the linear systems play with uncertainties of parameters especially in mathematics, engineering and finance. Many researchers and practitioners used the FFLS to model their problem and they apply various methods to solve it. In this paper, we present the outcome of a comprehensive review that we have done on various methods used for solving the FFLS. We classify our findings based on parameters' type used for the FFLS either restricted or unrestricted. We also discuss some of the methods by illustrating numerical examples and identify the differences between the methods. Ultimately, we summarize all findings in a table. We hope this study will encourage researchers to appreciate the use of this method and with that it will be easier for them to choose the right method or to propose any new method for solving the FFLS.

  5. 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.

  6. Fuzzy methods in decision making process - A particular approach in manufacturing systems

    NASA Astrophysics Data System (ADS)

    Coroiu, A. M.

    2015-11-01

    We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk

  7. Ontology Development for Patient Education Documents Using a Professional- and Patient-Oriented Delphi Method.

    PubMed

    Heimonen, Juho; Danielsson-Ojala, Riitta; Salakoski, Tapio; Lundgrén-Laine, Heljä; Salanterä, Sanna

    2018-04-12

    Written patient education materials are essential to motivate and help patients to participate in their own care, but the production and management of a large collection of high-quality and easily accessible patient education documents can be challenging. Ontologies can aid in these tasks, but the existing resources are not directly applicable to patient education. An ontology that models patient education documents and their readers was constructed. The Delphi method was used to identify a compact but sufficient set of entities with which the topics of documents may be described. The preferred terms of the entities were also considered to ensure their understandability. In the ontology, readers may be characterized by gender, age group, language, and role (patient or professional), whereas documents may be characterized by audience, topic(s), and content, as well as the time and place of use. The Delphi method yielded 265 unique document topics that are organized into seven hierarchies. Advantages and disadvantages of the ontology design, as well as possibilities for improvements, were identified. The patient education material ontology can enhance many applications, but further development is needed to reach its full potential.

  8. 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

  9. 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.

  10. Evaluating the construct of triage acuity against a set of reference vignettes developed via modified Delphi method.

    PubMed

    Twomey, Michèle; Wallis, Lee A; Myers, Jonathan E

    2014-07-01

    To evaluate the construct of triage acuity as measured by the South African Triage Scale (SATS) against a set of reference vignettes. A modified Delphi method was used to develop a set of reference vignettes. Delphi participants completed a 2-round consensus-building process, and independently assigned triage acuity ratings to 100 written vignettes unaware of the ratings given by others. Triage acuity ratings were summarised for all vignettes, and only those that reached 80% consensus during round 2 were included in the reference set. Triage ratings for the reference vignettes given by two independent experts using the SATS were compared with the ratings given by the international Delphi panel. Measures of sensitivity, specificity, associated percentages for over-triage/under-triage were used to evaluate the construct of triage acuity (as measured by the SATS) by examining the association between the ratings by the two experts and the international panel. On completion of the Delphi process, 42 of the 100 vignettes reached 80% consensus on their acuity rating and made up the reference set. On average, over all acuity levels, sensitivity was 74% (CI 64% to 82%), specificity 92% (CI 87% to 94%), under-triage occurred 14% (CI 8% to 23%) and over-triage 12% (CI 8% to 23%) of the time. The results of this study provide an alternative to evaluating triage scales against the construct of acuity as measured with the SATS. This method of using 80% consensus vignettes may, however, systematically bias the validity estimate towards better performance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  11. 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.

  12. 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.

  13. The Accuracy Of Fuzzy Sugeno Method With Antropometry On Determination Natural Patient Status

    NASA Astrophysics Data System (ADS)

    Syahputra, Dinur; Tulus; Sawaluddin

    2017-12-01

    Anthropometry is one of the processes that can be used to assess nutritional status. In general anthropometry is defined as body size in terms of nutrition, then anthropometry is reviewed from various age levels and nutritional levels. Nutritional status is a description of the balance between nutritional intake with the needs of the body individually. Fuzzy logic is a logic that has a vagueness between right and wrong or between 0 and 1. Sugeno method is used because in the process of calculating nutritional status so far is still done by anthropometry. Currently information technology is growing in any aspect, one of them in the aspect of calculation with data taken from anthropometry. In this case the calculation can use the Fuzzy Sugeno Method, in order to know the great accuracy obtained. Then the results obtained using fuzzy sugeno integrated with anthropometry has an accuracy of 81.48%.

  14. 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.

  15. Personal Learning Environments and University Teacher Roles Explored Using Delphi

    ERIC Educational Resources Information Center

    Shaikh, Zaffar Ahmed; Khoja, Shakeel Ahmed

    2014-01-01

    This paper presents the results of research using an online Delphi method, which aimed to explore university teacher roles and readiness for learner-centred pedagogy, driven by personal learning environments (PLEs). Using a modified Policy Delphi technique, a group of researchers worked with 34 international experts who are university teachers by…

  16. 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.

  17. The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

    NASA Astrophysics Data System (ADS)

    Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

    2017-05-01

    The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

  18. Modelling Multi Hazard Mapping in Semarang City Using GIS-Fuzzy Method

    NASA Astrophysics Data System (ADS)

    Nugraha, A. L.; Awaluddin, M.; Sasmito, B.

    2018-02-01

    One important aspect of disaster mitigation planning is hazard mapping. Hazard mapping can provide spatial information on the distribution of locations that are threatened by disaster. Semarang City as the capital of Central Java Province is one of the cities with high natural disaster intensity. Frequent natural disasters Semarang city is tidal flood, floods, landslides, and droughts. Therefore, Semarang City needs spatial information by doing multi hazard mapping to support disaster mitigation planning in Semarang City. Multi Hazards map modelling can be derived from parameters such as slope maps, rainfall, land use, and soil types. This modelling is done by using GIS method with scoring and overlay technique. However, the accuracy of modelling would be better if the GIS method is combined with Fuzzy Logic techniques to provide a good classification in determining disaster threats. The Fuzzy-GIS method will build a multi hazards map of Semarang city can deliver results with good accuracy and with appropriate threat class spread so as to provide disaster information for disaster mitigation planning of Semarang city. from the multi-hazard modelling using GIS-Fuzzy can be known type of membership that has a good accuracy is the type of membership Gauss with RMSE of 0.404 the smallest of the other membership and VAF value of 72.909% of the largest of the other membership.

  19. An international survey and modified Delphi approach revealed numerous rapid review methods.

    PubMed

    Tricco, Andrea C; Zarin, Wasifa; Antony, Jesmin; Hutton, Brian; Moher, David; Sherifali, Diana; Straus, Sharon E

    2016-02-01

    To solicit experiences with and perceptions of rapid reviews from stakeholders, including researchers, policy makers, industry, journal editors, and health care providers. An international survey of rapid review producers and modified Delphi. Forty rapid review producers responded on our survey (63% response rate). Eighty-eight rapid reviews with 31 different names were reported. Rapid review commissioning organizations were predominantly government (78%) and health care (58%) organizations. Several rapid review approaches were identified, including updating the literature search of previous reviews (92%); limiting the search strategy by date of publication (88%); and having only one reviewer screen (85%), abstract data (84%), and assess the quality of studies (86%). The modified Delphi included input from 113 stakeholders on the rapid review approaches from the survey. Approach 1 (search limited by date and language; study selection by one reviewer only, and data abstraction and quality appraisal conducted by one reviewer and one verifier) was ranked the most feasible (72%, 81/113 responses), with the lowest perceived risk of bias (12%, 12/103); it also ranked second in timeliness (37%, 38/102) and fifth in comprehensiveness (5%, 5/100). Rapid reviews have many names and approaches, and some methods might be more desirable than others. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. 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.

  1. Three decision-making aids: brainstorming, nominal group, and Delphi technique.

    PubMed

    McMurray, A R

    1994-01-01

    The methods of brainstorming, Nominal Group Technique, and the Delphi technique can be important resources for nursing staff development educators who wish to expand their decision-making skills. Staff development educators may find opportunities to use these methods for such tasks as developing courses, setting departmental goals, and forecasting trends for planning purposes. Brainstorming, Nominal Group Technique, and the Delphi technique provide a structured format that helps increase the quantity and quality of participant responses.

  2. Using the Delphi Method for Selecting Effective Rehabilitation Practices for Case Study Research: Methods, Challenges, and Solutions and Implications for Future Research

    ERIC Educational Resources Information Center

    Fleming, Allison R.; Boeltzig-Brown, Heike; Foley, Susan M.

    2015-01-01

    Purpose: We describe a modified Delphi method used to select effective state vocational rehabilitation agency practices to prioritize rehabilitation services for individuals with most significant disabilities within the context of Order of Selection, an area where there is little known and published. Specifically, we describe how we applied the…

  3. 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.

  4. Defining the activities of publicness for Korea's public community hospitals using the Delphi method.

    PubMed

    Lee, Kunsei; Kim, Hyun Joo; You, Myoungsoon; Lee, Jin-Seok; Eun, Sang Jun; Jeong, Hyoseon; Ahn, Hye Mi; Lee, Jin Yong

    2017-03-01

    This study aims to identify which activities of a public community hospital (PHC) should be included in their definition of publicness and tries to achieve a consensus among experts using the Delphi method. We conduct 2 rounds of the Delphi process with 17 panel members using a developed draft of tentative activities for publicness including 5 main categories covering 27 items. The questions remain the same in both rounds and the applicability of each of the 27 items to publicness is measured on a 9-point scale. If the participants believe government funding is needed, we ask how much they think the government should support each item on a 0% to 100% scale. After conducting 2 rounds of the Delphi process, 22 out of the 27 items reached a consensus as activities defining the publicness of the PHCs. Among the 5 major categories, in category C, activities preventing market failure, all 10 items were considered activities of publicness. Nine of these were evaluated as items that should be compensated at 100% of total financial loss by the Korean government. Throughout results, we were able to define the activities of the PCH that encompassed its publicness and confirm that there are "good deficits" in the context of the PCHs. Thus, some PCH deficits are unavoidable and not wasted as these monies support a necessary role and function in providing public health. The Korean government should therefore consider taking actions such as exempting such "good deficits" or providing additional financial aid to reimburse the PHCs for "good deficits."

  5. 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.

  6. Evaluate E-loyalty of sales website: a Fuzzy mathematics method

    NASA Astrophysics Data System (ADS)

    Yi, Ying; Liu, Zhen-Yu; Xiong, Ying-Zi

    The study about online consumer loyalty is limited, but how to evaluate the customers' E-loyalty to a sales website is always a noticeable question. By using some methods of fuzzy mathematics, we provide a more accurate way to evaluate E-loyalty of sales website. Moreover, this method can differentiate level and degree of each factor that influences E-loyalty.

  7. A YinYang bipolar fuzzy cognitive TOPSIS method to bipolar disorder diagnosis.

    PubMed

    Han, Ying; Lu, Zhenyu; Du, Zhenguang; Luo, Qi; Chen, Sheng

    2018-05-01

    Bipolar disorder is often mis-diagnosed as unipolar depression in the clinical diagnosis. The main reason is that, different from other diseases, bipolarity is the norm rather than exception in bipolar disorder diagnosis. YinYang bipolar fuzzy set captures bipolarity and has been successfully used to construct a unified inference mathematical modeling method to bipolar disorder clinical diagnosis. Nevertheless, symptoms and their interrelationships are not considered in the existing method, circumventing its ability to describe complexity of bipolar disorder. Thus, in this paper, a YinYang bipolar fuzzy multi-criteria group decision making method to bipolar disorder clinical diagnosis is developed. Comparing with the existing method, the new one is more comprehensive. The merits of the new method are listed as follows: First of all, multi-criteria group decision making method is introduced into bipolar disorder diagnosis for considering different symptoms and multiple doctors' opinions. Secondly, the discreet diagnosis principle is adopted by the revised TOPSIS method. Last but not the least, YinYang bipolar fuzzy cognitive map is provided for the understanding of interrelations among symptoms. The illustrated case demonstrates the feasibility, validity, and necessity of the theoretical results obtained. Moreover, the comparison analysis demonstrates that the diagnosis result is more accurate, when interrelations about symptoms are considered in the proposed method. In a conclusion, the main contribution of this paper is to provide a comprehensive mathematical approach to improve the accuracy of bipolar disorder clinical diagnosis, in which both bipolarity and complexity are considered. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. 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.

  9. Career and Technical Education at a Crossroads: A Delphi Study

    ERIC Educational Resources Information Center

    Cutright, Michael W.

    2011-01-01

    Career and technical education in the United States has reached a critical juncture. A three round Delphi method was used to determine a consensus on the future events of career and technical education to better inform educational decision makers. Forty-one individual experts in the field were invited to serve as panelists for the Delphi study and…

  10. A Simplified Version of the Fuzzy Decision Method and its Comparison with the Paraconsistent Decision Method

    NASA Astrophysics Data System (ADS)

    de Carvalho, Fábio Romeu; Abe, Jair Minoro

    2010-11-01

    Two recent non-classical logics have been used to make decision: fuzzy logic and paraconsistent annotated evidential logic Et. In this paper we present a simplified version of the fuzzy decision method and its comparison with the paraconsistent one. Paraconsistent annotated evidential logic Et, introduced by Da Costa, Vago and Subrahmanian (1991), is capable of handling uncertain and contradictory data without becoming trivial. It has been used in many applications such as information technology, robotics, artificial intelligence, production engineering, decision making etc. Intuitively, one Et logic formula is type p(a, b), in which a and b belong to [0, 1] (real interval) and represent respectively the degree of favorable evidence (or degree of belief) and the degree of contrary evidence (or degree of disbelief) found in p. The set of all pairs (a; b), called annotations, when plotted, form the Cartesian Unitary Square (CUS). This set, containing a similar order relation of real number, comprises a network, called lattice of the annotations. Fuzzy logic was introduced by Zadeh (1965). It tries to systematize the knowledge study, searching mainly to study the fuzzy knowledge (you don't know what it means) and distinguish it from the imprecise one (you know what it means, but you don't know its exact value). This logic is similar to paraconsistent annotated one, since it attributes a numeric value (only one, not two values) to each proposition (then we can say that it is an one-valued logic). This number translates the intensity (the degree) with which the preposition is true. Let's X a set and A, a subset of X, identified by the function f(x). For each element x∈X, you have y = f(x)∈[0, 1]. The number y is called degree of pertinence of x in A. Decision making theories based on these logics have shown to be powerful in many aspects regarding more traditional methods, like the one based on Statistics. In this paper we present a first study for a simplified

  11. Fuzzy Neuron: Method and Hardware Realization

    NASA Technical Reports Server (NTRS)

    Krasowski, Michael J.; Prokop, Norman F.

    2014-01-01

    This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.

  12. 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.

  13. Setting Priorities for Gerontological Social Work Research: A National Delphi Study

    ERIC Educational Resources Information Center

    Burnette, Denise; Morrow-Howell, Nancy; Chen, Li-Mei

    2003-01-01

    Purpose: An increasingly important task for all disciplines involved in aging research is to identify and prioritize areas for investigation. This article reports the results of a national Delphi study on setting research priorities for gerontological social work. Design and Methods: Delphi methodology, a structured process for eliciting and…

  14. Experience of Delphi technique in the process of establishing consensus on core competencies.

    PubMed

    Raghav, Pankaja Ravi; Kumar, Dewesh; Bhardwaj, Pankaj

    2016-01-01

    The Department of Community Medicine and Family Medicine (CMFM) has been started as a new model for imparting the components of family medicine and delivering health-care services at primary and secondary levels in all six newly established All India Institute of Medical Sciences (AIIMS), but there is no competency-based curriculum for it. The paper aims to share the experience of Delphi method in the process of developing consensus on core competencies of the new model of CMFM in AIIMS for undergraduate medical students in India. The study adopted different approaches and methods, but Delphi was the most critical method used in this research. In Delphi, the experts were contacted by e-mail and their feedback on the same was analyzed. Two rounds of Delphi were conducted in which 150 participants were contacted in Delphi-I but only 46 responded. In Delphi-II, 26 participants responded whose responses were finally considered for analysis. Three of the core competencies namely clinician, primary-care physician, and professionalism were agreed by all the participants, and the least agreement was observed in the competencies of epidemiologist and medical teacher. The experts having more experience were less consistent as responses were changed from agree to disagree in more than 15% of participants and 6% changed from disagree to agree. Within the given constraints, the final list of competencies and skills for the discipline of CMFM compiled after the Delphi process will provide a useful insight into the development of competency-based curriculum of the subject.

  15. Internet-Based Delphi Research: Case Based Discussion

    PubMed Central

    Donohoe, Holly M.; Stellefson, Michael L.

    2013-01-01

    The interactive capacity of the Internet offers benefits that are intimately linked with contemporary research innovation in the natural resource and environmental studies domains. However, e-research methodologies, such as the e-Delphi technique, have yet to undergo critical review. This study advances methodological discourse on the e-Delphi technique by critically assessing an e-Delphi case study. The analysis suggests that the benefits of using e-Delphi are noteworthy but the authors acknowledge that researchers are likely to face challenges that could potentially compromise research validity and reliability. To ensure that these issues are sufficiently considered when planning and designing an e-Delphi, important facets of the technique are discussed and recommendations are offered to help the environmental researcher avoid potential pitfalls associated with coordinating e-Delphi research. PMID:23288149

  16. Key Features of Academic Detailing: Development of an Expert Consensus Using the Delphi Method.

    PubMed

    Yeh, James S; Van Hoof, Thomas J; Fischer, Michael A

    2016-02-01

    Academic detailing is an outreach education technique that combines the direct social marketing traditionally used by pharmaceutical representatives with unbiased content summarizing the best evidence for a given clinical issue. Academic detailing is conducted with clinicians to encourage evidence-based practice in order to improve the quality of care and patient outcomes. The adoption of academic detailing has increased substantially since the original studies in the 1980s. However, the lack of standard agreement on its implementation makes the evaluation of academic detailing outcomes challenging. To identify consensus on the key elements of academic detailing among a group of experts with varying experiences in academic detailing. This study is based on an online survey of 20 experts with experience in academic detailing. We used the Delphi process, an iterative and systematic method of developing consensus within a group. We conducted 3 rounds of online surveys, which addressed 72 individual items derived from a previous literature review of 5 features of academic detailing, including (1) content, (2) communication process, (3) clinicians targeted, (4) change agents delivering intervention, and (5) context for intervention. Nonrespondents were removed from later rounds of the surveys. For most questions, a 4-point ordinal scale was used for responses. We defined consensus agreement as 70% of respondents for a single rating category or 80% for dichotomized ratings. The overall survey response rate was 95% (54 of 57 surveys) and nearly 92% consensus agreement on the survey items (66 of 72 items) by the end of the Delphi exercise. The experts' responses suggested that (1) focused clinician education offering support for clinical decision-making is a key component of academic detailing, (2) detailing messages need to be tailored and provide feasible strategies and solutions to challenging cases, and (3) academic detailers need to develop specific skill sets

  17. 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.

  18. Evaluating water management strategies in watersheds by new hybrid Fuzzy Analytical Network Process (FANP) methods

    NASA Astrophysics Data System (ADS)

    RazaviToosi, S. L.; Samani, J. M. V.

    2016-03-01

    Watersheds are considered as hydrological units. Their other important aspects such as economic, social and environmental functions play crucial roles in sustainable development. The objective of this work is to develop methodologies to prioritize watersheds by considering different development strategies in environmental, social and economic sectors. This ranking could play a significant role in management to assign the most critical watersheds where by employing water management strategies, best condition changes are expected to be accomplished. Due to complex relations among different criteria, two new hybrid fuzzy ANP (Analytical Network Process) algorithms, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy max-min set methods are used to provide more flexible and accurate decision model. Five watersheds in Iran named Oroomeyeh, Atrak, Sefidrood, Namak and Zayandehrood are considered as alternatives. Based on long term development goals, 38 water management strategies are defined as subcriteria in 10 clusters. The main advantage of the proposed methods is its ability to overcome uncertainty. This task is accomplished by using fuzzy numbers in all steps of the algorithms. To validate the proposed method, the final results were compared with those obtained from the ANP algorithm and the Spearman rank correlation coefficient is applied to find the similarity in the different ranking methods. Finally, the sensitivity analysis was conducted to investigate the influence of cluster weights on the final ranking.

  19. Defect inspection in hot slab surface: multi-source CCD imaging based fuzzy-rough sets method

    NASA Astrophysics Data System (ADS)

    Zhao, Liming; Zhang, Yi; Xu, Xiaodong; Xiao, Hong; Huang, Chao

    2016-09-01

    To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.

  20. 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.

  1. 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

  2. Application of Delphi expert panel in joint venture projects

    NASA Astrophysics Data System (ADS)

    Adnan, H.; Rosman, M. R.; Rashid, Z. Z. Ahmad; Mohamad Yusuwan, N.; Bakhary, N. A.

    2018-02-01

    This study was conducted with the aim to identify the application of the Delphi Technique in validating findings obtained from questionnaire surveys and interviews done in- depth on the subject of joint venture projects in Malaysia. The Delphi technique aims to achieve a consensus of opinion amongst expert panellist that were selected on the primary factors in JV projects. To achieve research objectives, a progressive series of questions was designed where a selected panel of expert to confirm and validate the final findings. The rationale, benefits, limitations and recommendations for the use of Delphi were given in this study. From the literature review done, twenty-one factors were identified as critical factors to the making any joint venture project successful. Detail information from contractors were obtained by using the questionnaire survey method and forty-three in-depth interviews were carried out. Trust between partners, mutual understanding, partner selection criteria, agreement of contract, objective compatibility, conflict, and commitment were confirmed by the Delphi panel to be the critical success factors besides another fourteen factors which were found to be the Failure Reduction Criteria. Delphi techniques has proven to successfully assist in recognising the main factors and would be beneficial in supplementing the success of joint venture arrangements application for construction projects in Malaysia.

  3. Malaria chemoprophylaxis recommendations for immigrants to Europe, visiting relatives and friends - a Delphi method study

    PubMed Central

    2011-01-01

    Background Numbers of travellers visiting friends and relatives (VFRs) from Europe to malaria endemic countries are increasing and include long-term and second generation immigrants, who represent the major burden of malaria cases imported back into Europe. Most recommendations for malaria chemoprophylaxis lack a solid evidence base, and often fail to address the cultural, social and economic needs of VFRs. Methods European travel medicine experts, who are members of TropNetEurop, completed a sequential series of questionnaires according to the Delphi method. This technique aims at evaluating and developing a consensus through repeated iterations of questionnaires. The questionnaires in this study included questions about professional experience with VFRs, controversial issues in malaria prophylaxis, and 16 scenarios exploring indications for prescribing and choice of chemoprophylaxis. Results The experience of participants was rather diverse as was their selection of chemoprophylaxis regimen. A significant consensus was observed in only seven of 16 scenarios. The analysis revealed a wide variation in prescribing choices with preferences grouped by region of practice and increased prescribing seen in Northern Europe compared to Central Europe. Conclusions Improving the evidence base on efficacy, adherence to chemoprophylaxis and risk of malaria and encouraging discussion among experts, using techniques such as the Delphi method, may reduce the variability in prescription in European travel clinics. PMID:21599909

  4. Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

    PubMed

    de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2017-01-01

    Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

  5. Preliminary identification of key clinical domains for outcome evaluation in fibromyalgia using the Delphi method: the Italian experience.

    PubMed

    Salaffi, F; Ciapetti, A; Sarzi Puttini, P; Atzeni, F; Iannuccelli, C; Di Franco, M; Cazzola, M; Bazzichi, L

    2012-03-19

    Fibromyalgia (FM) is a complex syndrome that, in Italy, affects at least 2% of the adult population. It is characterized by chronic widespread musculoskeletal pain often accompanied by multiple other symptoms. The aim of this study was to identify a set of clinical domains for FM considered relevant by both clinicians and patients using a consensus process. Consensus was achieved using the Delphi method based on questionnaires and systematic, controlled opinion feedback. The Delphi exercise involved a panel of 252 rheumatologists and 86 patients with FM as defined by the American College of Rheumatology criteria. All of the patients and clinicians were asked to rank the relative different domains of FM in order of priority. The content validity index (CVI) was used to establish the percentage agreement. The importance of each item was ranked on a 0-3 Likert scale. The frequency, mean relevance scores, and frequency importance product were also calculated. The Delphi exercise showed that the domains ranked highest by patients were similar to those of the clinicians, with the exception of tender point intensity (considered relevant by the clinicians but not by the patients) and environmental sensitivity (considered important by the patients but not by the clinicians). A final 8-item model was developed which was considered to demonstrate adequate validity. The Delphi exercises identified and ranked relevant key clinical domains that need to be assessed in FM research. On the basis of these results, a new patient-reported composite outcome index can be developed and used in clinical trials.

  6. MRI brain tumor segmentation based on improved fuzzy c-means method

    NASA Astrophysics Data System (ADS)

    Deng, Wankai; Xiao, Wei; Pan, Chao; Liu, Jianguo

    2009-10-01

    This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective.

  7. Evaluation of Nine Consensus Indices in Delphi Foresight Research and Their Dependency on Delphi Survey Characteristics: A Simulation Study and Debate on Delphi Design and Interpretation.

    PubMed

    Birko, Stanislav; Dove, Edward S; Özdemir, Vural

    2015-01-01

    The extent of consensus (or the lack thereof) among experts in emerging fields of innovation can serve as antecedents of scientific, societal, investor and stakeholder synergy or conflict. Naturally, how we measure consensus is of great importance to science and technology strategic foresight. The Delphi methodology is a widely used anonymous survey technique to evaluate consensus among a panel of experts. Surprisingly, there is little guidance on how indices of consensus can be influenced by parameters of the Delphi survey itself. We simulated a classic three-round Delphi survey building on the concept of clustered consensus/dissensus. We evaluated three study characteristics that are pertinent for design of Delphi foresight research: (1) the number of survey questions, (2) the sample size, and (3) the extent to which experts conform to group opinion (the Group Conformity Index) in a Delphi study. Their impacts on the following nine Delphi consensus indices were then examined in 1000 simulations: Clustered Mode, Clustered Pairwise Agreement, Conger's Kappa, De Moivre index, Extremities Version of the Clustered Pairwise Agreement, Fleiss' Kappa, Mode, the Interquartile Range and Pairwise Agreement. The dependency of a consensus index on the Delphi survey characteristics was expressed from 0.000 (no dependency) to 1.000 (full dependency). The number of questions (range: 6 to 40) in a survey did not have a notable impact whereby the dependency values remained below 0.030. The variation in sample size (range: 6 to 50) displayed the top three impacts for the Interquartile Range, the Clustered Mode and the Mode (dependency = 0.396, 0.130, 0.116, respectively). The Group Conformity Index, a construct akin to measuring stubbornness/flexibility of experts' opinions, greatly impacted all nine Delphi consensus indices (dependency = 0.200 to 0.504), except the Extremity CPWA and the Interquartile Range that were impacted only beyond the first decimal point (dependency = 0

  8. Evaluation of Nine Consensus Indices in Delphi Foresight Research and Their Dependency on Delphi Survey Characteristics: A Simulation Study and Debate on Delphi Design and Interpretation

    PubMed Central

    Birko, Stanislav; Dove, Edward S.; Özdemir, Vural

    2015-01-01

    The extent of consensus (or the lack thereof) among experts in emerging fields of innovation can serve as antecedents of scientific, societal, investor and stakeholder synergy or conflict. Naturally, how we measure consensus is of great importance to science and technology strategic foresight. The Delphi methodology is a widely used anonymous survey technique to evaluate consensus among a panel of experts. Surprisingly, there is little guidance on how indices of consensus can be influenced by parameters of the Delphi survey itself. We simulated a classic three-round Delphi survey building on the concept of clustered consensus/dissensus. We evaluated three study characteristics that are pertinent for design of Delphi foresight research: (1) the number of survey questions, (2) the sample size, and (3) the extent to which experts conform to group opinion (the Group Conformity Index) in a Delphi study. Their impacts on the following nine Delphi consensus indices were then examined in 1000 simulations: Clustered Mode, Clustered Pairwise Agreement, Conger’s Kappa, De Moivre index, Extremities Version of the Clustered Pairwise Agreement, Fleiss’ Kappa, Mode, the Interquartile Range and Pairwise Agreement. The dependency of a consensus index on the Delphi survey characteristics was expressed from 0.000 (no dependency) to 1.000 (full dependency). The number of questions (range: 6 to 40) in a survey did not have a notable impact whereby the dependency values remained below 0.030. The variation in sample size (range: 6 to 50) displayed the top three impacts for the Interquartile Range, the Clustered Mode and the Mode (dependency = 0.396, 0.130, 0.116, respectively). The Group Conformity Index, a construct akin to measuring stubbornness/flexibility of experts’ opinions, greatly impacted all nine Delphi consensus indices (dependency = 0.200 to 0.504), except the Extremity CPWA and the Interquartile Range that were impacted only beyond the first decimal point (dependency

  9. Solving Fuzzy Optimization Problem Using Hybrid Ls-Sa Method

    NASA Astrophysics Data System (ADS)

    Vasant, Pandian

    2011-06-01

    Fuzzy optimization problem has been one of the most and prominent topics inside the broad area of computational intelligent. It's especially relevant in the filed of fuzzy non-linear programming. It's application as well as practical realization can been seen in all the real world problems. In this paper a large scale non-linear fuzzy programming problem has been solved by hybrid optimization techniques of Line Search (LS), Simulated Annealing (SA) and Pattern Search (PS). As industrial production planning problem with cubic objective function, 8 decision variables and 29 constraints has been solved successfully using LS-SA-PS hybrid optimization techniques. The computational results for the objective function respect to vagueness factor and level of satisfaction has been provided in the form of 2D and 3D plots. The outcome is very promising and strongly suggests that the hybrid LS-SA-PS algorithm is very efficient and productive in solving the large scale non-linear fuzzy programming problem.

  10. [The application of Delphi method in improving the score table for the hygienic quantifying and classification of hotels].

    PubMed

    Wang, Zi-yun; Liu, Yong-quan; Wang, Hong-bo; Zheng, Yang; Wu, Qi; Yang, Xia; Wu, Yong-wei; Zhao, Yi-ming

    2009-04-01

    By means of Delphi method and expert panel consultations, to choose suitable indicators and improve the score table for classifying the hygienic condition of hotels so that it can be widely used at nationwide. A two-round Delphi consultation was held to choose suitable indicators among 78 experts from 18 provinces, municipalities and autonomous regions. The suitable indicators were selected according to the importance recognized by experts. The average length of service in public health of the experts was (21.08 +/- 5.78) years and the average coefficient of experts' authorities C(r) was 0.89 +/- 0.07. The response rates of the two-round consultation were 98.72% (77/78) and 100.00% (77/77). The average feedback time were (8.49 +/- 4.48) d, (5.86 +/- 2.28) d, and the difference between two rounds was statistically significant (t = 4.60, P < 0.01). Kendall's coefficient were 0.26 (chi(2) = 723.63, P < 0.01), 0.32 (chi(2) = 635.65, P < 0.01) and opinions among experts became consistent. The score table for the hygienic quantifying and classification of hotels was composed of three first-class indicators (hygienic management, hygienic facilities and hygienic practices) and 36 second-class indicators. The weight coefficients of the three first-class indicators were 0.35, 0.34, 0.31. Delphi method might be used in a large-scale consultation among experts and be propitious to improve the score table for the hygienic quantifying and classification.

  11. 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.

  12. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

    PubMed Central

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

  13. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

    PubMed

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

    2016-09-09

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

  14. Applications of fuzzy ranking methods to risk-management decisions

    NASA Astrophysics Data System (ADS)

    Mitchell, Harold A.; Carter, James C., III

    1993-12-01

    The Department of Energy is making significant improvements to its nuclear facilities as a result of more stringent regulation, internal audits, and recommendations from external review groups. A large backlog of upgrades has resulted. Currently, a prioritization method is being utilized which relies on a matrix of potential consequence and probability of occurrence. The attributes of the potential consequences considered include likelihood, exposure, public health and safety, environmental impact, site personnel safety, public relations, legal liability, and business loss. This paper describes an improved method which utilizes fuzzy multiple attribute decision methods to rank proposed improvement projects.

  15. An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation.

    PubMed

    Hayati, Elyas; Majnounian, Baris; Abdi, Ehsan; Sessions, John; Makhdoum, Majid

    2013-02-01

    Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.

  16. Assessment of critical thinking: a Delphi study.

    PubMed

    Paul, Sheila A

    2014-11-01

    Nurse educators are responsible for preparing nurses who critically analyze patient information and provide meaningful interventions in today's complex health care system. By using the Delphi research method, this study, utilized the specialized and experiential knowledge of Certified Nurse Educators. This original Delphi research study asked Certified Nurse Educators how to assess the critical-thinking ability of nursing students in the clinical setting. The results showed that nurse educators need time, during the clinical experience, to accurately assess each individual nursing student. This study demonstrated the need for extended student clinical time, and a variety of clinical learning assessment tools. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Military Medical Leadership in Uniformed Medical Students: Creating a New Assessment Instrument Using the Delphi Method

    DTIC Science & Technology

    2015-12-17

    healthcare management and have not focused on assessing leadership among student physicians. A systematic review of 80 Delphi method studies by...medical students ( Research Question 1), to create a leadership assessment instrument based on those important components ( Research Question 2), and... research question 2 (RQ2) saw the creation of a three page assessment instrument to assess medical leadership in student physicians. Based on critical

  18. 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

  19. Distribution network connection pricing framework and methodology: identification of areas of improvement for Sarawak Energy Berhad Connection Charges Guidelines through modified delphi method

    NASA Astrophysics Data System (ADS)

    Tan, J. K.; Abas, N.

    2017-07-01

    Complaints on issues and matters related to connection charges have been very common for electricity supply utility companies around the world including Sarawak Energy Berhad. In order to identify the areas that can be improved, a mixed method of exploratory research involving qualitative and quantitative methods have been designed and undertaken rather than a single method of survey. This will ensure a more comprehensive and detailed understanding of the issues from various target groups. The method is designed under three phases, employing Modified Delphi Technique for phase 1 through a series of stake holder engagements, online and offline survey questionnaires to be filled by internal wiring contractors for phase 2 whilst under phase 3, case studies shall be carried out on the issues identified from phase 1 and phase 2 of the study. This paper presented the findings from the Modified Delphi Technique. The findings revealed that there are areas of improvement for Sarawak Energy Berhad connection guidelines in term of differentiation of dedicated and shared assets which leads to unfairness to the connecting customers, inconsistency and non-transparent in charging. The findings of Modified Delphi Technique shall be used for implementation of phase 2 and phase 3 of the study.

  20. Zero point and zero suffix methods with robust ranking for solving fully fuzzy transportation problems

    NASA Astrophysics Data System (ADS)

    Ngastiti, P. T. B.; Surarso, Bayu; Sutimin

    2018-05-01

    Transportation issue of the distribution problem such as the commodity or goods from the supply tothe demmand is to minimize the transportation costs. Fuzzy transportation problem is an issue in which the transport costs, supply and demand are in the form of fuzzy quantities. Inthe case study at CV. Bintang Anugerah Elektrik, a company engages in the manufacture of gensets that has more than one distributors. We use the methods of zero point and zero suffix to investigate the transportation minimum cost. In implementing both methods, we use robust ranking techniques for the defuzzification process. The studyresult show that the iteration of zero suffix method is less than that of zero point method.

  1. Empirical research in service engineering based on AHP and fuzzy methods

    NASA Astrophysics Data System (ADS)

    Zhang, Yanrui; Cao, Wenfu; Zhang, Lina

    2015-12-01

    Recent years, management consulting industry has been rapidly developing worldwide. Taking a big management consulting company as research object, this paper established an index system of service quality of consulting, based on customer satisfaction survey, evaluated service quality of the consulting company by AHP and fuzzy comprehensive evaluation methods.

  2. Finger-Vein Image Enhancement Using a Fuzzy-Based Fusion Method with Gabor and Retinex Filtering

    PubMed Central

    Shin, Kwang Yong; Park, Young Ho; Nguyen, Dat Tien; Park, Kang Ryoung

    2014-01-01

    Because of the advantages of finger-vein recognition systems such as live detection and usage as bio-cryptography systems, they can be used to authenticate individual people. However, images of finger-vein patterns are typically unclear because of light scattering by the skin, optical blurring, and motion blurring, which can degrade the performance of finger-vein recognition systems. In response to these issues, a new enhancement method for finger-vein images is proposed. Our method is novel compared with previous approaches in four respects. First, the local and global features of the vein lines of an input image are amplified using Gabor filters in four directions and Retinex filtering, respectively. Second, the means and standard deviations in the local windows of the images produced after Gabor and Retinex filtering are used as inputs for the fuzzy rule and fuzzy membership function, respectively. Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method. Fourth, the use of a fuzzy-based method means that image enhancement does not require additional training data to determine the optimal weights. Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods. PMID:24549251

  3. Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

    PubMed Central

    Diao, Yuzhu; Hu, Aqin

    2018-01-01

    Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

  4. Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

    PubMed

    Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

    2018-03-02

    Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

  5. Fuzzy Multicriteria Ranking of Aluminium Coating Methods

    NASA Astrophysics Data System (ADS)

    Batzias, A. F.

    2007-12-01

    This work deals with multicriteria ranking of aluminium coating methods. The alternatives used are: sulfuric acid anodization, A1; oxalic acid anodization, A2; chromic acid anodization, A3; phosphoric acid anodization, A4; integral color anodizing, A5; chemical conversion coating, A6; electrostatic powder deposition, A7. The criteria used are: cost of production, f1; environmental friendliness of production process, f2; appearance (texture), f3; reflectivity, f4; response to coloring, f5; corrosion resistance, f6; abrasion resistance, f7; fatigue resistance, f8. Five experts coming from relevant industrial units set grades to the criteria vector and the preference matrix according to a properly modified Delphi method. Sensitivity analysis of the ranked first alternative A1 against the `second best', which was A3 at low and A7 at high resolution levels proved that the solution is robust. The dependence of anodized products quality on upstream processes is presented and the impact of energy price increase on industrial cost is discussed.

  6. Fuzzy feature selection based on interval type-2 fuzzy sets

    NASA Astrophysics Data System (ADS)

    Cherif, Sahar; Baklouti, Nesrine; Alimi, Adel; Snasel, Vaclav

    2017-03-01

    When dealing with real world data; noise, complexity, dimensionality, uncertainty and irrelevance can lead to low performance and insignificant judgment. Fuzzy logic is a powerful tool for controlling conflicting attributes which can have similar effects and close meanings. In this paper, an interval type-2 fuzzy feature selection is presented as a new approach for removing irrelevant features and reducing complexity. We demonstrate how can Feature Selection be joined with Interval Type-2 Fuzzy Logic for keeping significant features and hence reducing time complexity. The proposed method is compared with some other approaches. The results show that the number of attributes is proportionally small.

  7. 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.

  8. 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.

  9. Construction safety monitoring based on the project's characteristic with fuzzy logic approach

    NASA Astrophysics Data System (ADS)

    Winanda, Lila Ayu Ratna; Adi, Trijoko Wahyu; Anwar, Nadjadji; Wahyuni, Febriana Santi

    2017-11-01

    Construction workers accident is the highest number compared with other industries and falls are the main cause of fatal and serious injuries in high rise projects. Generally, construction workers accidents are caused by unsafe act and unsafe condition that can occur separately or together, thus a safety monitoring system based on influencing factors is needed to achieve zero accident in construction industry. The dynamic characteristic in construction causes high mobility for workers while doing the task, so it requires a continuously monitoring system to detect unsafe condition and to protect workers from potential hazards. In accordance with the unique nature of project, fuzzy logic approach is one of the appropriate methods for workers safety monitoring on site. In this study, the focus of discussion is based on the characteristic of construction projects in analyzing "potential hazard" and the "protection planning" to be used in accident prevention. The data have been collected from literature review, expert opinion and institution of safety and health. This data used to determine hazard identification. Then, an application model is created using Delphi programming. The process in fuzzy is divided into fuzzification, inference and defuzzification, according to the data collection. Then, the input and final output data are given back to the expert for assessment as a validation of application model. The result of the study showed that the potential hazard of construction workers accident could be analysed based on characteristic of project and protection system on site and fuzzy logic approach can be used for construction workers accident analysis. Based on case study and the feedback assessment from expert, it showed that the application model can be used as one of the safety monitoring tools.

  10. 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.

  11. A Comparison of Neural Networks and Fuzzy Logic Methods for Process Modeling

    NASA Technical Reports Server (NTRS)

    Cios, Krzysztof J.; Sala, Dorel M.; Berke, Laszlo

    1996-01-01

    The goal of this work was to analyze the potential of neural networks and fuzzy logic methods to develop approximate response surfaces as process modeling, that is for mapping of input into output. Structural response was chosen as an example. Each of the many methods surveyed are explained and the results are presented. Future research directions are also discussed.

  12. Metadata-driven Delphi rating on the Internet.

    PubMed

    Deshpande, Aniruddha M; Shiffman, Richard N; Nadkarni, Prakash M

    2005-01-01

    Paper-based data collection and analysis for consensus development is inefficient and error-prone. Computerized techniques that could improve efficiency, however, have been criticized as costly, inconvenient and difficult to use. We designed and implemented a metadata-driven Web-based Delphi rating and analysis tool, employing the flexible entity-attribute-value schema to create generic, reusable software. The software can be applied to various domains by altering the metadata; the programming code remains intact. This approach greatly reduces the marginal cost of re-using the software. We implemented our software to prepare for the Conference on Guidelines Standardization. Twenty-three invited experts completed the first round of the Delphi rating on the Web. For each participant, the software generated individualized reports that described the median rating and the disagreement index (calculated from the Interpercentile Range Adjusted for Symmetry) as defined by the RAND/UCLA Appropriateness Method. We evaluated the software with a satisfaction survey using a five-level Likert scale. The panelists felt that Web data entry was convenient (median 4, interquartile range [IQR] 4.0-5.0), acceptable (median 4.5, IQR 4.0-5.0) and easily accessible (median 5, IQR 4.0-5.0). We conclude that Web-based Delphi rating for consensus development is a convenient and acceptable alternative to the traditional paper-based method.

  13. Fuzzy method for pre-diagnosis of breast cancer from the Fine Needle Aspirate analysis

    PubMed Central

    2012-01-01

    Background Across the globe, breast cancer is one of the leading causes of death among women and, currently, Fine Needle Aspirate (FNA) with visual interpretation is the easiest and fastest biopsy technique for the diagnosis of this deadly disease. Unfortunately, the ability of this method to diagnose cancer correctly when the disease is present varies greatly, from 65% to 98%. This article introduces a method to assist in the diagnosis and second opinion of breast cancer from the analysis of descriptors extracted from smears of breast mass obtained by FNA, with the use of computational intelligence resources - in this case, fuzzy logic. Methods For data acquisition of FNA, the Wisconsin Diagnostic Breast Cancer Data (WDBC), from the University of California at Irvine (UCI) Machine Learning Repository, available on the internet through the UCI domain was used. The knowledge acquisition process was carried out by the extraction and analysis of numerical data of the WDBC and by interviews and discussions with medical experts. The PDM-FNA-Fuzzy was developed in four steps: 1) Fuzzification Stage; 2) Rules Base; 3) Inference Stage; and 4) Defuzzification Stage. Performance cross-validation was used in the tests, with three databases with gold pattern clinical cases randomly extracted from the WDBC. The final validation was held by medical specialists in pathology, mastology and general practice, and with gold pattern clinical cases, i.e. with known and clinically confirmed diagnosis. Results The Fuzzy Method developed provides breast cancer pre-diagnosis with 98.59% sensitivity (correct pre-diagnosis of malignancies); and 85.43% specificity (correct pre-diagnosis of benign cases). Due to the high sensitivity presented, these results are considered satisfactory, both by the opinion of medical specialists in the aforementioned areas and by comparison with other studies involving breast cancer diagnosis using FNA. Conclusions This paper presents an intelligent method to

  14. Gadamerian philosophical hermeneutics as a useful methodological framework for the Delphi technique.

    PubMed

    Guzys, Diana; Dickson-Swift, Virginia; Kenny, Amanda; Threlkeld, Guinever

    2015-01-01

    In this article we aim to demonstrate how Gadamerian philosophical hermeneutics may provide a sound methodological framework for researchers using the Delphi Technique (Delphi) in studies exploring health and well-being. Reporting of the use of Delphi in health and well-being research is increasing, but less attention has been given to covering its methodological underpinnings. In Delphi, a structured anonymous conversation between participants is facilitated, via an iterative survey process. Participants are specifically selected for their knowledge and experience with the topic of interest. The purpose of structuring conversation in this manner is to cultivate collective opinion and highlight areas of disagreement, using a process that minimizes the influence of group dynamics. The underlying premise is that the opinion of a collective is more useful than that of an individual. In designing our study into health literacy, Delphi aligned well with our research focus and would enable us to capture collective views. However, we were interested in the methodology that would inform our study. As researchers, we believe that methodology provides the framework and principles for a study and is integral to research integrity. In assessing the suitability of Delphi for our research purpose, we found little information about underpinning methodology. The absence of a universally recognized or consistent methodology associated with Delphi was highlighted through a scoping review we undertook to assist us in our methodological thinking. This led us to consider alternative methodologies, which might be congruent with the key principles of Delphi. We identified Gadamerian philosophical hermeneutics as a methodology that could provide a supportive framework and principles. We suggest that this methodology may be useful in health and well-being studies utilizing the Delphi method.

  15. Gadamerian philosophical hermeneutics as a useful methodological framework for the Delphi technique

    PubMed Central

    Guzys, Diana; Dickson-Swift, Virginia; Kenny, Amanda; Threlkeld, Guinever

    2015-01-01

    In this article we aim to demonstrate how Gadamerian philosophical hermeneutics may provide a sound methodological framework for researchers using the Delphi Technique (Delphi) in studies exploring health and well-being. Reporting of the use of Delphi in health and well-being research is increasing, but less attention has been given to covering its methodological underpinnings. In Delphi, a structured anonymous conversation between participants is facilitated, via an iterative survey process. Participants are specifically selected for their knowledge and experience with the topic of interest. The purpose of structuring conversation in this manner is to cultivate collective opinion and highlight areas of disagreement, using a process that minimizes the influence of group dynamics. The underlying premise is that the opinion of a collective is more useful than that of an individual. In designing our study into health literacy, Delphi aligned well with our research focus and would enable us to capture collective views. However, we were interested in the methodology that would inform our study. As researchers, we believe that methodology provides the framework and principles for a study and is integral to research integrity. In assessing the suitability of Delphi for our research purpose, we found little information about underpinning methodology. The absence of a universally recognized or consistent methodology associated with Delphi was highlighted through a scoping review we undertook to assist us in our methodological thinking. This led us to consider alternative methodologies, which might be congruent with the key principles of Delphi. We identified Gadamerian philosophical hermeneutics as a methodology that could provide a supportive framework and principles. We suggest that this methodology may be useful in health and well-being studies utilizing the Delphi method. PMID:25948132

  16. Using a fuzzy DEMATEL method for analyzing the factors influencing subcontractors selection

    NASA Astrophysics Data System (ADS)

    Kozik, Renata

    2016-06-01

    Subcontracting is a long-standing practice in the construction industry. This form of project organization, if manage properly, could provide the better quality, reduction in project time and costs. Subcontractors selection is a multi-criterion problem and can be determined by many factors. Identifying the importance of each of them as well as the direction of cause-effect relations between various types of factors can improve the management process. Their values could be evaluated on the basis of the available expert opinions with the application of a fuzzy multi-stage grading scale. In this paper it is recommended to use fuzzy DEMATEL method to analyze the relationship between factors affecting subcontractors selection.

  17. Development of a quality instrument for assessing the spontaneous reports of ADR/ADE using Delphi method in China.

    PubMed

    Chen, Lixun; Jiang, Ling; Shen, Aizong; Wei, Wei

    2016-09-01

    The frequently low quality of submitted spontaneous reports is of an increasing concern; to our knowledge, no validated instrument exists for assessing case reports' quality comprehensively enough. This work was conducted to develop such a quality instrument for assessing the spontaneous reports of adverse drug reaction (ADR)/adverse drug event (ADE) in China. Initial evaluation indicators were generated using systematic and literature data analysis. Final indicators and their weights were identified using Delphi method. The final quality instrument was developed by adopting the synthetic scoring method. A consensus was reached after four rounds of Delphi survey. The developed quality instrument consisted of 6 first-rank indicators, 18 second-rank indicators, and 115 third-rank indicators, and each rank indicator has been weighted. It evaluates the quality of spontaneous reports of ADR/ADE comprehensively and quantitatively on six parameters: authenticity, duplication, regulatory, completeness, vigilance level, and reporting time frame. The developed instrument was tested with good reliability and validity, which can be used to comprehensively and quantitatively assess the submitted spontaneous reports of ADR/ADE in China.

  18. How to Choose? Using the Delphi Method to Develop Consensus Triggers and Indicators for Disaster Response.

    PubMed

    Lis, Rebecca; Sakata, Vicki; Lien, Onora

    2017-08-01

    To identify key decisions along the continuum of care (conventional, contingency, and crisis) and the critical triggers and data elements used to inform those decisions concerning public health and health care response during an emergency. A classic Delphi method, a consensus-building survey technique, was used with clinicians around Washington State to identify regional triggers and indicators. Additionally, using a modified Delphi method, we combined a workshop and single-round survey with panelists from public health (state and local) and health care coalitions to identify consensus state-level triggers and indicators. In the clinical survey, 122 of 223 proposed triggers or indicators (43.7%) reached consensus and were deemed important in regional decision-making during a disaster. In the state-level survey, 110 of 140 proposed triggers or indicators (78.6%) reached consensus and were deemed important in state-level decision-making during a disaster. The identification of consensus triggers and indicators for health care emergency response is crucial in supporting a comprehensive health care situational awareness process. This can inform the creation of standardized questions to ask health care, public health, and other partners to support decision-making during a response. (Disaster Med Public Health Preparedness. 2017;11:467-472).

  19. [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.

  20. AF-DHNN: Fuzzy Clustering and Inference-Based Node Fault Diagnosis Method for Fire Detection

    PubMed Central

    Jin, Shan; Cui, Wen; Jin, Zhigang; Wang, Ying

    2015-01-01

    Wireless Sensor Networks (WSNs) have been utilized for node fault diagnosis in the fire detection field since the 1990s. However, the traditional methods have some problems, including complicated system structures, intensive computation needs, unsteady data detection and local minimum values. In this paper, a new diagnosis mechanism for WSN nodes is proposed, which is based on fuzzy theory and an Adaptive Fuzzy Discrete Hopfield Neural Network (AF-DHNN). First, the original status of each sensor over time is obtained with two features. One is the root mean square of the filtered signal (FRMS), the other is the normalized summation of the positive amplitudes of the difference spectrum between the measured signal and the healthy one (NSDS). Secondly, distributed fuzzy inference is introduced. The evident abnormal nodes’ status is pre-alarmed to save time. Thirdly, according to the dimensions of the diagnostic data, an adaptive diagnostic status system is established with a Fuzzy C-Means Algorithm (FCMA) and Sorting and Classification Algorithm to reducing the complexity of the fault determination. Fourthly, a Discrete Hopfield Neural Network (DHNN) with iterations is improved with the optimization of the sensors’ detected status information and standard diagnostic levels, with which the associative memory is achieved, and the search efficiency is improved. The experimental results show that the AF-DHNN method can diagnose abnormal WSN node faults promptly and effectively, which improves the WSN reliability. PMID:26193280

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. Consensus in controversy: The modified Delphi method applied to Gynecologic Oncology practice.

    PubMed

    Cohn, David E; Havrilesky, Laura J; Osann, Kathryn; Lipscomb, Joseph; Hsieh, Susie; Walker, Joan L; Wright, Alexi A; Alvarez, Ronald D; Karlan, Beth Y; Bristow, Robert E; DiSilvestro, Paul A; Wakabayashi, Mark T; Morgan, Robert; Mukamel, Dana B; Wenzel, Lari

    2015-09-01

    To determine the degree of consensus regarding the probabilities of outcomes associated with IP/IV and IV chemotherapy. A survey was administered to an expert panel using the Delphi method. Ten ovarian cancer experts were asked to estimate outcomes for patients receiving IP/IV or IV chemotherapy. The clinical estimates were: 1) probability of completing six cycles of chemotherapy, 2) probability of surviving five years, 3) median survival, and 4) probability of ER/hospital visits during treatment. Estimates for two patients, one with a low comorbidity index (patient 1) and the other with a moderate index (patient 2), were included. The survey was administered in three rounds, and panelists could revise their subsequent responses based on review of the anonymous opinions of their peers. The ranges were smaller for IV compared with IP/IV therapy. Ranges decreased with each round. Consensus converged around outcomes related to IP/IV chemotherapy for: 1) completion of 6 cycles of therapy (type 1 patient, 62%, type 2 patient, 43%); 2) percentage of patients surviving 5 years (type 1 patient, 66%, type 2 patient, 47%); and 3) median survival (type 1 patient, 83 months, type 2 patient, 58 months). The group required three rounds to achieve consensus on the probabilities of ER/hospital visits (type 1 patient, 24%, type 2 patient, 35%). Initial estimates of survival and adverse events associated with IP/IV chemotherapy differ among experts. The Delphi process works to build consensus and may be a pragmatic tool to inform patients of their expected outcomes. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. 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.

  8. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    PubMed

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  9. Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

    NASA Astrophysics Data System (ADS)

    Santosa, I.; Romla, L.; Herawati, S.

    2018-01-01

    Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

  10. Using the modified Delphi method to establish a new Chinese clinical consensus of the treatments for cervical radiculopathy.

    PubMed

    Zang, Lei; Fan, Ning; Hai, Yong; Lu, S B; Su, Q J; Yang, J C; Du, Peng; Gao, Y J

    2015-06-01

    Although cervical radiculopathy is very common, there is no standard treatment for this condition, with little high-level evidence available to guide the treatment choice. Thus, this study aimed to review the current data on the management of cervical radiculopathy; and, further, to establish a new Chinese clinical consensus of the treatments for cervical radiculopathy using the Delphi method. First, a systematic review of the previously established treatment guidelines and of articles related to cervical radiculopathy was conducted to establish a protocol for the clinical consensus of the treatment for cervical radiculopathy. Second, from February 2012 to June 2014, we performed a modified Delphi survey in which the current professional opinions from 30 experienced experts, representing almost all of the Chinese provinces, were gathered. Three rounds were performed, and consensus was defined as ≥70% agreement. Consensus of the treatments for cervical radiculopathy was reached on seven aspects, including the proportion of patients requiring only non-surgical therapies; the effectiveness of neck immobilization, physiotherapy, pharmacologic treatment; surgical indications; contraindications; surgery. The modified Delphi study conducted herein reached a consensus concerning several treatment issues for cervical radiculopathy. In the absence of high-level evidence, at present, these expert opinion findings will help guide health care providers to define the appropriate treatment in their regions. Items with no consensus provide excellent areas for future research.

  11. Application of fuzzy AHP method to IOCG prospectivity mapping: A case study in Taherabad prospecting area, eastern Iran

    NASA Astrophysics Data System (ADS)

    Najafi, Ali; Karimpour, Mohammad Hassan; Ghaderi, Majid

    2014-12-01

    Using fuzzy analytical hierarchy process (AHP) technique, we propose a method for mineral prospectivity mapping (MPM) which is commonly used for exploration of mineral deposits. The fuzzy AHP is a popular technique which has been applied for multi-criteria decision-making (MCDM) problems. In this paper we used fuzzy AHP and geospatial information system (GIS) to generate prospectivity model for Iron Oxide Copper-Gold (IOCG) mineralization on the basis of its conceptual model and geo-evidence layers derived from geological, geochemical, and geophysical data in Taherabad area, eastern Iran. The FuzzyAHP was used to determine the weights belonging to each criterion. Three geoscientists knowledge on exploration of IOCG-type mineralization have been applied to assign weights to evidence layers in fuzzy AHP MPM approach. After assigning normalized weights to all evidential layers, fuzzy operator was applied to integrate weighted evidence layers. Finally for evaluating the ability of the applied approach to delineate reliable target areas, locations of known mineral deposits in the study area were used. The results demonstrate the acceptable outcomes for IOCG exploration.

  12. Expert surgical consensus for prenatal counseling using the Delphi method.

    PubMed

    Berman, Loren; Jackson, Jordan; Miller, Kristen; Kowalski, Rebecca; Kolm, Paul; Luks, Francois I

    2017-11-28

    Pediatric surgeons frequently offer prenatal consultation for congenital pulmonary airway malformation (CPAM) and congenital diaphragmatic hernia (CDH); however, there is no evidence-based consensus to guide prenatal decision making and counseling for these conditions. Eliciting feedback from experts is integral to defining best practice regarding prenatal counseling and intervention. A Delphi consensus process was undertaken using a panel of pediatric surgeons identified as experts in fetal therapy to address current limitations. Areas of discrepancy in the literature on CPAM and CDH were identified and used to generate a list of content and intervention questions. Experts were invited to participate in an online Delphi survey. Items that did not reach first-round consensus were broken down into additional questions, and consensus was achieved in the second round. Fifty-four surgeons (69%) responded to at least one of the two survey rounds. During round one, consensus was reached on 54 of 89 survey questions (61%), and 45 new questions were developed. During round two, consensus was reached on 53 of 60 survey questions (88%). We determined expert consensus to establish guidelines regarding perinatal management of CPAM and CDH. Our results can help educate pediatric surgeons participating in perinatal care of these patients. V. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Fuzzy logic particle tracking velocimetry

    NASA Technical Reports Server (NTRS)

    Wernet, Mark P.

    1993-01-01

    Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.

  14. Application of multi response optimization with grey relational analysis and fuzzy logic method

    NASA Astrophysics Data System (ADS)

    Winarni, Sri; Wahyu Indratno, Sapto

    2018-01-01

    Multi-response optimization is an optimization process by considering multiple responses simultaneously. The purpose of this research is to get the optimum point on multi-response optimization process using grey relational analysis and fuzzy logic method. The optimum point is determined from the Fuzzy-GRG (Grey Relational Grade) variable which is the conversion of the Signal to Noise Ratio of the responses involved. The case study used in this research are case optimization of electrical process parameters in electrical disharge machining. It was found that the combination of treatments resulting to optimum MRR and SR was a 70 V gap voltage factor, peak current 9 A and duty factor 0.8.

  15. 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.

  16. 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.

  17. Improving the care of older persons in Australian prisons using the Policy Delphi method.

    PubMed

    Patterson, Karen; Newman, Claire; Doona, Katherine

    2016-09-01

    There are currently no internationally recognised and approved processes relating to the care of older persons with dementia in prison. This research aimed to develop tools and procedures related to managing the care of, including the identification and assessment of, older persons with dementia who are imprisoned in New South Wales, Australia. A modified approach to the Policy Delphi method, using both surveys and facilitated discussion groups, enabled experts to come together to discuss improving the quality of care provision for older persons with dementia in prison and achieve research aims. © The Author(s) 2014.

  18. Comparison of Fuzzy-Based Models in Landslide Hazard Mapping

    NASA Astrophysics Data System (ADS)

    Mijani, N.; Neysani Samani, N.

    2017-09-01

    Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR) and Quality Sum (QS). The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P) and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

  19. Delphi`s DETOXSM process: Preparing to treat high organic content hazardous and mixed wastes

    SciTech Connect

    Robertson, D.T.; Rogers, T.W.; Goldblatt, S.D.

    1998-12-31

    The US Department of Energy (DOE) Federal Energy Technology Center is sponsoring a full-scale technology demonstration of Delphi Research, Inc.`s patented DETOX{sup SM} catalytic wet chemical oxidation waste treatment process at the Savannah River Site (SRS) in South Carolina. The process is being developed primarily to treat hazardous and mixed wastes within the DOE complex as an alternative to incineration, but it has significant potential to treat wastes in the commercial sector. The results of the demonstration will be intensively studied and used to validate the technology. A critical objective in preparing for the demonstration was the successful completion ofmore » a programmatic Operational Readiness Review. Readiness Reviews are required by DOE for all new process startups. The Readiness Review provided the vehicle to ensure that Delphi was ready to start up and operate the DETOX{sup SM} process in the safest manner possible by implementing industry accepted management practices for safe operation. This paper provides an overview of the DETOX{sup SM} demonstration at SRS, and describes the crucial areas of the Readiness Review that marked the first steps in Delphi`s transition from a technology developer to an operating waste treatment services provider.« less

  20. Solving fully fuzzy transportation problem using pentagonal fuzzy numbers

    NASA Astrophysics Data System (ADS)

    Maheswari, P. Uma; Ganesan, K.

    2018-04-01

    In this paper, we propose a simple approach for the solution of fuzzy transportation problem under fuzzy environment in which the transportation costs, supplies at sources and demands at destinations are represented by pentagonal fuzzy numbers. The fuzzy transportation problem is solved without converting to its equivalent crisp form using a robust ranking technique and a new fuzzy arithmetic on pentagonal fuzzy numbers. To illustrate the proposed approach a numerical example is provided.

  1. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

    PubMed Central

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

  2. Delphi Rating on the Internet

    PubMed Central

    Deshpande, Aniruddha M.; Shiffman, Richard N.

    2003-01-01

    We designed an application to allow respondents to rate components of clinical guidelines on the Internet. Twenty-three invited experts completed the rating followed by a satisfaction survey using a 5-level Likert scale. The experts felt that Web data entry was convenient, acceptable and easily accessible. We conclude that Web-based Delphi rating for consensus development is a convenient and acceptable alternative to the traditional paper-based method. PMID:14728333

  3. 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.

  4. Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

    PubMed Central

    Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis

    2014-01-01

    A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428

  5. 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.

  6. A Delphi Study on Staff Bereavement Training in the Intellectual and Developmental Disabilities Field

    ERIC Educational Resources Information Center

    Gray, Jennifer A.; Truesdale, Jesslyn

    2015-01-01

    The Delphi technique was used to obtain expert panel consensus to prioritize content areas and delivery methods for developing staff grief and bereavement curriculum training in the intellectual and developmental disabilities (IDD) field. The Delphi technique was conducted with a panel of 18 experts from formal and informal disability caregiving,…

  7. Defining consensus: a systematic review recommends methodologic criteria for reporting of Delphi studies.

    PubMed

    Diamond, Ivan R; Grant, Robert C; Feldman, Brian M; Pencharz, Paul B; Ling, Simon C; Moore, Aideen M; Wales, Paul W

    2014-04-01

    To investigate how consensus is operationalized in Delphi studies and to explore the role of consensus in determining the results of these studies. Systematic review of a random sample of 100 English language Delphi studies, from two large multidisciplinary databases [ISI Web of Science (Thompson Reuters, New York, NY) and Scopus (Elsevier, Amsterdam, NL)], published between 2000 and 2009. About 98 of the Delphi studies purported to assess consensus, although a definition for consensus was only provided in 72 of the studies (64 a priori). The most common definition for consensus was percent agreement (25 studies), with 75% being the median threshold to define consensus. Although the authors concluded in 86 of the studies that consensus was achieved, consensus was only specified a priori (with a threshold value) in 42 of these studies. Achievement of consensus was related to the decision to stop the Delphi study in only 23 studies, with 70 studies terminating after a specified number of rounds. Although consensus generally is felt to be of primary importance to the Delphi process, definitions of consensus vary widely and are poorly reported. Improved criteria for reporting of methods of Delphi studies are required. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis

    NASA Astrophysics Data System (ADS)

    Sun, Bingxiang; Jiang, Jiuchun; Zheng, Fangdan; Zhao, Wei; Liaw, Bor Yann; Ruan, Haijun; Han, Zhiqiang; Zhang, Weige

    2015-05-01

    The state of health (SOH) estimation is very critical to battery management system to ensure the safety and reliability of EV battery operation. Here, we used a unique hybrid approach to enable complex SOH estimations. The approach hybridizes the Delphi method known for its simplicity and effectiveness in applying weighting factors for complicated decision-making and the grey relational grade analysis (GRGA) for multi-factor optimization. Six critical factors were used in the consideration for SOH estimation: peak power at 30% state-of-charge (SOC), capacity, the voltage drop at 30% SOC with a C/3 pulse, the temperature rises at the end of discharge and charge at 1C; respectively, and the open circuit voltage at the end of charge after 1-h rest. The weighting of these factors for SOH estimation was scored by the 'experts' in the Delphi method, indicating the influencing power of each factor on SOH. The parameters for these factors expressing the battery state variations are optimized by GRGA. Eight battery cells were used to illustrate the principle and methodology to estimate the SOH by this hybrid approach, and the results were compared with those based on capacity and power capability. The contrast among different SOH estimations is discussed.

  9. Designing a Standardized Laparoscopy Curriculum for Gynecology Residents: A Delphi Approach

    PubMed Central

    Shore, Eliane M.; Lefebvre, Guylaine G.; Husslein, Heinrich; Bjerrum, Flemming; Sorensen, Jette Led; Grantcharov, Teodor P.

    2015-01-01

    Background Evidence suggests that simulation leads to improved operative skill, shorter operating room time, and better patient outcomes. Currently, no standardized laparoscopy curriculum exists for gynecology residents. Objective To design a structured laparoscopy curriculum for gynecology residents using Delphi consensus methodology. Methods This study began with Delphi methodology to determine expert consensus on the components of a gynecology laparoscopic skills curriculum. We generated a list of cognitive content, technical skills, and nontechnical skills for training in laparoscopic surgery, and asked 39 experts in gynecologic education to rate the items on a Likert scale (1–5) for inclusion in the curriculum. Consensus was predefined as Cronbach α of ≥ 0.80. We then conducted another Delphi survey with 9 experienced users of laparoscopic virtual reality simulators to delineate relevant curricular tasks. Finally, a cross-sectional design defined benchmark scores for all identified tasks, with 10 experienced gynecologic surgeons performing the identified tasks at basic, intermediate, and advanced levels. Results Consensus (Cronbach α = 0.85) was achieved in the first round of the curriculum Delphi, and after 2 rounds (Cronbach α = 0.80) in the virtual reality curriculum Delphi. Consensus was reached for cognitive, technical, and nontechnical skills as well as for 6 virtual reality tasks. Median time and economy of movement scores defined benchmarks for all tasks. Conclusions This study used Delphi consensus to develop a comprehensive curriculum for teaching gynecologic laparoscopy. The curriculum conforms to current educational standards of proficiency-based training, and is suggested as a standard in residency programs. PMID:26221434

  10. A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES

    SciTech Connect

    Druckmueller, M., E-mail: druckmuller@fme.vutbr.cz

    A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.

  11. 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.

  12. Computer Technology and Education: A Policy Delphi.

    ERIC Educational Resources Information Center

    Steier, Lloyd P.

    Realizing the educational potential of computer technology largely depends on developing appropriate policies related to the technology. A Policy Delphi method was used to identify changes in education that are both probable and possible on account of the introduction of computers, and to explore potential patterns for arriving at a desired…

  13. A cross-validation Delphi method approach to the diagnosis and treatment of personality disorders in older adults.

    PubMed

    Rosowsky, Erlene; Young, Alexander S; Malloy, Mary C; van Alphen, S P J; Ellison, James M

    2018-03-01

    The Delphi method is a consensus-building technique using expert opinion to formulate a shared framework for understanding a topic with limited empirical support. This cross-validation study replicates one completed in the Netherlands and Belgium, and explores US experts' views on the diagnosis and treatment of older adults with personality disorders (PD). Twenty-one geriatric PD experts participated in a Delphi survey addressing diagnosis and treatment of older adults with PD. The European survey was translated and administered electronically. First-round consensus was reached for 16 out of 18 items relevant to diagnosis and specific mental health programs for personality disorders in older adults. Experts agreed on the usefulness of establishing criteria for specific types of treatments. The majority of psychologists did not initially agree on the usefulness of pharmacotherapy. Expert consensus was reached following two subsequent rounds after clarification addressing medication use. Study results suggest consensus among regarding psychosocial treatments. Limited acceptance amongst US psychologists about the suitability of pharmacotherapy for late-life PDs contrasted with the views expressed by experts surveyed in Netherlands and Belgium studies.

  14. Fuzzy-Rough Nearest Neighbour Classification

    NASA Astrophysics Data System (ADS)

    Jensen, Richard; Cornelis, Chris

    A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar's fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the experimental analysis, we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm.

  15. 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.

  16. The gap values in the profile matching method by fuzzy logic

    NASA Astrophysics Data System (ADS)

    Sitepu, S. A.; Efendi, S.; Situmorang, Z.

    2018-03-01

    In this research, the determination of the appropriate values of Gap for the assessment of promotion criteria of position in an institution / company. In this study the authors use Fuzzy Sugeno logic on the determination of Gap values used in Profile Matching method. Test results of 5 employees obtained the eligibility of promotion with the position of Z* values between in 3.20 to 4.11.

  17. Fuzzy Logic Engine

    NASA Technical Reports Server (NTRS)

    Howard, Ayanna

    2005-01-01

    The Fuzzy Logic Engine is a software package that enables users to embed fuzzy-logic modules into their application programs. Fuzzy logic is useful as a means of formulating human expert knowledge and translating it into software to solve problems. Fuzzy logic provides flexibility for modeling relationships between input and output information and is distinguished by its robustness with respect to noise and variations in system parameters. In addition, linguistic fuzzy sets and conditional statements allow systems to make decisions based on imprecise and incomplete information. The user of the Fuzzy Logic Engine need not be an expert in fuzzy logic: it suffices to have a basic understanding of how linguistic rules can be applied to the user's problem. The Fuzzy Logic Engine is divided into two modules: (1) a graphical-interface software tool for creating linguistic fuzzy sets and conditional statements and (2) a fuzzy-logic software library for embedding fuzzy processing capability into current application programs. The graphical- interface tool was developed using the Tcl/Tk programming language. The fuzzy-logic software library was written in the C programming language.

  18. Brain tumor segmentation in MRI by using the fuzzy connectedness method

    NASA Astrophysics Data System (ADS)

    Liu, Jian-Guo; Udupa, Jayaram K.; Hackney, David; Moonis, Gul

    2001-07-01

    The aim of this paper is the precise and accurate quantification of brain tumor via MRI. This is very useful in evaluating disease progression, response to therapy, and the need for changes in treatment plans. We use multiple MRI protocols including FLAIR, T1, and T1 with Gd enhancement to gather information about different aspects of the tumor and its vicinity- edema, active regions, and scar left over due to surgical intervention. We have adapted the fuzzy connectedness framework to segment tumor and to measure its volume. The method requires only limited user interaction in routine clinical MRI. The first step in the process is to apply an intensity normalization method to the images so that the same body region has the same tissue meaning independent of the scanner and patient. Subsequently, a fuzzy connectedness algorithm is utilized to segment the different aspects of the tumor. The system has been tested, for its precision, accuracy, and efficiency, utilizing 40 patient studies. The percent coefficient of variation (% CV) in volume due to operator subjectivity in specifying seeds for fuzzy connectedness segmentation is less than 1%. The mean operator and computer time taken per study is 3 minutes. The package is designed to run under operator supervision. Delineation has been found to agree with the operators' visual inspection most of the time except in some cases when the tumor is close to the boundary of the brain. In the latter case, the scalp is included in the delineation and an operator has to exclude this manually. The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system.

  19. Decomposed fuzzy systems and their application in direct adaptive fuzzy control.

    PubMed

    Hsueh, Yao-Chu; Su, Shun-Feng; Chen, Ming-Chang

    2014-10-01

    In this paper, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator for adaptive fuzzy control systems. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables form the so-called component fuzzy systems. DFS is proposed to provide more adjustable parameters to facilitate possible adaptation in fuzzy rules, but without introducing a learning burden. It is because those component fuzzy systems are independent so that it can facilitate minimum distribution learning effects among component fuzzy systems. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this paper to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure.

  20. Model Multi Criteria Decision Making with Fuzzy ANP Method for Performance Measurement Small Medium Enterprise (SME)

    NASA Astrophysics Data System (ADS)

    Rahmanita, E.; Widyaningrum, V. T.; Kustiyahningsih, Y.; Purnama, J.

    2018-04-01

    SMEs have a very important role in the development of the economy in Indonesia. SMEs assist the government in terms of creating new jobs and can support household income. The number of SMEs in Madura and the number of measurement indicators in the SME mapping so that it requires a method.This research uses Fuzzy Analytic Network Process (FANP) method for performance measurement SME. The FANP method can handle data that contains uncertainty. There is consistency index in determining decisions. Performance measurement in this study is based on a perspective of the Balanced Scorecard. This research approach integrated internal business perspective, learning, and growth perspective and fuzzy Analytic Network Process (FANP). The results of this research areframework a priority weighting of assessment indicators SME.

  1. An improved parallel fuzzy connected image segmentation method based on CUDA.

    PubMed

    Wang, Liansheng; Li, Dong; Huang, Shaohui

    2016-05-12

    Fuzzy connectedness method (FC) is an effective method for extracting fuzzy objects from medical images. However, when FC is applied to large medical image datasets, its running time will be greatly expensive. Therefore, a parallel CUDA version of FC (CUDA-kFOE) was proposed by Ying et al. to accelerate the original FC. Unfortunately, CUDA-kFOE does not consider the edges between GPU blocks, which causes miscalculation of edge points. In this paper, an improved algorithm is proposed by adding a correction step on the edge points. The improved algorithm can greatly enhance the calculation accuracy. In the improved method, an iterative manner is applied. In the first iteration, the affinity computation strategy is changed and a look up table is employed for memory reduction. In the second iteration, the error voxels because of asynchronism are updated again. Three different CT sequences of hepatic vascular with different sizes were used in the experiments with three different seeds. NVIDIA Tesla C2075 is used to evaluate our improved method over these three data sets. Experimental results show that the improved algorithm can achieve a faster segmentation compared to the CPU version and higher accuracy than CUDA-kFOE. The calculation results were consistent with the CPU version, which demonstrates that it corrects the edge point calculation error of the original CUDA-kFOE. The proposed method has a comparable time cost and has less errors compared to the original CUDA-kFOE as demonstrated in the experimental results. In the future, we will focus on automatic acquisition method and automatic processing.

  2. Using a Delphi process to establish consensus on emergency medicine clerkship competencies.

    PubMed

    Penciner, Rick; Langhan, Trevor; Lee, Richard; McEwen, Jill; Woods, Robert A; Bandiera, Glen

    2011-01-01

    Currently, there is no consensus on the core competencies required for emergency medicine (EM) clerkships in Canada. Existing EM curricula have been developed through informal consensus or local efforts. The Delphi process has been used extensively as a means for establishing consensus. The purpose of this project was to define core competencies for EM clerkships in Canada, to validate a Delphi process in the context of national curriculum development, and to demonstrate the adoption of the CanMEDS physician competency paradigm in the undergraduate medical education realm. Using a modified Delphi process, we developed a consensus amongst a panel of expert emergency physicians from across Canada utilizing the CanMEDS 2005 Physician Competency Framework. Thirty experts from nine different medical schools across Canada participated on the panel. The initial list consisted of 152 competencies organized in the seven domains of the CanMEDS 2005 Physician Competency Framework. After the second round of the Delphi process, the list of competencies was reduced to 62 (59% reduction). This study demonstrated that a modified Delphi process can result in a strong consensus around a realistic number of core competencies for EM clerkships. We propose that such a method could be used by other medical specialties and health professions to develop rotation-specific core competencies.

  3. 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.

  4. A neural fuzzy controller learning by fuzzy error propagation

    NASA Technical Reports Server (NTRS)

    Nauck, Detlef; Kruse, Rudolf

    1992-01-01

    In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

  5. 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.

  6. Development of an Electronic Pediatric All-Cause Harm Measurement Tool Using a Modified Delphi Method.

    PubMed

    Stockwell, David Christopher; Bisarya, Hema; Classen, David C; Kirkendall, Eric S; Lachman, Peter I; Matlow, Anne G; Tham, Eric; Hyman, Dan; Lehman, Samuel M; Searles, Elizabeth; Muething, Stephen E; Sharek, Paul J

    2016-12-01

    To have impact on reducing harm in pediatric inpatients, an efficient and reliable process for harm detection is needed. This work describes the first step toward the development of a pediatric all-cause harm measurement tool by recognized experts in the field. An international group of leaders in pediatric patient safety and informatics were charged with developing a comprehensive pediatric inpatient all-cause harm measurement tool using a modified Delphi technique. The process was conducted in 5 distinct steps: (1) literature review of triggers (elements from a medical record that assist in identifying patient harm) for inclusion; (2) translation of triggers to likely associated harm, improving the ability for expert prioritization; (3) 2 applications of a modified Delphi selection approach with consensus criteria using severity and frequency of harm as well as detectability of the associated trigger as criteria to rate each trigger and associated harm; (4) developing specific trigger logic and relevant values when applicable; and (5) final vetting of the entire trigger list for pilot testing. Literature and expert panel review identified 108 triggers and associated harms suitable for consideration (steps 1 and 2). This list was pared to 64 triggers and their associated harms after the first of the 2 independent expert reviews. The second independent expert review led to further refinement of the trigger package, resulting in 46 items for inclusion (step 3). Adding in specific trigger logic expanded the list. Final review and voting resulted in a list of 51 triggers (steps 4 and 5). Application of a modified Delphi method on an expert-constructed list of 108 triggers, focusing on severity and frequency of harms as well as detectability of triggers in an electronic medical record, resulted in a final list of 51 pediatric triggers. Pilot testing this list of pediatric triggers to identify all-cause harm for pediatric inpatients is the next step to establish the

  7. The Stammering Information Programme: A Delphi Study

    ERIC Educational Resources Information Center

    Berquez, Ali E.; Cook, Frances M.; Millard, Sharon K.; Jarvis, Effie

    2011-01-01

    Purpose: To find out what information children, parents and education staff feel would be important to know to support a child who stutters in the educational environment, in order to develop appropriate resources. Method: A Delphi study was carried out to seek the opinions of experts about the information to include. A structured six stage…

  8. An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

    PubMed Central

    Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

    2016-01-01

    With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

  9. Consulting the oracle: ten lessons from using the Delphi technique in nursing research.

    PubMed

    Keeney, Sinead; Hasson, Felicity; McKenna, Hugh

    2006-01-01

    The aim of this paper was to provide insight into the Delphi technique by outlining our personal experiences during its use over a 10-year period in a variety of applications. As a means of achieving consensus on an issue, the Delphi research method has become widely used in healthcare research generally and nursing research in particular. The literature on this technique is expanding, mainly addressing what it is and how it should be used. However, there is still much confusion and uncertainty surrounding it, particularly about issues such as modifications, consensus, anonymity, definition of experts, how 'experts' are selected and how non-respondents are pursued. This issues that arise when planning and carrying out a Delphi study include the definition of consensus; the issue of anonymity vs. quasi-anonymity for participants; how to estimate the time needed to collect the data, analyse each 'round', feed back results to participants, and gain their responses to this feedback; how to define and select the 'experts' who will be asked to participate; how to enhance response rates; and how many 'rounds' to conduct. Many challenges and questions are raised when using the Delphi technique, but there is no doubt that it is an important method for achieving consensus on issues where none previously existed. Researchers need to adapt the method to suit their particular study.

  10. 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.

  11. Use of a Computer-Mediated Delphi Process to Validate a Mass Casualty Conceptual Model

    PubMed Central

    CULLEY, JOAN M.

    2012-01-01

    Since the original work on the Delphi technique, multiple versions have been developed and used in research and industry; however, very little empirical research has been conducted that evaluates the efficacy of using online computer, Internet, and e-mail applications to facilitate a Delphi method that can be used to validate theoretical models. The purpose of this research was to develop computer, Internet, and e-mail applications to facilitate a modified Delphi technique through which experts provide validation for a proposed conceptual model that describes the information needs for a mass-casualty continuum of care. Extant literature and existing theoretical models provided the basis for model development. Two rounds of the Delphi process were needed to satisfy the criteria for consensus and/or stability related to the constructs, relationships, and indicators in the model. The majority of experts rated the online processes favorably (mean of 6.1 on a seven-point scale). Using online Internet and computer applications to facilitate a modified Delphi process offers much promise for future research involving model building or validation. The online Delphi process provided an effective methodology for identifying and describing the complex series of events and contextual factors that influence the way we respond to disasters. PMID:21076283

  12. Use of a computer-mediated Delphi process to validate a mass casualty conceptual model.

    PubMed

    Culley, Joan M

    2011-05-01

    Since the original work on the Delphi technique, multiple versions have been developed and used in research and industry; however, very little empirical research has been conducted that evaluates the efficacy of using online computer, Internet, and e-mail applications to facilitate a Delphi method that can be used to validate theoretical models. The purpose of this research was to develop computer, Internet, and e-mail applications to facilitate a modified Delphi technique through which experts provide validation for a proposed conceptual model that describes the information needs for a mass-casualty continuum of care. Extant literature and existing theoretical models provided the basis for model development. Two rounds of the Delphi process were needed to satisfy the criteria for consensus and/or stability related to the constructs, relationships, and indicators in the model. The majority of experts rated the online processes favorably (mean of 6.1 on a seven-point scale). Using online Internet and computer applications to facilitate a modified Delphi process offers much promise for future research involving model building or validation. The online Delphi process provided an effective methodology for identifying and describing the complex series of events and contextual factors that influence the way we respond to disasters.

  13. 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.

  14. 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.

  15. Fuzzy scalar and vector median filters based on fuzzy distances.

    PubMed

    Chatzis, V; Pitas, I

    1999-01-01

    In this paper, the fuzzy scalar median (FSM) is proposed, defined by using ordering of fuzzy numbers based on fuzzy minimum and maximum operations defined by using the extension principle. Alternatively, the FSM is defined from the minimization of a fuzzy distance measure, and the equivalence of the two definitions is proven. Then, the fuzzy vector median (FVM) is proposed as an extension of vector median, based on a novel distance definition of fuzzy vectors, which satisfy the property of angle decomposition. By defining properly the fuzziness of a value, the combination of the basic properties of the classical scalar and vector median (VM) filter with other desirable characteristics can be succeeded.

  16. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    NASA Astrophysics Data System (ADS)

    Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

    2017-12-01

    There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

  17. Complex Fuzzy Set-Valued Complex Fuzzy Measures and Their Properties

    PubMed Central

    Ma, Shengquan; Li, Shenggang

    2014-01-01

    Let F*(K) be the set of all fuzzy complex numbers. In this paper some classical and measure-theoretical notions are extended to the case of complex fuzzy sets. They are fuzzy complex number-valued distance on F*(K), fuzzy complex number-valued measure on F*(K), and some related notions, such as null-additivity, pseudo-null-additivity, null-subtraction, pseudo-null-subtraction, autocontionuous from above, autocontionuous from below, and autocontinuity of the defined fuzzy complex number-valued measures. Properties of fuzzy complex number-valued measures are studied in detail. PMID:25093202

  18. 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.

  19. 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.

  20. 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.

  1. Approximation abilities of neuro-fuzzy networks

    NASA Astrophysics Data System (ADS)

    Mrówczyńska, Maria

    2010-01-01

    The paper presents the operation of two neuro-fuzzy systems of an adaptive type, intended for solving problems of the approximation of multi-variable functions in the domain of real numbers. Neuro-fuzzy systems being a combination of the methodology of artificial neural networks and fuzzy sets operate on the basis of a set of fuzzy rules "if-then", generated by means of the self-organization of data grouping and the estimation of relations between fuzzy experiment results. The article includes a description of neuro-fuzzy systems by Takaga-Sugeno-Kang (TSK) and Wang-Mendel (WM), and in order to complement the problem in question, a hierarchical structural self-organizing method of teaching a fuzzy network. A multi-layer structure of the systems is a structure analogous to the structure of "classic" neural networks. In its final part the article presents selected areas of application of neuro-fuzzy systems in the field of geodesy and surveying engineering. Numerical examples showing how the systems work concerned: the approximation of functions of several variables to be used as algorithms in the Geographic Information Systems (the approximation of a terrain model), the transformation of coordinates, and the prediction of a time series. The accuracy characteristics of the results obtained have been taken into consideration.

  2. 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.

  3. Combining fuzzy mathematics with fuzzy logic to solve business management problems

    NASA Astrophysics Data System (ADS)

    Vrba, Joseph A.

    1993-12-01

    Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

  4. 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.

  5. Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator.

    PubMed

    Nguyen, Sy Dzung; Vo, Hoang Duy; Seo, Tae-Il

    2017-09-01

    It is difficult to efficiently control nonlinear systems in the presence of uncertainty and disturbance (UAD). One of the main reasons derives from the negative impact of the unknown features of UAD as well as the response delay of the control system on the accuracy rate in the real time of the control signal. In order to deal with this, we propose a new controller named CO-FSMC for a class of nonlinear control systems subjected to UAD, which is constituted of a fuzzy sliding mode controller (FSMC) and a fuzzy-based compensator (CO). Firstly, the FSMC and CO are designed independently, and then an adaptive fuzzy structure is discovered to combine them. Solutions for avoiding the singular cases of the fuzzy-based function approximation and reducing the calculating cost are proposed. Based on the solutions, fuzzy sliding mode technique, lumped disturbance observer and Lyapunov stability analysis, a closed-loop adaptive control law is formulated. Simulations along with a real application based on a semi-active train-car suspension are performed to fully evaluate the method. The obtained results reflected that vibration of the chassis mass is insensitive to UAD. Compared with the other fuzzy sliding mode control strategies, the CO-FSMC can provide the best control ability to reduce unwanted vibrations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. A Delphi Study: Exploring Faculty Perceptions of the Best Practices Influencing Student Persistence in Blended Courses

    ERIC Educational Resources Information Center

    Manning, Kim Elise

    2010-01-01

    This Delphi study explored the instructional practices of community college faculty who were teaching blended or Web-assisted courses and how these practices influenced student persistence. The Delphi method provided qualitative data in the form of expert advice through consensus building on the instructional practices most likely to influence…

  7. A genetic fuzzy analytical hierarchy process based projection pursuit method for selecting schemes of water transportation projects

    NASA Astrophysics Data System (ADS)

    Jin, Juliang; Li, Lei; Wang, Wensheng; Zhang, Ming

    2006-10-01

    The optimal selection of schemes of water transportation projects is a process of choosing a relatively optimal scheme from a number of schemes of water transportation programming and management projects, which is of importance in both theory and practice in water resource systems engineering. In order to achieve consistency and eliminate the dimensions of fuzzy qualitative and fuzzy quantitative evaluation indexes, to determine the weights of the indexes objectively, and to increase the differences among the comprehensive evaluation index values of water transportation project schemes, a projection pursuit method, named FPRM-PP for short, was developed in this work for selecting the optimal water transportation project scheme based on the fuzzy preference relation matrix. The research results show that FPRM-PP is intuitive and practical, the correction range of the fuzzy preference relation matrix A it produces is relatively small, and the result obtained is both stable and accurate; therefore FPRM-PP can be widely used in the optimal selection of different multi-factor decision-making schemes.

  8. Successful and Unsuccessful Multicultural Supervisory Behaviors: A Delphi Poll

    ERIC Educational Resources Information Center

    Dressel, Jeana L.; Consoli, Andres J.; Kim, Bryan S.K.; Atkinson, Donald R.

    2007-01-01

    Using the Delphi method, university counseling center supervisors with significant experience in multicultural supervision generated and ranked elements of successful and unsuccessful multicultural supervision. Twenty-seven of 35 successful elements and 24 of 33 unsuccessful elements involved cultural considerations. Multicultural supervision was…

  9. Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

    PubMed

    Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

    2017-07-01

    The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

  10. 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

  11. A new method for generating an invariant iris private key based on the fuzzy vault system.

    PubMed

    Lee, Youn Joo; Park, Kang Ryoung; Lee, Sung Joo; Bae, Kwanghyuk; Kim, Jaihie

    2008-10-01

    Cryptographic systems have been widely used in many information security applications. One main challenge that these systems have faced has been how to protect private keys from attackers. Recently, biometric cryptosystems have been introduced as a reliable way of concealing private keys by using biometric data. A fuzzy vault refers to a biometric cryptosystem that can be used to effectively protect private keys and to release them only when legitimate users enter their biometric data. In biometric systems, a critical problem is storing biometric templates in a database. However, fuzzy vault systems do not need to directly store these templates since they are combined with private keys by using cryptography. Previous fuzzy vault systems were designed by using fingerprint, face, and so on. However, there has been no attempt to implement a fuzzy vault system that used an iris. In biometric applications, it is widely known that an iris can discriminate between persons better than other biometric modalities. In this paper, we propose a reliable fuzzy vault system based on local iris features. We extracted multiple iris features from multiple local regions in a given iris image, and the exact values of the unordered set were then produced using the clustering method. To align the iris templates with the new input iris data, a shift-matching technique was applied. Experimental results showed that 128-bit private keys were securely and robustly generated by using any given iris data without requiring prealignment.

  12. A Delphi forecast of technology in education

    NASA Technical Reports Server (NTRS)

    Robinson, B. E.

    1973-01-01

    The results are reported of a Delphi forecast of the utilization and social impacts of large-scale educational telecommunications technology. The focus is on both forecasting methodology and educational technology. The various methods of forecasting used by futurists are analyzed from the perspective of the most appropriate method for a prognosticator of educational technology, and review and critical analysis are presented of previous forecasts and studies. Graphic responses, summarized comments, and a scenario of education in 1990 are presented.

  13. Fuzzy logic in control systems: Fuzzy logic controller. I, II

    NASA Technical Reports Server (NTRS)

    Lee, Chuen Chien

    1990-01-01

    Recent advances in the theory and applications of fuzzy-logic controllers (FLCs) are examined in an analytical review. The fundamental principles of fuzzy sets and fuzzy logic are recalled; the basic FLC components (fuzzification and defuzzification interfaces, knowledge base, and decision-making logic) are described; and the advantages of FLCs for incorporating expert knowledge into a control system are indicated. Particular attention is given to fuzzy implication functions, the interpretation of sentence connectives (and, also), compositional operators, and inference mechanisms. Applications discussed include the FLC-guided automobile developed by Sugeno and Nishida (1985), FLC hardware systems, FLCs for subway trains and ship-loading cranes, fuzzy-logic chips, and fuzzy computers.

  14. Fuzzy associative memories

    NASA Technical Reports Server (NTRS)

    Kosko, Bart

    1991-01-01

    Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

  15. The Semiconductor Industry and Emerging Technologies: A Study Using a Modified Delphi Method

    ERIC Educational Resources Information Center

    Jordan, Edgar A.

    2010-01-01

    The purpose of this qualitative descriptive study was to determine what leaders in the semiconductor industry thought the future of computing would look like and what emerging materials showed the most promise to overcome the current theoretical limit of 10 nanometers for silicon dioxide. The researcher used a modified Delphi technique in two…

  16. Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement

    PubMed Central

    Yang, Jie; Kasabov, Nikola

    2017-01-01

    Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect. PMID:28744464

  17. 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.

  18. Imprecise (fuzzy) information in geostatistics

    SciTech Connect

    Bardossy, A.; Bogardi, I.; Kelly, W.E.

    1988-05-01

    A methodology based on fuzzy set theory for the utilization of imprecise data in geostatistics is presented. A common problem preventing a broader use of geostatistics has been the insufficient amount of accurate measurement data. In certain cases, additional but uncertain (soft) information is available and can be encoded as subjective probabilities, and then the soft kriging method can be applied (Journal, 1986). In other cases, a fuzzy encoding of soft information may be more realistic and simplify the numerical calculations. Imprecise (fuzzy) spatial information on the possible variogram is integrated into a single variogram which is used in amore » fuzzy kriging procedure. The overall uncertainty of prediction is represented by the estimation variance and the calculated membership function for each kriged point. The methodology is applied to the permeability prediction of a soil liner for hazardous waste containment. The available number of hard measurement data (20) was not enough for a classical geostatistical analysis. An additional 20 soft data made it possible to prepare kriged contour maps using the fuzzy geostatistical procedure.« less

  19. Practical Considerations for Conducting Delphi Studies: The Oracle Enters a New Age.

    ERIC Educational Resources Information Center

    Eggers, Renee M.; Jones, Charles M.

    1998-01-01

    In addition to giving an overview of Delphi methodology and describing the methodology used by the researchers in two Delphi studies, the authors provide information about electronic communication in Delphi studies. Also provided are suggestions that can be used in a Delphi study involving any form of communication. (SLD)

  20. Future Directions for Business Education: A Delphi Study

    ERIC Educational Resources Information Center

    Kesten, Cyril A.; Lambrecht, Judith J.

    2010-01-01

    Purpose: The purpose of this study was to synthesize perceptions from the field about current issues and to propose future directions for the field of business education. Method: A modified three-stage Delphi study was carried out with business educators who attended national conferences and/or belonged to national professional organizations.…

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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].

  7. Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

    NASA Astrophysics Data System (ADS)

    Irvanizam, I.

    2018-03-01

    Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

  8. DELPHI: An introduction to output layout and data content

    SciTech Connect

    Smith, C.F.

    1994-08-16

    DELPHI was the data summary and interpretation code used by gas diagnostics personnel during the period from 1968 through 1986. It was written by Floyd Momyer, and went through several revisions during its period of use. Described here is the final version, which provided the most extensive set of summary tables. Earlier versions of the code lacked some of the capabilities of the final version, but what they did include was of substantially the same format. DELPHI was run against most available input decks in the mid 1980s. Microfiche and hardcopy output were generated. Both now reside in our archives.more » These reruns used modified input decks, which may not have had the proper {open_quotes}trigger{close_quotes} to instruct DELPHI to output some tables. These tables could, therefore be missing from a printout even though the necessary data was present. Also, modifications to DELPHI did, in some instances, eliminate DELPHIs` capability to correctly output some of the earlier optional tables. This monologue is intended to compliment the archived printout, and to provide enough insight so that someone unfamiliar with the techniques of Gas Diagnostics can retrieve the results at some future date. DELPHI last ran on the CDC-7600 machines, and was not converted to run on the Crays when the CDC-7600`s were decommissioned. DELPHI accepted data from various analytical systems, set up data summary tables, and combined preshot tracer and detector data with these results to calculate the total production of measured species and the indicated fission yields and detector conversions.« less

  9. Verification of a Quality Management Theory: Using a Delphi Study

    PubMed Central

    Mosadeghrad, Ali Mohammad

    2013-01-01

    Background: A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. Methods: The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. Results: The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. Conclusion: A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence. PMID:24596883

  10. Use of the Delphi method for determining community growth goals inventory: the Nashville experience

    Treesearch

    Vishwa K. Varma

    1977-01-01

    The author discusses the growth-inducing pressures on Nashville, Tennessee, describes the application of the Delphi technique to develop an inventory of the community's growth goals, and suggests that the development of a list of community goals is a necessary first step toward growth management.

  11. Emergent fuzzy geometry and fuzzy physics in four dimensions

    NASA Astrophysics Data System (ADS)

    Ydri, Badis; Rouag, Ahlam; Ramda, Khaled

    2017-03-01

    A detailed Monte Carlo calculation of the phase diagram of bosonic mass-deformed IKKT Yang-Mills matrix models in three and six dimensions with quartic mass deformations is given. Background emergent fuzzy geometries in two and four dimensions are observed with a fluctuation given by a noncommutative U (1) gauge theory very weakly coupled to normal scalar fields. The geometry, which is determined dynamically, is given by the fuzzy spheres SN2 and SN2 × SN2 respectively. The three and six matrix models are effectively in the same universality class. For example, in two dimensions the geometry is completely stable, whereas in four dimensions the geometry is stable only in the limit M ⟶ ∞, where M is the mass of the normal fluctuations. The behaviors of the eigenvalue distribution in the two theories are also different. We also sketch how we can obtain a stable fuzzy four-sphere SN2 × SN2 in the large N limit for all values of M as well as models of topology change in which the transition between spheres of different dimensions is observed. The stable fuzzy spheres in two and four dimensions act precisely as regulators which is the original goal of fuzzy geometry and fuzzy physics. Fuzzy physics and fuzzy field theory on these spaces are briefly discussed.

  12. 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.

  13. Fuzzy simulation in concurrent engineering

    NASA Technical Reports Server (NTRS)

    Kraslawski, A.; Nystrom, L.

    1992-01-01

    Concurrent engineering is becoming a very important practice in manufacturing. A problem in concurrent engineering is the uncertainty associated with the values of the input variables and operating conditions. The problem discussed in this paper concerns the simulation of processes where the raw materials and the operational parameters possess fuzzy characteristics. The processing of fuzzy input information is performed by the vertex method and the commercial simulation packages POLYMATH and GEMS. The examples are presented to illustrate the usefulness of the method in the simulation of chemical engineering processes.

  14. Fuzzy logic control of telerobot manipulators

    NASA Technical Reports Server (NTRS)

    Franke, Ernest A.; Nedungadi, Ashok

    1992-01-01

    Telerobot systems for advanced applications will require manipulators with redundant 'degrees of freedom' (DOF) that are capable of adapting manipulator configurations to avoid obstacles while achieving the user specified goal. Conventional methods for control of manipulators (based on solution of the inverse kinematics) cannot be easily extended to these situations. Fuzzy logic control offers a possible solution to these needs. A current research program at SRI developed a fuzzy logic controller for a redundant, 4 DOF, planar manipulator. The manipulator end point trajectory can be specified by either a computer program (robot mode) or by manual input (teleoperator). The approach used expresses end-point error and the location of manipulator joints as fuzzy variables. Joint motions are determined by a fuzzy rule set without requiring solution of the inverse kinematics. Additional rules for sensor data, obstacle avoidance and preferred manipulator configuration, e.g., 'righty' or 'lefty', are easily accommodated. The procedure used to generate the fuzzy rules can be extended to higher DOF systems.

  15. 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.

  16. 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).

  17. The Policy Delphi: A Method for Identifying Intended and Unintended Consequences of Educational Policy

    ERIC Educational Resources Information Center

    Manley, R. Adam

    2013-01-01

    This article highlights a rarely utilized but effective technique for identifying intended and unintended consequences of past or current policy or policy change. The author guides the reader through the process of identifying potential participants, contacting participants, developing the policy Delphi instrument, and analyzing the findings by…

  18. Fuzzy set methods for object recognition in space applications

    NASA Technical Reports Server (NTRS)

    Keller, James M.

    1991-01-01

    Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

  19. Nonlinear Performance Seeking Control using Fuzzy Model Reference Learning Control and the Method of Steepest Descent

    NASA Technical Reports Server (NTRS)

    Kopasakis, George

    1997-01-01

    Performance Seeking Control (PSC) attempts to find and control the process at the operating condition that will generate maximum performance. In this paper a nonlinear multivariable PSC methodology will be developed, utilizing the Fuzzy Model Reference Learning Control (FMRLC) and the method of Steepest Descent or Gradient (SDG). This PSC control methodology employs the SDG method to find the operating condition that will generate maximum performance. This operating condition is in turn passed to the FMRLC controller as a set point for the control of the process. The conventional SDG algorithm is modified in this paper in order for convergence to occur monotonically. For the FMRLC control, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for effective tuning of the FMRLC controller.

  20. Alternative method of highway traffic safety analysis for developing countries using delphi technique and Bayesian network.

    PubMed

    Mbakwe, Anthony C; Saka, Anthony A; Choi, Keechoo; Lee, Young-Jae

    2016-08-01

    Highway traffic accidents all over the world result in more than 1.3 million fatalities annually. An alarming number of these fatalities occurs in developing countries. There are many risk factors that are associated with frequent accidents, heavy loss of lives, and property damage in developing countries. Unfortunately, poor record keeping practices are very difficult obstacle to overcome in striving to obtain a near accurate casualty and safety data. In light of the fact that there are numerous accident causes, any attempts to curb the escalating death and injury rates in developing countries must include the identification of the primary accident causes. This paper, therefore, seeks to show that the Delphi Technique is a suitable alternative method that can be exploited in generating highway traffic accident data through which the major accident causes can be identified. In order to authenticate the technique used, Korea, a country that underwent similar problems when it was in its early stages of development in addition to the availability of excellent highway safety records in its database, is chosen and utilized for this purpose. Validation of the methodology confirms the technique is suitable for application in developing countries. Furthermore, the Delphi Technique, in combination with the Bayesian Network Model, is utilized in modeling highway traffic accidents and forecasting accident rates in the countries of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Evaluation of B2C website based on the usability factors by using fuzzy AHP & hierarchical fuzzy TOPSIS

    NASA Astrophysics Data System (ADS)

    Masudin, I.; Saputro, T. E.

    2016-02-01

    In today's technology, electronic trading transaction via internet has been utilized properly with rapid growth. This paper intends to evaluate related to B2C e-commerce website in order to find out the one which meets the usability factors better than another. The influential factors to B2C e-commerce website are determined for two big retailer websites. The factors are investigated based on the consideration of several studies and conformed to the website characteristics. The evaluation is conducted by using different methods namely fuzzy AHP and hierarchical fuzzy TOPSIS so that the final evaluation can be compared. Fuzzy triangular number is adopted to deal with imprecise judgment under fuzzy environment.

  2. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

    SciTech Connect

    Liu, Hu-Chen; Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552; Wu, Jing

    Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires considerationmore » of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.« less

  3. Scientific framework for research on disaster and mass casualty incident in Korea: building consensus using Delphi method.

    PubMed

    Kim, Chu Hyun; Park, Ju Ok; Park, Chang Bae; Kim, Seong Chun; Kim, Soo Jin; Hong, Ki Jeong

    2014-01-01

    We aimed to determine the scientific framework for research on disaster and mass casualty incident (MCI) in Korea, especially Korean terminology, feasible definition, and epidemiologic indices. The two staged policy Delphi method was performed by instructors of National Disaster Life Support (NDLS®) with the constructed questionnaire containing items based on the literature review. The first-stage survey was conducted by 11 experts through two rounds of survey for making issue and option. The second-stage survey was conducted by 35 experts for making a generalized group based consensus. Experts were selected among instructors of National Disaster Life Support Course. Through two staged Delphi survey experts made consensus: 1) the Korean terminology "jaenan" with "disaster" and "dajung-sonsang-sago" with "MCI"; 2) the feasible definition of "disaster" as the events that have an effect on one or more municipal local government area (city-county-district) or results in ≥ 10 of death or ≥ 50 injured victims; 3) the feasible definition of MCI as the events that result in ≥ 6 casualties including death; 4) essential 31 epidemiologic indices. Experts could determine the scientific framework in Korea for research on disaster medicine, considering the distinct characteristics of Korea and current research trends.

  4. 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.

  5. A Delphi Investigation into the Research Needs in Swedish Librarianship

    ERIC Educational Resources Information Center

    Maceviciute, Elena; Wilson, T. D.

    2009-01-01

    Introduction: Reports the conduct of a national survey in Sweden to establish the desired research priorities for libraries. The research sought to establish what evidence-base is needed for evidence-based practice. Method: The Delphi method was employed to solicit opinions on the kinds of research needed by libraries of all kinds in Sweden.…

  6. Fuzzy Subspace Clustering

    NASA Astrophysics Data System (ADS)

    Borgelt, Christian

    In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to transfer an alternative to the fuzzifier (Klawonn and Höppner, What is fuzzy about fuzzy clustering? Understanding and improving the concept of the fuzzifier, In: Proc. 5th Int. Symp. on Intelligent Data Analysis, 254-264, Springer, Berlin, 2003) to attribute weighting fuzzy clustering (Keller and Klawonn, Int J Uncertain Fuzziness Knowl Based Syst 8:735-746, 2000). In addition, by reformulating Gustafson-Kessel fuzzy clustering, a scheme for weighting and selecting principal axes can be obtained. While in Borgelt (Feature weighting and feature selection in fuzzy clustering, In: Proc. 17th IEEE Int. Conf. on Fuzzy Systems, IEEE Press, Piscataway, NJ, 2008) I already presented such an approach for a global selection of attributes and principal axes, this paper extends it to a cluster-specific selection, thus arriving at a fuzzy subspace clustering algorithm (Parsons, Haque, and Liu, 2004).

  7. Incorporating Information Value into Navy Tactical Data System: System Configuration Management Through the Delphi Method

    DTIC Science & Technology

    1989-03-01

    e"-s tcc,: -e .- r reverse of necessary an., ice-tfy by bi.-:’ ru-’ce," 5uz"ou configuration management. Delphi method. Command and Control 19 Ac-s:’a...Aos!,ac: 21 Aostraczt Security Classitcator : R uncassf~’! i~e sa-e as renc- E 0orC users Unclassified 22a Na-e of Respon’s :e iro, v c a 22o Te’eo’one...i!r’ciule A’ea coce’ 22: C’" ce . Thomnas 1’. Mitchell (4081 646-2620 155k.11i DD FORI, 1473.6.: VAR 63 A-- R e-.!c- rnay be usec~ unti exhausted se

  8. Examining the Roles of Blended Learning Approaches in Computer-Supported Collaborative Learning (CSCL) Environments: A Delphi Study

    ERIC Educational Resources Information Center

    So, Hyo-Jeong; Bonk, Curtis J.

    2010-01-01

    In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…

  9. Determination of Problematic ICD-9-CM Subcategories for Further Study of Coding Performance: Delphi Method

    PubMed Central

    Zeng, Xiaoming; Bell, Paul D

    2011-01-01

    In this study, we report on a qualitative method known as the Delphi method, used in the first part of a research study for improving the accuracy and reliability of ICD-9-CM coding. A panel of independent coding experts interacted methodically to determine that the three criteria to identify a problematic ICD-9-CM subcategory for further study were cost, volume, and level of coding confusion caused. The Medicare Provider Analysis and Review (MEDPAR) 2007 fiscal year data set as well as suggestions from the experts were used to identify coding subcategories based on cost and volume data. Next, the panelists performed two rounds of independent ranking before identifying Excisional Debridement as the subcategory that causes the most confusion among coders. As a result, they recommended it for further study aimed at improving coding accuracy and variation. This framework can be adopted at different levels for similar studies in need of a schema for determining problematic subcategories of code sets. PMID:21796264

  10. Anatomical Society core regional anatomy syllabus for undergraduate medicine: the Delphi process.

    PubMed

    Smith, C F; Finn, G M; Stewart, J; McHanwell, S

    2016-01-01

    A modified Delphi method was employed to seek consensus when revising the UK and Ireland's core syllabus for regional anatomy in undergraduate medicine. A Delphi panel was constructed involving 'expert' (individuals with at least 5 years' experience in teaching medical students anatomy at the level required for graduation). The panel (n = 39) was selected and nominated by members of Council and/or the Education Committee of the Anatomical Society and included a range of specialists including surgeons, radiologists and anatomists. The experts were asked in two stages to 'accept', 'reject' or 'modify' (first stage only) each learning outcome. A third stage, which was not part of the Delphi method, then allowed the original authors of the syllabus to make changes either to correct any anatomical errors or to make minor syntax changes. From the original syllabus of 182 learning outcomes, removing the neuroanatomy component (163), 23 learning outcomes (15%) remained unchanged, seven learning outcomes were removed and two new learning outcomes added. The remaining 133 learning outcomes were modified. All learning outcomes on the new core syllabus achieved over 90% acceptance by the panel. © 2015 Anatomical Society.

  11. Proposing integrated Shannon's entropy-inverse data envelopment analysis methods for resource allocation problem under a fuzzy environment

    NASA Astrophysics Data System (ADS)

    Çakır, Süleyman

    2017-10-01

    In this study, a two-phase methodology for resource allocation problems under a fuzzy environment is proposed. In the first phase, the imprecise Shannon's entropy method and the acceptability index are suggested, for the first time in the literature, to select input and output variables to be used in the data envelopment analysis (DEA) application. In the second step, an interval inverse DEA model is executed for resource allocation in a short run. In an effort to exemplify the practicality of the proposed fuzzy model, a real case application has been conducted involving 16 cement firms listed in Borsa Istanbul. The results of the case application indicated that the proposed hybrid model is a viable procedure to handle input-output selection and resource allocation problems under fuzzy conditions. The presented methodology can also lend itself to different applications such as multi-criteria decision-making problems.

  12. 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.

  13. 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.

  14. 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.

  15. A new method of regional eco-environmental quality assessment and its application.

    PubMed

    Wang, Xiaodan; Cao, Yingzi; Zhong, Xianghao; Gao, Pan

    2012-01-01

    Eco-environmental quality assessment (EQA) is an intricate and challenging task that must take into account numerous natural, economic, political, and social factors, which are subject to multiple conflicting criteria. In this paper, a methodological reference framework is developed for EQA that combines the fuzzy Delphi method (FDM) and fuzzy analytical hierarchy process (FAHP) with a geographic information system (GIS). The proposed method significantly improves the accuracy and reliability of evaluation results through the incorporation of fuzzy set theory. A GIS not only has the ability to store and analyze large amounts of spatial data from different sources but also provides a consistent visualization environment for displaying the input data and the results of EQA. Furthermore, unlike prior EQAs, the proposed method can support the dynamic estimation of regional eco-environmental quality by updating historical spatiotemporal data at little additional cost. A case study is presented for the western Tibetan Plateau. The study results show that worse, bad, and moderate eco-environmental quality classes comprised 16.58, 20.15, and 24.84% of the total area, respectively. Good and better eco-environmental quality classes accounted for 38.43%. This result indicates that nearly 62% of the total area is eco-environmentally vulnerable. The results verified the usefulness and feasibility of the proposed method. The EQA can also help local managers make scientifically based and effective decisions about Tibetan eco-environmental protection and land use. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  16. A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

    PubMed

    Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

    2018-02-19

    The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

  17. Achieving 90% Adoption of Clinical Practice Guidelines Using the Delphi Consensus Method in a Large Orthopedic Group.

    PubMed

    Bini, Stefano A; Mahajan, John

    2016-11-01

    Little is known about the implementation rate of clinical practice guidelines (CPGs). Our purpose was to report on the adoption rate of CPGs created and implemented by a large orthopedic group using the Delphi consensus method. The draft CPGs were created before the group's annual meeting by 5 teams each assigned a subset of topics. The draft guidelines included a statement and a summary of the available evidence. Each guideline was debated in both small-group and plenary sessions. Voting was anonymous and a 75% supermajority was required for passage. A Likert scale was used to survey the patient's experience with the process at 1 week, and the Kirkpatrick evaluation model was used to gauge the efficacy of the process over a 6-month time frame. Eighty-five orthopedic surgeons attended the meeting. Fifteen guidelines grouped into 5 topics were created. All passed. Eighty-six percent of attendees found the process effective and 84% felt that participating in the process made it more likely that they would adopt the guidelines. At 1 week, an average of 62% of attendees stated they were practicing the guideline as written (range: 35%-72%), and at 6 months, 96% stated they were practicing them (range: 82%-100%). We have demonstrated that a modified Delphi method for reaching consensus can be very effective in both creating CPGs and leading to their adoption. Further we have shown that the process is well received by participants and that an inclusionary approach can be highly successful. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Remediation System Evaluation, Delphi Corporation Site in Vandalia, Ohio

    EPA Pesticide Factsheets

    This RSE pertains to aspects of the corrective action underway at two neighboring plants, the Delphi Energy and Chassis Systems Plant and Delphi Safety and Interior Systems Plant, collectively referred to as the “facility” in this report.

  19. Helping Competencies of Student Affairs Professionals: A Delphi Study

    ERIC Educational Resources Information Center

    Reynolds, Amy L.

    2011-01-01

    The purpose of this study was to gather student affairs professionals' perceptions of the knowledge and skills needed to effectively help students. Using the Delphi method, 159 entry-level and mid-level student affairs administrators from institutions across the United States were surveyed regarding their perceptions of the helping skills they use…

  20. 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.

  1. 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.

  2. 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.

  3. Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

    NASA Astrophysics Data System (ADS)

    Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

    2018-04-01

    Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

  4. Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

    NASA Astrophysics Data System (ADS)

    Shah, Mazlina Muzafar; Wahab, Abdul Fatah

    2017-08-01

    Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

  5. Using the Delphi Technique to Support Curriculum Development

    ERIC Educational Resources Information Center

    Sitlington, Helen Barbara; Coetzer, Alan John

    2015-01-01

    Purpose: The purpose of this paper is to present an analysis of the use of the Delphi technique to support curriculum development with a view to enhancing existing literature on use of the technique for renewal of business course curricula. Design/methodology/approach: The authors outline the Delphi process for obtaining consensus amongst a…

  6. Identifying the features of an exercise addiction: A Delphi study

    PubMed Central

    Macfarlane, Lucy; Owens, Glynn; Cruz, Borja del Pozo

    2016-01-01

    Objectives There remains limited consensus regarding the definition and conceptual basis of exercise addiction. An understanding of the factors motivating maintenance of addictive exercise behavior is important for appropriately targeting intervention. The aims of this study were twofold: first, to establish consensus on features of an exercise addiction using Delphi methodology and second, to identify whether these features are congruous with a conceptual model of exercise addiction adapted from the Work Craving Model. Methods A three-round Delphi process explored the views of participants regarding the features of an exercise addiction. The participants were selected from sport and exercise relevant domains, including physicians, physiotherapists, coaches, trainers, and athletes. Suggestions meeting consensus were considered with regard to the proposed conceptual model. Results and discussion Sixty-three items reached consensus. There was concordance of opinion that exercising excessively is an addiction, and therefore it was appropriate to consider the suggestions in light of the addiction-based conceptual model. Statements reaching consensus were consistent with all three components of the model: learned (negative perfectionism), behavioral (obsessive–compulsive drive), and hedonic (self-worth compensation and reduction of negative affect and withdrawal). Conclusions Delphi methodology allowed consensus to be reached regarding the features of an exercise addiction, and these features were consistent with our hypothesized conceptual model of exercise addiction. This study is the first to have applied Delphi methodology to the exercise addiction field, and therefore introduces a novel approach to exercise addiction research that can be used as a template to stimulate future examination using this technique. PMID:27554504

  7. 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.

  8. 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

  9. 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.

  10. Fuzzy architecture assessment for critical infrastructure resilience

    SciTech Connect

    Muller, George

    2012-12-01

    This paper presents an approach for the selection of alternative architectures in a connected infrastructure system to increase resilience of the overall infrastructure system. The paper begins with a description of resilience and critical infrastructure, then summarizes existing approaches to resilience, and presents a fuzzy-rule based method of selecting among alternative infrastructure architectures. This methodology includes considerations which are most important when deciding on an approach to resilience. The paper concludes with a proposed approach which builds on existing resilience architecting methods by integrating key system aspects using fuzzy memberships and fuzzy rule sets. This novel approach aids the systemsmore » architect in considering resilience for the evaluation of architectures for adoption into the final system architecture.« less

  11. 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.

  12. Application of fuzzy system theory in addressing the presence of uncertainties

    SciTech Connect

    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

  13. 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.

  14. Stock and option portfolio using fuzzy logic approach

    NASA Astrophysics Data System (ADS)

    Sumarti, Novriana; Wahyudi, Nanang

    2014-03-01

    Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

  15. Habitat suitability index curves for paddlefish, developed by the delphi technique

    USGS Publications Warehouse

    Crance, John H.

    1987-01-01

    A Delphi exercise conducted with a panel of 11 experts on paddlefish (Polyodon spathula) and an evaluator resulted in 14 riverine habitat suitability index curves associating various life stages or activities of paddlefish with four variables: velocity, depth, substrate type, and temperature. The panel reached a consensus on six of the curves and eight to 10 panelists agreed on the others. Several panelists reported that they found the Delphi exercise to be a good learning experience, and they believed the technique is an appropriate interim method for developing suitability index curves when available data are inadequate for more conventional statistical analyses. Documentation of good paddlefish spawning habitat was the data need most commonly identified by the panelists.

  16. 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.

  17. Learning and tuning fuzzy logic controllers through reinforcements

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.; Khedkar, Pratap

    1992-01-01

    This paper presents a new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system. In particular, our generalized approximate reasoning-based intelligent control (GARIC) architecture (1) learns and tunes a fuzzy logic controller even when only weak reinforcement, 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 neural network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto et al. (1983) to include the prior control knowledge of human operators. 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.

  18. 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

  19. 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.

  20. A Delphi Study and Initial Validation of Counselor Supervision Competencies

    ERIC Educational Resources Information Center

    Neuer Colburn, Anita A.; Grothaus, Tim; Hays, Danica G.; Milliken, Tammi

    2016-01-01

    The authors addressed the lack of supervision training standards for doctoral counseling graduates by developing and validating an initial list of supervision competencies. They used content analysis, Delphi polling, and content validity methods to generate a list, vetted by 2 different panels of supervision experts, of 33 competencies grouped…

  1. 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.

  2. Identifying Threshold Concepts for Information Literacy: A Delphi Study

    ERIC Educational Resources Information Center

    Townsend, Lori; Hofer, Amy R.; Hanick, Silvia Lin; Brunetti, Korey

    2016-01-01

    This study used the Delphi method to engage expert practitioners on the topic of threshold concepts--core ideas and processes in a discipline that students need to grasp in order to progress in their learning, but that are often unspoken or unrecognized by expert practitioners--for information literacy. A panel of experts considered two questions:…

  3. Generalized fuzzy C-means clustering algorithm with improved fuzzy partitions.

    PubMed

    Zhu, Lin; Chung, Fu-Lai; Wang, Shitong

    2009-06-01

    The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithms, and it should not be forced to fix at the usual value m = 2. In view of its distinctive features in applications and its limitation in having m = 2 only, a recent advance of fuzzy clustering called fuzzy c-means clustering with improved fuzzy partitions (IFP-FCM) is extended in this paper, and a generalized algorithm called GIFP-FCM for more effective clustering is proposed. By introducing a novel membership constraint function, a new objective function is constructed, and furthermore, GIFP-FCM clustering is derived. Meanwhile, from the viewpoints of L(p) norm distance measure and competitive learning, the robustness and convergence of the proposed algorithm are analyzed. Furthermore, the classical fuzzy c-means algorithm (FCM) and IFP-FCM can be taken as two special cases of the proposed algorithm. Several experimental results including its application to noisy image texture segmentation are presented to demonstrate its average advantage over FCM and IFP-FCM in both clustering and robustness capabilities.

  4. Introduction to Fuzzy Set Theory

    NASA Technical Reports Server (NTRS)

    Kosko, Bart

    1990-01-01

    An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

  5. Fuzzy set methods for object recognition in space applications

    NASA Technical Reports Server (NTRS)

    Keller, James M.

    1991-01-01

    During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.

  6. What procedure to choose while designing a fuzzy control? Towards mathematical foundations of fuzzy control

    NASA Technical Reports Server (NTRS)

    Kreinovich, Vladik YA.; Quintana, Chris; Lea, Robert

    1991-01-01

    Fuzzy control has been successfully applied in industrial systems. However, there is some caution in using it. The reason is that it is based on quite reasonable ideas, but each of these ideas can be implemented in several different ways, and depending on which of the implementations chosen different results are achieved. Some implementations lead to a high quality control, some of them not. And since there are no theoretical methods for choosing the implementation, the basic way to choose it now is experimental. But if one chooses a method that is good for several examples, there is no guarantee that it will work fine in all of them. Hence the caution. A theoretical basis for choosing the fuzzy control procedures is provided. In order to choose a procedure that transforms a fuzzy knowledge into a control, one needs, first, to choose a membership function for each of the fuzzy terms that the experts use, second, to choose operations of uncertainty values that corresponds to 'and' and 'or', and third, when a membership function for control is obtained, one must defuzzy it, that is, somehow generate a value of the control u that will be actually used. A general approach that will help to make all these choices is described: namely, it is proved that under reasonable assumptions membership functions should be linear or fractionally linear, defuzzification must be described by a centroid rule and describe all possible 'and' and 'or' operations. Thus, a theoretical explanation of the existing semi-heuristic choices is given and the basis for the further research on optimal fuzzy control is formulated.

  7. 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

  8. 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.

  9. Mamdani Fuzzy System for Indoor Autonomous Mobile Robot

    NASA Astrophysics Data System (ADS)

    Khan, M. K. A. Ahamed; Rashid, Razif; Elamvazuthi, I.

    2011-06-01

    Several control algorithms for autonomous mobile robot navigation have been proposed in the literature. Recently, the employment of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, Mamdani fuzzy system for an autonomous mobile robot is developed. The paper begins with the discussion on the conventional controller and then followed by the description of fuzzy logic controller in detail.

  10. Verification of a quality management theory: using a delphi study.

    PubMed

    Mosadeghrad, Ali Mohammad

    2013-11-01

    A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence.

  11. Adaptive neuro fuzzy inference system-based power estimation method for CMOS VLSI circuits

    NASA Astrophysics Data System (ADS)

    Vellingiri, Govindaraj; Jayabalan, Ramesh

    2018-03-01

    Recent advancements in very large scale integration (VLSI) technologies have made it feasible to integrate millions of transistors on a single chip. This greatly increases the circuit complexity and hence there is a growing need for less-tedious and low-cost power estimation techniques. The proposed work employs Back-Propagation Neural Network (BPNN) and Adaptive Neuro Fuzzy Inference System (ANFIS), which are capable of estimating the power precisely for the complementary metal oxide semiconductor (CMOS) VLSI circuits, without requiring any knowledge on circuit structure and interconnections. The ANFIS to power estimation application is relatively new. Power estimation using ANFIS is carried out by creating initial FIS modes using hybrid optimisation and back-propagation (BP) techniques employing constant and linear methods. It is inferred that ANFIS with the hybrid optimisation technique employing the linear method produces better results in terms of testing error that varies from 0% to 0.86% when compared to BPNN as it takes the initial fuzzy model and tunes it by means of a hybrid technique combining gradient descent BP and mean least-squares optimisation algorithms. ANFIS is the best suited for power estimation application with a low RMSE of 0.0002075 and a high coefficient of determination (R) of 0.99961.

  12. Incomplete fuzzy data processing systems using artificial neural network

    NASA Technical Reports Server (NTRS)

    Patyra, Marek J.

    1992-01-01

    In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

  13. Terminology and definitions on groin pain in athletes: building agreement using a short Delphi method.

    PubMed

    Weir, Adam; Hölmich, Per; Schache, Anthony G; Delahunt, Eamonn; de Vos, Robert-Jan

    2015-06-01

    Groin pain in athletes occurs frequently and can be difficult to treat, which may partly be due to the lack of agreement on diagnostic terminology. To perform a short Delphi survey on terminology agreement for groin pain in athletes by a group of experts. A selected number of experts were invited to participate in a Delphi questionnaire. The study coordinator sent a questionnaire, which consisted of demographic questions and two 'real-life' case reports of athletes with groin pain. The experts were asked to complete the questionnaire and to provide the most likely diagnosis for each case. Questionnaire responses were analysed by an independent researcher. The Cohen's κ statistic was used to evaluate the level of agreement between the diagnostic terms provided by the experts. Twenty-three experts participated (96% of those invited). For case 1, experts provided 9 different terms to describe the most likely diagnosis; for case 2, 11 different terms were provided to describe the most likely diagnosis. With respect to the terms provided for the most likely diagnosis, the Cohen's κ was 0.06 and 0.002 for case 1 and 2, respectively. This heterogeneous taxonomy reflects only a slight agreement between the various diagnostic terms provided by the selected experts. This short Delphi survey of two 'typical, straightforward' cases demonstrated major inconsistencies in the diagnostic terminology used by experts for groin pain in athletes. These results underscore the need for consensus on definitions and terminology on groin pain in athletes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  14. Train repathing in emergencies based on fuzzy linear programming.

    PubMed

    Meng, Xuelei; Cui, Bingmou

    2014-01-01

    Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

  15. Using the Delphi technique in economic evaluation: time to revisit the oracle?

    PubMed

    Simoens, S

    2006-12-01

    Although the Delphi technique has been commonly used as a data source in medical and health services research, its application in economic evaluation of medicines has been more limited. The aim of this study was to describe the methodology of the Delphi technique, to present a case for using the technique in economic evaluation, and to provide recommendations to improve such use. The literature was accessed through MEDLINE focusing on studies discussing the methodology of the Delphi technique and economic evaluations of medicines using the Delphi technique. The Delphi technique can be used to provide estimates of health care resources required and to modify such estimates when making inter-country comparisons. The Delphi technique can also contribute to mapping the treatment process under investigation, to identifying the appropriate comparator to be used, and to ensuring that the economic evaluation estimates cost-effectiveness rather than cost-efficacy. Ideally, economic evaluations of medicines should be based on real-patient data. In the absence of such data, evaluations need to incorporate the best evidence available by employing approaches such as the Delphi technique. Evaluations based on this approach should state the limitations, and explore the impact of the associated uncertainty in the results.

  16. Constructing post-surgical discharge instructions through a Delphi consensus methodology.

    PubMed

    Scott, Aaron R; Sanderson, Cody J; Rush, Augustus J; Alore, Elizabeth A; Naik, Aanand D; Berger, David H; Suliburk, James W

    2018-05-01

    Patient education materials are a crucial part of physician-patient communication. We hypothesize that available discharge instructions are difficult to read and fail to address necessary topics. Our objective is to evaluate readability and content of surgical discharge instructions using thyroidectomy to develop standardized discharge materials. Thyroidectomy discharge materials were analyzed for readability and assessed for content. Fifteen endocrine surgeons participated in a modified Delphi consensus panel to select necessary topics. Using readability best practices, we created standardized discharge instructions which included all selected topics. The panel evaluated 40 topics, selected 23, deemed 4 inappropriate, consolidated 5, and did not reach consensus on 8 topics after 4 rounds. The evaluated instructions' reading levels ranged from grade 6.5 to 13.2; none contained all consensus topics. Current post surgical thyroidectomy discharge instructions are more difficult to read than recommended by literacy standards and omit consensus warning signs of major complications. Our easy-to-read discharge instructions cover pertinent topics and may enhance patient education. Delphi methodology is useful for developing post-surgical instructions. Patient education materials need appropriate readability levels and content. We recommend the Delphi method to select content using consensus expert opinion whenever higher level data is lacking. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Fuzzy Arden Syntax: A fuzzy programming language for medicine.

    PubMed

    Vetterlein, Thomas; Mandl, Harald; Adlassnig, Klaus-Peter

    2010-05-01

    The programming language Arden Syntax has been optimised for use in clinical decision support systems. We describe an extension of this language named Fuzzy Arden Syntax, whose original version was introduced in S. Tiffe's dissertation on "Fuzzy Arden Syntax: Representation and Interpretation of Vague Medical Knowledge by Fuzzified Arden Syntax" (Vienna University of Technology, 2003). The primary aim is to provide an easy means of processing vague or uncertain data, which frequently appears in medicine. For both propositional and number data types, fuzzy equivalents have been added to Arden Syntax. The Boolean data type was generalised to represent any truth degree between the two extremes 0 (falsity) and 1 (truth); fuzzy data types were introduced to represent fuzzy sets. The operations on truth values and real numbers were generalised accordingly. As the conditions to decide whether a certain programme unit is executed or not may be indeterminate, a Fuzzy Arden Syntax programme may split. The data in the different branches may be optionally aggregated subsequently. Fuzzy Arden Syntax offers the possibility to formulate conveniently Medical Logic Modules (MLMs) based on the principle of a continuously graded applicability of statements. Furthermore, ad hoc decisions about sharp value boundaries can be avoided. As an illustrative example shows, an MLM making use of the features of Fuzzy Arden Syntax is not significantly more complex than its Arden Syntax equivalent; in the ideal case, a programme handling crisp data remains practically unchanged when compared to its fuzzified version. In the latter case, the output data, which can be a set of weighted alternatives, typically depends continuously from the input data. In typical applications an Arden Syntax MLM can produce a different output after only slight changes of the input; discontinuities are in fact unavoidable when the input varies continuously but the output is taken from a discrete set of possibilities

  18. A Delphi-matrix approach to SEA and its application within the tourism sector in Taiwan

    SciTech Connect

    Kuo, N.-W.; Hsiao, T.-Y.; Yu, Y.-H.

    Strategic Environmental Assessment (SEA) is a procedural tool and within the framework of SEA, several different types of analytical methods can be used in the assessment. However, the impact matrix used currently in Taiwan has some disadvantages. Hence, a Delphi-matrix approach to SEA is proposed here to improve the performance of Taiwan's SEA. This new approach is based on the impact matrix combination with indicators of sustainability, and then the Delphi method is employed to collect experts' opinions. In addition, the assessment of National Floriculture Park Plan and Taiwan Flora 2008 Program is taken as an example to examine thismore » new method. Although international exhibition is one of the important tourism (economic) activities, SEA is seldom about tourism sector. Finally, the Delphi-matrix approach to SEA for tourism development plan is established containing eight assessment topics and 26 corresponding categories. In summary, three major types of impacts: resources' usages, pollution emissions, and local cultures change are found. Resources' usages, such as water, electricity, and natural gas demand, are calculated on a per capita basis. Various forms of pollution resulting from this plan, such as air, water, soil, waste, and noise, are also identified.« less

  19. Effective self-management strategies for bipolar disorder: A community-engaged Delphi Consensus Consultation study.

    PubMed

    Michalak, Erin E; Suto, Melinda J; Barnes, Steven J; Hou, Sharon; Lapsley, Sara; Scott, Mike W; Murray, Greg; Austin, Jehannine; Elliott, Nusha Balram; Berk, Lesley; Crest Bd

    2016-12-01

    Self-management represents an important complement to psychosocial treatments for bipolar disorder (BD), but research is limited. Specifically, little is known about self-management approaches for elevated mood states; this study investigated self-management strategies for: (1) maintaining balance in mood, and (2) stopping progression into hypomania/mania. To identify the common components of BD self-management, Delphi Consensus Consultation methods were combined with a Community-Based Participatory Research (CBPR) approach across five study phases: (1) Qualitative dataset content analysis; (2) Academic/grey literature reviews; (3) Content analysis; (4) Two Delphi rounds (rating strategies on a 5-point Likert scale, Very Unhelpful-Very Helpful), and; (5) Quantitative analysis and interpretation. Participants were people with BD and healthcare providers. Phases 1 and 2 identified 262 and 3940 candidate strategies, respectively; 3709 were discarded as duplicates/unintelligible. The remaining 493 were assessed via Delphi methods in Phase 4: 101 people with BD and 52 healthcare providers participated in Round 1; 83 of the BD panel (82%) and 43 of the healthcare provider panel (83%) participated in Round 2-exploratory factor analysis (EFA) was conducted on Round 2 results. EFA was underpowered and sample was not ethnically diverse, limiting generalizability. High concordance was observed in ratings of strategy effectiveness between the two panels. Future research could usefully investigate the provisional discovery here of underlying factors which link individual strategies. For example, 'maintaining hope' underpinned strategies for maintaining balance, and 'decreasing use of stimulants' underpinned strategies to interrupt hypo/manic ascent. There is merit in combining CBPR and Delphi methods. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Fuzzy Neural Networks for Decision Support in Negotiation

    SciTech Connect

    Sakas, D. P.; Vlachos, D. S.; Simos, T. E.

    There is a large number of parameters which one can take into account when building a negotiation model. These parameters in general are uncertain, thus leading to models which represents them with fuzzy sets. On the other hand, the nature of these parameters makes them very difficult to model them with precise values. During negotiation, these parameters play an important role by altering the outcomes or changing the state of the negotiators. One reasonable way to model this procedure is to accept fuzzy relations (from theory or experience). The action of these relations to fuzzy sets, produce new fuzzy setsmore » which describe now the new state of the system or the modified parameters. But, in the majority of these situations, the relations are multidimensional, leading to complicated models and exponentially increasing computational time. In this paper a solution to this problem is presented. The use of fuzzy neural networks is shown that it can substitute the use of fuzzy relations with comparable results. Finally a simple simulation is carried in order to test the new method.« less

  1. 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.

  2. 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.

  3. Homotopy perturbation method: a versatile tool to evaluate linear and nonlinear fuzzy Volterra integral equations of the second kind.

    PubMed

    Narayanamoorthy, S; Sathiyapriya, S P

    2016-01-01

    In this article, we focus on linear and nonlinear fuzzy Volterra integral equations of the second kind and we propose a numerical scheme using homotopy perturbation method (HPM) to obtain fuzzy approximate solutions to them. To facilitate the benefits of this proposal, an algorithmic form of the HPM is also designed to handle the same. In order to illustrate the potentiality of the approach, two test problems are offered and the obtained numerical results are compared with the existing exact solutions and are depicted in terms of plots to reveal its precision and reliability.

  4. A checklist to assess the quality of reports on spa therapy and balneotherapy trials was developed using the Delphi consensus method: the SPAC checklist.

    PubMed

    Kamioka, Hiroharu; Kawamura, Yoichi; Tsutani, Kiichiro; Maeda, Masaharu; Hayasaka, Shinya; Okuizum, Hiroyasu; Okada, Shinpei; Honda, Takuya; Iijima, Yuichi

    2013-08-01

    The purpose of this study was to develop a checklist of items that describes and measures the quality of reports of interventional trials assessing spa therapy. The Delphi consensus method was used to select the number of items in the checklist. A total of eight individuals participated, including an epidemiologist, a clinical research methodologist, clinical researchers, a medical journalist, and a health fitness programmer. Participants ranked on a 9-point Likert scale whether an item should be included in the checklist. Three rounds of the Delphi method were conducted to achieve consensus. The final checklist contained 19 items, with items related to title, place of implementation (specificity of spa), care provider influence, and additional measures to minimize the potential bias from withdrawals, loss to follow-up, and low treatment adherence. This checklist is simple and quick to complete, and should help clinicians and researchers critically appraise the medical and healthcare literature, reviewers assess the quality of reports included in systematic reviews, and researchers plan interventional trials of spa therapy. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Fuzzy branching temporal logic.

    PubMed

    Moon, Seong-ick; Lee, Kwang H; Lee, Doheon

    2004-04-01

    Intelligent systems require a systematic way to represent and handle temporal information containing uncertainty. In particular, a logical framework is needed that can represent uncertain temporal information and its relationships with logical formulae. Fuzzy linear temporal logic (FLTL), a generalization of propositional linear temporal logic (PLTL) with fuzzy temporal events and fuzzy temporal states defined on a linear time model, was previously proposed for this purpose. However, many systems are best represented by branching time models in which each state can have more than one possible future path. In this paper, fuzzy branching temporal logic (FBTL) is proposed to address this problem. FBTL adopts and generalizes concurrent tree logic (CTL*), which is a classical branching temporal logic. The temporal model of FBTL is capable of representing fuzzy temporal events and fuzzy temporal states, and the order relation among them is represented as a directed graph. The utility of FBTL is demonstrated using a fuzzy job shop scheduling problem as an example.

  6. Identifying Dispositions That Matter: Reaching for Consensus Using a Delphi Study

    ERIC Educational Resources Information Center

    Bair, Mary Antony

    2017-01-01

    This article describes how one institution used the Delphi technique to identify and operationalize key professional dispositions to be addressed in its teacher education program. Participants included teacher educators, methods course instructors, and school administrators. Data collection occurred in three phases, with the results of each phase…

  7. Assessment Leaders' Perspectives of Institutional Cultures of Assessment: A Delphi Study

    ERIC Educational Resources Information Center

    Fuller, Matthew; Henderson, Susan; Bustamante, Rebecca

    2015-01-01

    Institutional cultures of assessment are praised as beneficial to student learning. Yet, extant studies have not explored the theoretical foundations and pragmatic approaches to shaping cultures of assessment. The researchers used the Delphi method to explore 10 higher education assessment leaders' attitudes and theoretical perspectives regarding…

  8. Fuzzy neural network methodology applied to medical diagnosis

    NASA Technical Reports Server (NTRS)

    Gorzalczany, Marian B.; Deutsch-Mcleish, Mary

    1992-01-01

    This paper presents a technique for building expert systems that combines the fuzzy-set approach with artificial neural network structures. This technique can effectively deal with two types of medical knowledge: a nonfuzzy one and a fuzzy one which usually contributes to the process of medical diagnosis. Nonfuzzy numerical data is obtained from medical tests. Fuzzy linguistic rules describing the diagnosis process are provided by a human expert. The proposed method has been successfully applied in veterinary medicine as a support system in the diagnosis of canine liver diseases.

  9. A recurrent self-organizing neural fuzzy inference network.

    PubMed

    Juang, C F; Lin, C T

    1999-01-01

    A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper. The RSONFIN is inherently a recurrent multilayered connectionist network for realizing the basic elements and functions of dynamic fuzzy inference, and may be considered to be constructed from a series of dynamic fuzzy rules. The temporal relations embedded in the network are built by adding some feedback connections representing the memory elements to a feedforward neural fuzzy network. Each weight as well as node in the RSONFIN has its own meaning and represents a special element in a fuzzy rule. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially in the RSONFIN. They are created on-line via concurrent structure identification (the construction of dynamic fuzzy if-then rules) and parameter identification (the tuning of the free parameters of membership functions). The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network. Two major characteristics of the RSONFIN can thus be seen: 1) the recurrent property of the RSONFIN makes it suitable for dealing with temporal problems and 2) no predetermination, like the number of hidden nodes, must be given, since the RSONFIN can find its optimal structure and parameters automatically and quickly. Moreover, to reduce the number of fuzzy rules generated, a flexible input partition method, the aligned clustering-based algorithm, is proposed. Various simulations on temporal problems are done and performance comparisons with some existing recurrent networks are also made. Efficiency of the RSONFIN is verified from these results.

  10. The semantics of fuzzy logic

    NASA Technical Reports Server (NTRS)

    Ruspini, Enrique H.

    1991-01-01

    Summarized here are the results of recent research on the conceptual foundations of fuzzy logic. The focus is primarily on the principle characteristics of a model that quantifies resemblance between possible worlds by means of a similarity function that assigns a number between 0 and 1 to every pair of possible worlds. Introduction of such a function permits one to interpret the major constructs and methods of fuzzy logic: conditional and unconditional possibility and necessity distributions and the generalized modus ponens of Zadeh on the basis of related metric relationships between subsets of possible worlds.

  11. Development of quality indicators for physiotherapy for patients with PAOD in the Netherlands: a Delphi study.

    PubMed

    Gijsbers, H J H; Lauret, G J; van Hofwegen, A; van Dockum, T A; Teijink, J A W; Hendriks, H J M

    2016-06-01

    The aim of the study was to develop quality indicators (QIs) for physiotherapy management of patients with intermittent claudication (IC) in the Netherlands. As part of an international six-step method to develop QIs, an online survey Delphi-procedure was completed. After two Delphi-rounds a validation round was performed. Twenty-six experts were recruited to participate in this study. Twenty-four experts completed two Delphi-rounds. A third round was conducted inviting 1200 qualified and registered physiotherapists of the Dutch integrated care network 'Claudicationet' to validate a draft set of quality indicators. Out of 83 potential QIs in the Dutch physiotherapy guideline on 'Intermittent claudication', consensus among the experts selected nine indicators. All nine quality indicators were validated by 300 physiotherapists. A final set of nine indicators was derived from (1) a Dutch evidence-based physiotherapy guideline, (2) an expert Delphi procedure and (3) a validation by 300 physiotherapists. This set of indicators should be validated in clinical practice. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  12. Developing the E-Delphi System: A Web-Based Forecasting Tool for Educational Research.

    ERIC Educational Resources Information Center

    Chou, Chien

    2002-01-01

    Discusses use of the Delphi technique and describes the development of an electronic version, called e-Delphi, in which questionnaire construction and communication with panel members was accomplished using the Web. Explains system function and interface and discusses evaluation of the e-Delphi system. (Author/LRW)

  13. 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.

  14. 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

  15. 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.

  16. Fuzzy logic

    NASA Technical Reports Server (NTRS)

    Zadeh, Lofti A.

    1988-01-01

    The author presents a condensed exposition of some basic ideas underlying fuzzy logic and describes some representative applications. The discussion covers basic principles; meaning representation and inference; basic rules of inference; and the linguistic variable and its application to fuzzy control.

  17. [Episodic breathlessness: translation and consenting of the international definition using the Delphi method].

    PubMed

    Simon, S T; Weingärtner, V; Voltz, R; Bausewein, C

    2014-10-01

    Similar to pain, refractory breathlessness can occur episodically. Episodic Breathlessness is a distressing symptom in patients with advanced life-limiting disease. The lack of a universal definition impedes symptom understanding in clinical practice and effective management, respectively. The aim of the study was to formally consent a German translation of the English definition and terminology of episodic breathlessness. A web-based Delphi survey was conducted with German breathlessness experts (breathlessness working group of Germany's National Guideline (S3) for Palliative Care). Drafts of German-language definitions und terminology were assessed using structured questionnaires by binary rating or rankings, respectively. Optional comments were analysed by content analysis. Consensus was defined by ≥ 70% agreement among participants. In two resulting Delphi-rounds 8/16 (50%) und 11/16 (69%) experts, 30-59 years of age, 50%/55% female, participated. After the second round, consensus was reached for the symptom's description "Atemnotattacke" (73%) and a German-language definition (90%). The terms "vorhersehbar" vs. "unvorhersehbar" were directly consented for the categorization (88%). The formally consented German definition and terminology of episodic breathlessness enable clearer symptom understanding and provide a precise basis for education and research on the symptom and its management also in Germany. Effective management options are warranted to improve quality of life of suffering patients and their relatives. © Georg Thieme Verlag KG Stuttgart · New York.

  18. Development of an antibiotic spectrum score based on veterans affairs culture and susceptibility data for the purpose of measuring antibiotic de-escalation: a modified Delphi approach.

    PubMed

    Madaras-Kelly, Karl; Jones, Makoto; Remington, Richard; Hill, Nicole; Huttner, Benedikt; Samore, Matthew

    2014-09-01

    Development of a numerical score to measure the microbial spectrum of antibiotic regimens (spectrum score) and method to identify antibiotic de-escalation events based on application of the score. Web-based modified Delphi method. Physician and pharmacist antimicrobial stewards practicing in the United States recruited through infectious diseases-focused listservs. Three Delphi rounds investigated: organisms and antibiotics to include in the spectrum score, operationalization of rules for the score, and de-escalation measurement. A 4-point ordinal scale was used to score antibiotic susceptibility for organism-antibiotic domain pairs. Antibiotic regimen scores, which represented combined activity of antibiotics in a regimen across all organism domains, were used to compare antibiotic spectrum administered early (day 2) and later (day 4) in therapy. Changes in spectrum score were calculated and compared with Delphi participants' judgments on de-escalation with 20 antibiotic regimen vignettes and with non-Delphi steward judgments on de-escalation of 300 pneumonia regimen vignettes. Method sensitivity and specificity to predict expert de-escalation status were calculated. Twenty-four participants completed all Delphi rounds. Expert support for concepts utilized in metric development was identified. For vignettes presented in the Delphi, the sign of change in score correctly classified de-escalation in all vignettes except those involving substitution of oral antibiotics. The sensitivity and specificity of the method to identify de-escalation events as judged by non-Delphi stewards were 86.3% and 96.0%, respectively. Identification of de-escalation events based on an algorithm that measures microbial spectrum of antibiotic regimens generally agreed with steward judgments of de-escalation status.

  19. Competency model for dentists in China: Results of a Delphi study

    PubMed Central

    Zhao, Liying; Wang, Yu; Jiang, Yiyuan; Meng, Kai; Zheng, Dongxiang

    2018-01-01

    Objective With the increasing awareness of the importance of oral health, patients have an increasing need for integrated care from dentists. In China, the dentistry examination consists of two parts: a practical skills examination and a comprehensive medical examination; to date, no assessment methods that are based on specialized dentistry competencies, unlike the United States, Canada, and other countries, have been established. Therefore, the purpose of this study was to construct a competency model for dentists in China in order to guide the development, admission, training and assessment of dentists. Methods Using a literature review, focus group interviews and in-depth personal interviews, a dentist competency index was developed with an expert consultation questionnaire. A panel of 20 specialist experts was chosen from ten national medical universities to carry out two rounds of Delphi expert analysis, using the boundary value method to filter the indicators and the Analytic Hierarchy Process to calculate the weights of the primary indicators. Results Two rounds of Delphi results showed that the expert authority, enthusiasm, and coordination coefficients were high. Constructs of the competency model that included seven primary indicators and 62 secondary indicators determined the weight of each index. The seven primary indicators included the following: clinical skills and medical services, disease prevention and health promotion, interpersonal communication skills, core values and professionalism, medical knowledge and lifelong learning ability, teamwork ability and scientific research ability. Conclusion In conclusion, the use of the Delphi method to construct an initial model of Chinese physician competency is scientific and feasible. The initial competency model conforms to the characteristics and quality requirements of dentists in China and has a strong scientific basis. The dentist competency model should be used in the National Dental Licensing

  20. 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.

  1. Multidisciplinary Delphi Development of a Scale to Evaluate Team Function in Obstetric Emergencies: The PETRA Scale.

    PubMed

    Balki, Mrinalini; Hoppe, David; Monks, David; Cooke, Mary Ellen; Sharples, Lynn; Windrim, Rory

    2017-06-01

    The objective of this study was to develop a new interdisciplinary teamwork scale, the Perinatal Emergency: Team Response Assessment (PETRA), for the management of obstetric crises, through consensus agreement of obstetric caregivers. This prospective study was performed using expert consensus, based on a Delphi method. The study investigators developed a new PETRA tool, specifically related to obstetric crisis management, based on the existing literature and discussions among themselves. The scale was distributed to a selected panel of experts in the field for the Delphi process. After each round of Delphi, every component of the scale was analyzed quantitatively by the percentage of agreement ratings and each comment reviewed by the blinded investigators. The assessment scale was then modified, with components of less than 80% agreement removed from the scale. The process was repeated on three occasions to reach a consensus and final PETRA scale. Fourteen of 24 invited experts participated in the Delphi process. The original PETRA scale included six categories and 48 items, one global scale item, and a 3-point rubric for rating. The overall percentage agreement by experts in the first, second, and third rounds was 95.0%, 93.2%, and 98.5%, respectively. The final scale after the third round of Delphi consisted of the following seven categories: shared mental model, communication, situational awareness, leadership, followership, workload management, and positive/effective behaviours and attitudes. There were 34 individual items within these categories, each with a 5-point rating rubric (1 = unacceptable to 5 = perfect). Using a structured Delphi method, we established the face and content validity of this assessment scale that focuses on important aspects of interdisciplinary teamwork in the management of obstetric crises. Copyright © 2017 The Society of Obstetricians and Gynaecologists of Canada/La Société des obstétriciens et gynécologues du Canada

  2. Using Delphi Methodology to Design Assessments of Teachers' Pedagogical Content Knowledge

    ERIC Educational Resources Information Center

    Manizade, Agida Gabil; Mason, Marguerite M.

    2011-01-01

    Descriptions of methodologies that can be used to create items for assessing teachers' "professionally situated" knowledge are lacking in mathematics education research literature. In this study, researchers described and used the Delphi method to design an instrument to measure teachers' pedagogical content knowledge. The instrument focused on a…

  3. Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care: Recommendations based on a methodological systematic review.

    PubMed

    Jünger, Saskia; Payne, Sheila A; Brine, Jenny; Radbruch, Lukas; Brearley, Sarah G

    2017-09-01

    The Delphi technique is widely used for the development of guidance in palliative care, having impact on decisions with relevance for patient care. To systematically examine the application of the Delphi technique for the development of best practice guidelines in palliative care. A methodological systematic review was undertaken using the databases PubMed, CINAHL, Web of Science, Academic Search Complete and EMBASE. Original articles (English language) were included when reporting on empirical studies that had used the Delphi technique to develop guidance for good clinical practice in palliative care. Data extraction included a quality appraisal on the rigour in conduct of the studies and the quality of reporting. A total of 30 empirical studies (1997-2015) were considered for full-text analysis. Considerable differences were identified regarding the rigour of the design and the reporting of essential process and outcome parameters. Furthermore, discrepancies regarding the use of terms for describing the method were observed, for example, concerning the understanding of a 'round' or a 'modified Delphi study'. Substantial variation was found concerning the quality of the study conduct and the transparency of reporting of Delphi studies used for the development of best practice guidance in palliative care. Since credibility of the resulting recommendations depends on the rigorous use of the Delphi technique, there is a need for consistency and quality both in the conduct and reporting of studies. To allow a critical appraisal of the methodology and the resulting guidance, a reporting standard for Conducting and REporting of DElphi Studies (CREDES) is proposed.

  4. Testing an Adapted Modified Delphi Method: Synthesizing Multiple Stakeholder Ratings of Health Care Service Effectiveness.

    PubMed

    Escaron, Anne L; Chang Weir, Rosy; Stanton, Petra; Vangala, Sitaram; Grogan, Tristan R; Clarke, Robin M

    2016-03-01

    The Affordable Care Act incentivizes health systems for better meeting patient needs, but often guidance about patient preferences for particular health services is limited. All too often vulnerable patient populations are excluded from these decision-making settings. A community-based participatory approach harnesses the in-depth knowledge of those experiencing barriers to health care. We made three modifications to the RAND-UCLA appropriateness method, a modified Delphi approach, involving patients, adding an advisory council group to characterize existing knowledge in this little studied area, and using effectiveness rather than "appropriateness" as the basis for rating. As a proof of concept, we tested this method by examining the broadly delivered but understudied nonmedical services that community health centers provide. This method created discrete, new knowledge about these services by defining 6 categories and 112 unique services and by prioritizing among these services based on effectiveness using a 9-point scale. Consistent with the appropriateness method, we found statistical convergence of ratings among the panelists. Challenges include time commitment and adherence to a clear definition of effectiveness of services. This diverse stakeholder engagement method efficiently addresses gaps in knowledge about the effectiveness of health care services to inform population health management. © 2015 Society for Public Health Education.

  5. 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

  6. 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.

  7. Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

    NASA Astrophysics Data System (ADS)

    Zhang, Nannan; Zhou, Kefa; Du, Xishihui

    2017-04-01

    Mineral prospectivity mapping (MPM) is a multi-step process that ranks promising target areas for further exploration. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are knowledge-driven MPM approaches. In this study, both approaches were used for data processing, based on which MPM was performed for porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang. The results of the two methods were then compared. The two methods combined expert experience and the Studentized contrast (S(C)) values of the weights-of-evidence approach to calculate the weights of 15 layers, and these layers were then integrated by the gamma operator (γ). Through prediction-area (P-A) plot analysis, the optimal γ for fuzzy logic and fuzzy AHP was determined as 0.95 and 0.93, respectively. The thresholds corresponding to different levels of metallogenic probability were defined via concentration-area (C-A) fractal analysis. The prediction performances of the two methods were compared on this basis. The results showed that in MPM based on fuzzy logic, the area under the receiver operating characteristic (ROC) curve was 0.806 and 81.48% of the known deposits were predicted, whereas in MPM based on fuzzy AHP, the area under the ROC curve was 0.862 and 92.59% of the known deposits were predicted. Therefore, prediction based on fuzzy AHP is more accurate and can provide directions for future prospecting.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Fuzzy correlation analysis with realization

    NASA Astrophysics Data System (ADS)

    Tang, Yue Y.; Fan, Xinrui; Zheng, Ying N.

    1998-10-01

    The fundamental concept of fuzzy correlation is briefly discussed. Based on the correlation coefficient of classic correlation, polarity correlation and fuzzy correlation, the relationship between the correlations are analyzed. A fuzzy correlation analysis has the merits of both rapidity and accuracy as some amplitude information of random signals has been utilized. It has broad prospects for application. The form of fuzzy correlative analyzer with NLX 112 fuzzy data correlator and single-chip microcomputer is introduced.

  13. A novel method of fuzzy fault tree analysis combined with VB program to identify and assess the risk of coal dust explosions

    PubMed Central

    Li, Jia; Wang, Deming; Huang, Zonghou

    2017-01-01

    Coal dust explosions (CDE) are one of the main threats to the occupational safety of coal miners. Aiming to identify and assess the risk of CDE, this paper proposes a novel method of fuzzy fault tree analysis combined with the Visual Basic (VB) program. In this methodology, various potential causes of the CDE are identified and a CDE fault tree is constructed. To overcome drawbacks from the lack of exact probability data for the basic events, fuzzy set theory is employed and the probability data of each basic event is treated as intuitionistic trapezoidal fuzzy numbers. In addition, a new approach for calculating the weighting of each expert is also introduced in this paper to reduce the error during the expert elicitation process. Specifically, an in-depth quantitative analysis of the fuzzy fault tree, such as the importance measure of the basic events and the cut sets, and the CDE occurrence probability is given to assess the explosion risk and acquire more details of the CDE. The VB program is applied to simplify the analysis process. A case study and analysis is provided to illustrate the effectiveness of this proposed method, and some suggestions are given to take preventive measures in advance and avoid CDE accidents. PMID:28793348

  14. A novel method of fuzzy fault tree analysis combined with VB program to identify and assess the risk of coal dust explosions.

    PubMed

    Wang, Hetang; Li, Jia; Wang, Deming; Huang, Zonghou

    2017-01-01

    Coal dust explosions (CDE) are one of the main threats to the occupational safety of coal miners. Aiming to identify and assess the risk of CDE, this paper proposes a novel method of fuzzy fault tree analysis combined with the Visual Basic (VB) program. In this methodology, various potential causes of the CDE are identified and a CDE fault tree is constructed. To overcome drawbacks from the lack of exact probability data for the basic events, fuzzy set theory is employed and the probability data of each basic event is treated as intuitionistic trapezoidal fuzzy numbers. In addition, a new approach for calculating the weighting of each expert is also introduced in this paper to reduce the error during the expert elicitation process. Specifically, an in-depth quantitative analysis of the fuzzy fault tree, such as the importance measure of the basic events and the cut sets, and the CDE occurrence probability is given to assess the explosion risk and acquire more details of the CDE. The VB program is applied to simplify the analysis process. A case study and analysis is provided to illustrate the effectiveness of this proposed method, and some suggestions are given to take preventive measures in advance and avoid CDE accidents.

  15. A pertinent approach to solve nonlinear fuzzy integro-differential equations.

    PubMed

    Narayanamoorthy, S; Sathiyapriya, S P

    2016-01-01

    Fuzzy integro-differential equations is one of the important parts of fuzzy analysis theory that holds theoretical as well as applicable values in analytical dynamics and so an appropriate computational algorithm to solve them is in essence. In this article, we use parametric forms of fuzzy numbers and suggest an applicable approach for solving nonlinear fuzzy integro-differential equations using homotopy perturbation method. A clear and detailed description of the proposed method is provided. Our main objective is to illustrate that the construction of appropriate convex homotopy in a proper way leads to highly accurate solutions with less computational work. The efficiency of the approximation technique is expressed via stability and convergence analysis so as to guarantee the efficiency and performance of the methodology. Numerical examples are demonstrated to verify the convergence and it reveals the validity of the presented numerical technique. Numerical results are tabulated and examined by comparing the obtained approximate solutions with the known exact solutions. Graphical representations of the exact and acquired approximate fuzzy solutions clarify the accuracy of the approach.

  16. Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

    NASA Astrophysics Data System (ADS)

    Mohd, Wan Rosanisah Wan; Abdullah, Lazim

    2017-11-01

    A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.

  17. FUZZY DECISION ANALYSIS FOR INTEGRATED ENVIRONMENTAL VULNERABILITY ASSESSMENT OF THE MID-ATLANTIC REGION

    EPA Science Inventory


    A fuzzy decision analysis method for integrating ecological indicators is developed. This is a combination of a fuzzy ranking method and the Analytic Hierarchy Process (AHP). The method is capable ranking ecosystems in terms of environmental conditions and suggesting cumula...

  18. Design of a robust fuzzy controller for the arc stability of CO(2) welding process using the Taguchi method.

    PubMed

    Kim, Dongcheol; Rhee, Sehun

    2002-01-01

    CO(2) welding is a complex process. Weld quality is dependent on arc stability and minimizing the effects of disturbances or changes in the operating condition commonly occurring during the welding process. In order to minimize these effects, a controller can be used. In this study, a fuzzy controller was used in order to stabilize the arc during CO(2) welding. The input variable of the controller was the Mita index. This index estimates quantitatively the arc stability that is influenced by many welding process parameters. Because the welding process is complex, a mathematical model of the Mita index was difficult to derive. Therefore, the parameter settings of the fuzzy controller were determined by performing actual control experiments without using a mathematical model of the controlled process. The solution, the Taguchi method was used to determine the optimal control parameter settings of the fuzzy controller to make the control performance robust and insensitive to the changes in the operating conditions.

  19. 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.

  20. (Fuzzy) Ideals of BN-Algebras

    PubMed Central

    Walendziak, Andrzej

    2015-01-01

    The notions of an ideal and a fuzzy ideal in BN-algebras are introduced. The properties and characterizations of them are investigated. The concepts of normal ideals and normal congruences of a BN-algebra are also studied, the properties of them are displayed, and a one-to-one correspondence between them is presented. Conditions for a fuzzy set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained. PMID:26125050

  1. Delphi based consensus study into planning for chemical incidents.

    PubMed

    Crawford, I W F; Mackway-Jones, K; Russell, D R; Carley, S D

    2004-01-01

    To achieve consensus in all phases of chemical incident planning and response. A three round Delphi study was conducted using a panel of 39 experts from specialties involved in the management of chemical incidents. Areas that did not reach consensus in the Delphi study were presented as synopsis statements for discussion in four syndicate groups at a conference hosted by the Department of Health Emergency Planning Co-ordination Unit. A total of 183 of 322 statements had reached consensus upon completion of the Delphi study. This represented 56.8% of the total number of statements. Of these, 148 reached consensus at >94% and 35 reached consensus at >89%. The results of the process are presented as a series of synopsis consensus statements that cover all phases of chemical incident planning and response. The use of a Delphi study and subsequent syndicate group discussions achieved consensus in aspects of all phases of chemical incident planning and response that can be translated into practical guidance for use at regional prehospital and hospital level. Additionally, areas of non-consensus have been identified where further work is required.

  2. Delphi based consensus study into planning for chemical incidents

    PubMed Central

    Crawford, I; Mackway-Jones, K; Russell, D; Carley, S

    2004-01-01

    Objective: To achieve consensus in all phases of chemical incident planning and response. Design: A three round Delphi study was conducted using a panel of 39 experts from specialties involved in the management of chemical incidents. Areas that did not reach consensus in the Delphi study were presented as synopsis statements for discussion in four syndicate groups at a conference hosted by the Department of Health Emergency Planning Co-ordination Unit. Results: A total of 183 of 322 statements had reached consensus upon completion of the Delphi study. This represented 56.8% of the total number of statements. Of these, 148 reached consensus at >94% and 35 reached consensus at >89%. The results of the process are presented as a series of synopsis consensus statements that cover all phases of chemical incident planning and response. Conclusions: The use of a Delphi study and subsequent syndicate group discussions achieved consensus in aspects of all phases of chemical incident planning and response that can be translated into practical guidance for use at regional prehospital and hospital level. Additionally, areas of non-consensus have been identified where further work is required. PMID:14734369

  3. Fuzzy method of recognition of high molecular substances in evidence-based biology

    NASA Astrophysics Data System (ADS)

    Olevskyi, V. I.; Smetanin, V. T.; Olevska, Yu. B.

    2017-10-01

    Nowadays modern requirements to achieving reliable results along with high quality of researches put mathematical analysis methods of results at the forefront. Because of this, evidence-based methods of processing experimental data have become increasingly popular in the biological sciences and medicine. Their basis is meta-analysis, a method of quantitative generalization of a large number of randomized trails contributing to a same special problem, which are often contradictory and performed by different authors. It allows identifying the most important trends and quantitative indicators of the data, verification of advanced hypotheses and discovering new effects in the population genotype. The existing methods of recognizing high molecular substances by gel electrophoresis of proteins under denaturing conditions are based on approximate methods for comparing the contrast of electrophoregrams with a standard solution of known substances. We propose a fuzzy method for modeling experimental data to increase the accuracy and validity of the findings of the detection of new proteins.

  4. 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.

  5. Fuzzy Edge Connectivity of Graphical Fuzzy State Space Model in Multi-connected System

    NASA Astrophysics Data System (ADS)

    Harish, Noor Ainy; Ismail, Razidah; Ahmad, Tahir

    2010-11-01

    Structured networks of interacting components illustrate complex structure in a direct or intuitive way. Graph theory provides a mathematical modeling for studying interconnection among elements in natural and man-made systems. On the other hand, directed graph is useful to define and interpret the interconnection structure underlying the dynamics of the interacting subsystem. Fuzzy theory provides important tools in dealing various aspects of complexity, imprecision and fuzziness of the network structure of a multi-connected system. Initial development for systems of Fuzzy State Space Model (FSSM) and a fuzzy algorithm approach were introduced with the purpose of solving the inverse problems in multivariable system. In this paper, fuzzy algorithm is adapted in order to determine the fuzzy edge connectivity between subsystems, in particular interconnected system of Graphical Representation of FSSM. This new approach will simplify the schematic diagram of interconnection of subsystems in a multi-connected system.

  6. A delphi study on health in future India.

    PubMed

    Rohatgi, K; Rohatgi, P K

    1980-07-01

    A delphi study was conducted to identify or envision health scenarios in India by the year 2000. Questionnaires consisting of 48 questions on 5 areas (diagnosis and therapy; family planning; pharmaceuticals and drugs; biochemical and biomedical research; health services) were mailed to 250 experts in India. 36 responded. Results were compiled and mailed back to the respondents for changes and comments. 17 people responded. Results of the delphi study shows that policy decisions with respect to compulsory family planning as well as health education at secondary school level will precede further breakthroughs in birth control technology. Non operation reversible sterilization procedures, immunological birth control, Ayurvedic medicines for contraception and abortion, and selection of baby's sex are all possible by 2000 thereafter. Complete eradication of infectious diseases, malnutrition and associated diseases is considered unlikely before 2000, as are advances in biomedical research. Changes in health services (e.g., significant increases in hospital beds and doctors, cheap bulk drugs), particularly in rural areas, are imminent, leading to prolonging of life expectancy to 70 years. Genetic engineering may provide significant breakthroughs in the prevention of malignancies and cardiac disorders. The India delphi study is patterned after a similar delphi study conducted in the U.S. by Smith, Kline and French (SKF) Laboratories in 1968. The SKF study was able to predict some breakthroughs with basic research which have been realized.

  7. Emerging Technologies Program Integration Report. Volume 2. Background, Delphi and Workshop Data. Appendices

    DTIC Science & Technology

    1987-05-04

    FTIILE COP’ AD-A196 840 EMERGING TECHNOLOGIES PROGRAM INTEGRATION REPORT VOLUME II BACKGROUND, DELPHI AND WORKSHOP DATA, APPENDICES . -- PREPARED...Security Classification) Emerging Technologies Program Integration Report Volume II: Background, Delphi and Workshop Data; Appendices (U) 12 PERSONAL...volumes of this integration report assess and synthesize information gathered through a Delphi survey, defense needs prioritization workshops, and

  8. Identifying Core Concepts of Cybersecurity: Results of Two Delphi Processes

    ERIC Educational Resources Information Center

    Parekh, Geet; DeLatte, David; Herman, Geoffrey L.; Oliva, Linda; Phatak, Dhananjay; Scheponik, Travis; Sherman, Alan T.

    2018-01-01

    This paper presents and analyzes results of two Delphi processes that polled cybersecurity experts to rate cybersecurity topics based on importance, difficulty, and timelessness. These ratings can be used to identify core concepts--cross-cutting ideas that connect knowledge in the discipline. The first Delphi process identified core concepts that…

  9. A Distributed Fuzzy Associative Classifier for Big Data.

    PubMed

    Segatori, Armando; Bechini, Alessio; Ducange, Pietro; Marcelloni, Francesco

    2017-09-19

    Fuzzy associative classification has not been widely analyzed in the literature, although associative classifiers (ACs) have proved to be very effective in different real domain applications. The main reason is that learning fuzzy ACs is a very heavy task, especially when dealing with large datasets. To overcome this drawback, in this paper, we propose an efficient distributed fuzzy associative classification approach based on the MapReduce paradigm. The approach exploits a novel distributed discretizer based on fuzzy entropy for efficiently generating fuzzy partitions of the attributes. Then, a set of candidate fuzzy association rules is generated by employing a distributed fuzzy extension of the well-known FP-Growth algorithm. Finally, this set is pruned by using three purposely adapted types of pruning. We implemented our approach on the popular Hadoop framework. Hadoop allows distributing storage and processing of very large data sets on computer clusters built from commodity hardware. We have performed an extensive experimentation and a detailed analysis of the results using six very large datasets with up to 11,000,000 instances. We have also experimented different types of reasoning methods. Focusing on accuracy, model complexity, computation time, and scalability, we compare the results achieved by our approach with those obtained by two distributed nonfuzzy ACs recently proposed in the literature. We highlight that, although the accuracies result to be comparable, the complexity, evaluated in terms of number of rules, of the classifiers generated by the fuzzy distributed approach is lower than the one of the nonfuzzy classifiers.

  10. Delphi in Criminal Justice Policy: A Case Study on Judgmental Forecasting

    ERIC Educational Resources Information Center

    Loyens, Kim; Maesschalck, Jeroen; Bouckaert, Geert

    2011-01-01

    This article provides an in-depth case study analysis of a pilot project organized by the section "Strategic Analysis" of the Belgian Federal Police. Using the Delphi method, which is a judgmental forecasting technique, a panel of experts was questioned about future developments of crime, based on their expertise in criminal or social…

  11. Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    PubMed Central

    Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

    2014-01-01

    A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

  12. WARP: Weight Associative Rule Processor. A dedicated VLSI fuzzy logic megacell

    NASA Technical Reports Server (NTRS)

    Pagni, A.; Poluzzi, R.; Rizzotto, G. G.

    1992-01-01

    During the last five years Fuzzy Logic has gained enormous popularity in the academic and industrial worlds. The success of this new methodology has led the microelectronics industry to create a new class of machines, called Fuzzy Machines, to overcome the limitations of traditional computing systems when utilized as Fuzzy Systems. This paper gives an overview of the methods by which Fuzzy Logic data structures are represented in the machines (each with its own advantages and inefficiencies). Next, the paper introduces WARP (Weight Associative Rule Processor) which is a dedicated VLSI megacell allowing the realization of a fuzzy controller suitable for a wide range of applications. WARP represents an innovative approach to VLSI Fuzzy controllers by utilizing different types of data structures for characterizing the membership functions during the various stages of the Fuzzy processing. WARP dedicated architecture has been designed in order to achieve high performance by exploiting the computational advantages offered by the different data representations.

  13. Fuzzy pharmacology: theory and applications.

    PubMed

    Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

    2002-09-01

    Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

  14. 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.

  15. Parallel fuzzy connected image segmentation on GPU

    PubMed Central

    Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

    2011-01-01

    Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm implementation on NVIDIA’s compute unified device Architecture (cuda) platform for segmenting medical image data sets. Methods: In the FC algorithm, there are two major computational tasks: (i) computing the fuzzy affinity relations and (ii) computing the fuzzy connectedness relations. These two tasks are implemented as cuda kernels and executed on GPU. A dramatic improvement in speed for both tasks is achieved as a result. Results: Our experiments based on three data sets of small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 24.4x, 18.1x, and 10.3x, correspondingly, for the three data sets on the NVIDIA Tesla C1060 over the implementation of the algorithm on CPU, and takes 0.25, 0.72, and 15.04 s, correspondingly, for the three data sets. Conclusions: The authors developed a parallel algorithm of the widely used fuzzy connected image segmentation method on the NVIDIA GPUs, which are far more cost- and speed-effective than both cluster of workstations and multiprocessing systems. A near-interactive speed of segmentation has been achieved, even for the large data set. PMID:21859037

  16. Learning Rate Updating Methods Applied to Adaptive Fuzzy Equalizers for Broadband Power Line Communications

    NASA Astrophysics Data System (ADS)

    Ribeiro, Moisés V.

    2004-12-01

    This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.

  17. Working towards consensus on methods used to elicit participant-reported safety data in uncomplicated malaria clinical drug studies: a Delphi technique study.

    PubMed

    Mandimika, Nyaradzo; Barnes, Karen I; Chandler, Clare I R; Pace, Cheryl; Allen, Elizabeth N

    2017-01-28

    Eliciting adverse event (AE) and non-study medication data reports from clinical research participants is integral to evaluating drug safety. However, using different methods to question participants yields inconsistent results, compromising the interpretation, comparison and pooling of data across studies. This is particularly important given the widespread use of anti-malarials in vulnerable populations, and their increasing use in healthy, but at-risk individuals, as preventive treatment or to reduce malaria transmission. Experienced and knowledgeable anti-malarial drug clinical researchers were invited to participate in a Delphi technique study, to facilitate consensus on what are considered optimal (relevant, important and feasible) methods, tools, and approaches for detecting participant-reported AE and non-study medication data in uncomplicated malaria treatment studies. Of 72 invited, 25, 16 and 10 panellists responded to the first, second and third rounds of the Delphi, respectively. Overall, 68% (68/100) of all questioning items presented for rating achieved consensus. When asking general questions about health, panellists agreed on the utility of a question/concept about any change in health, taking care to ensure that such questions/concepts do not imply causality. Eighty-nine percent (39/44) of specific signs and symptoms questions were rated as optimal. For non-study medications, a general question and most structured questioning items were considered an optimal approach. The use of mobile phones, patient diaries, rating scales as well as openly engaging with participants to discuss concerns were also considered optimal complementary data-elicitation tools. This study succeeded in reaching consensus within a section of the anti-malarial drug clinical research community about using a general question concept, and structured questions for eliciting data about AEs and non-study medication reports. The concepts and items considered in this Delphi to be

  18. 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.

  19. Application of Fuzzy Logic to Matrix FMECA

    NASA Astrophysics Data System (ADS)

    Shankar, N. Ravi; Prabhu, B. S.

    2001-04-01

    A methodology combining the benefits of Fuzzy Logic and Matrix FMEA is presented in this paper. The presented methodology extends the risk prioritization beyond the conventional Risk Priority Number (RPN) method. Fuzzy logic is used to calculate the criticality rank. Also the matrix approach is improved further to develop a pictorial representation retaining all relevant qualitative and quantitative information of several FMEA elements relationships. The methodology presented is demonstrated by application to an illustrative example.

  20. Fuzzy Logic Approaches to Multi-Objective Decision-Making in Aerospace Applications

    NASA Technical Reports Server (NTRS)

    Hardy, Terry L.

    1994-01-01

    Fuzzy logic allows for the quantitative representation of multi-objective decision-making problems which have vague or fuzzy objectives and parameters. As such, fuzzy logic approaches are well-suited to situations where alternatives must be assessed by using criteria that are subjective and of unequal importance. This paper presents an overview of fuzzy logic and provides sample applications from the aerospace industry. Applications include an evaluation of vendor proposals, an analysis of future space vehicle options, and the selection of a future space propulsion system. On the basis of the results provided in this study, fuzzy logic provides a unique perspective on the decision-making process, allowing the evaluator to assess the degree to which each option meets the evaluation criteria. Future decision-making should take full advantage of fuzzy logic methods to complement existing approaches in the selection of alternatives.

  1. 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

  2. Classification of air quality using fuzzy synthetic multiplication.

    PubMed

    Abdullah, Lazim; Khalid, Noor Dalina

    2012-11-01

    Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.

  3. 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.

  4. Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

    SciTech Connect

    Hamadameen, Abdulqader Othman; Zainuddin, Zaitul Marlizawati

    This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

  5. Developing clinical practice guidelines for Chinese herbal treatment of polycystic ovary syndrome: A mixed-methods modified Delphi study.

    PubMed

    Lai, Lily; Flower, Andrew; Moore, Michael; Lewith, George

    2015-06-01

    Preliminary evidence suggests Chinese herbal medicine (CHM) could be a viable treatment option for polycystic ovary syndrome (PCOS). Prior to conducting a clinical trial it is important to consider the characteristics of good clinical practice. This study aims to use professional consensus to establish good clinical practice guidelines for the CHM treatment of PCOS. CHM practitioners participated in a mixed-methods modified Delphi study involving three rounds of structured group communication. Round 1 involved qualitative interviews with practitioners to generate statements regarding good clinical practice. In round 2, these statements were distributed online to the same practitioners to rate their agreement using a 7-point Likert scale, where group consensus was defined as a median rating of ≥5. Statements reaching consensus were accepted for consideration onto the guideline whilst those not reaching consensus were re-distributed for consideration in round 3. Statements presented in the guidelines were graded from A (strong consensus) to D (no consensus) determined by median score and interquartile range. 11 CHM practitioners in the UK were recruited. After three Delphi rounds, 91 statement items in total had been considered, of which 89 (97.8%) reached consensus and 2 (2.2%) did not. The concluding set of guidelines consists of 85 items representing key features of CHM prescribing for PCOS. These guidelines can be viewed as an initial framework that captures fundamental principles of good clinical practice for CHM. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Fuzzy robust credibility-constrained programming for environmental management and planning.

    PubMed

    Zhang, Yimei; Hang, Guohe

    2010-06-01

    In this study, a fuzzy robust credibility-constrained programming (FRCCP) is developed and applied to the planning for waste management systems. It incorporates the concepts of credibility-based chance-constrained programming and robust programming within an optimization framework. The developed method can reflect uncertainties presented as possibility-density by fuzzy-membership functions. Fuzzy credibility constraints are transformed to the crisp equivalents with different credibility levels, and ordinary fuzzy inclusion constraints are determined by their robust deterministic constraints by setting a-cut levels. The FRCCP method can provide different system costs under different credibility levels (lambda). From the results of sensitivity analyses, the operation cost of the landfill is a critical parameter. For the management, any factors that would induce cost fluctuation during landfilling operation would deserve serious observation and analysis. By FRCCP, useful solutions can be obtained to provide decision-making support for long-term planning of solid waste management systems. It could be further enhanced through incorporating methods of inexact analysis into its framework. It can also be applied to other environmental management problems.

  7. Competency model for dentists in China: Results of a Delphi study.

    PubMed

    Geng, Yunxia; Zhao, Liying; Wang, Yu; Jiang, Yiyuan; Meng, Kai; Zheng, Dongxiang

    2018-01-01

    With the increasing awareness of the importance of oral health, patients have an increasing need for integrated care from dentists. In China, the dentistry examination consists of two parts: a practical skills examination and a comprehensive medical examination; to date, no assessment methods that are based on specialized dentistry competencies, unlike the United States, Canada, and other countries, have been established. Therefore, the purpose of this study was to construct a competency model for dentists in China in order to guide the development, admission, training and assessment of dentists. Using a literature review, focus group interviews and in-depth personal interviews, a dentist competency index was developed with an expert consultation questionnaire. A panel of 20 specialist experts was chosen from ten national medical universities to carry out two rounds of Delphi expert analysis, using the boundary value method to filter the indicators and the Analytic Hierarchy Process to calculate the weights of the primary indicators. Two rounds of Delphi results showed that the expert authority, enthusiasm, and coordination coefficients were high. Constructs of the competency model that included seven primary indicators and 62 secondary indicators determined the weight of each index. The seven primary indicators included the following: clinical skills and medical services, disease prevention and health promotion, interpersonal communication skills, core values and professionalism, medical knowledge and lifelong learning ability, teamwork ability and scientific research ability. In conclusion, the use of the Delphi method to construct an initial model of Chinese physician competency is scientific and feasible. The initial competency model conforms to the characteristics and quality requirements of dentists in China and has a strong scientific basis. The dentist competency model should be used in the National Dental Licensing Examination in China.

  8. Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering

    NASA Astrophysics Data System (ADS)

    Onishi, Masaki; Yoda, Ikushi

    In recent years, many human tracking researches have been proposed in order to analyze human dynamic trajectory. These researches are general technology applicable to various fields, such as customer purchase analysis in a shopping environment and safety control in a (railroad) crossing. In this paper, we present a new approach for tracking human positions by stereo image. We use the framework of two-stepped clustering with k-means method and fuzzy clustering to detect human regions. In the initial clustering, k-means method makes middle clusters from objective features extracted by stereo vision at high speed. In the last clustering, c-means fuzzy method cluster middle clusters based on attributes into human regions. Our proposed method can be correctly clustered by expressing ambiguity using fuzzy clustering, even when many people are close to each other. The validity of our technique was evaluated with the experiment of trajectories extraction of doctors and nurses in an emergency room of a hospital.

  9. 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

  10. 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.

  11. Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

    NASA Astrophysics Data System (ADS)

    Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

    2018-04-01

    A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

  12. An object recognition method based on fuzzy theory and BP networks

    NASA Astrophysics Data System (ADS)

    Wu, Chuan; Zhu, Ming; Yang, Dong

    2006-01-01

    It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling, shifting, rotation if eigenvectors can not be chosen appropriately. In order to solve this problem, the image is edged, the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively, correctly and quickly.

  13. 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.

  14. Fuzzy Control of Robotic Arm

    NASA Astrophysics Data System (ADS)

    Lin, Kyaw Kyaw; Soe, Aung Kyaw; Thu, Theint Theint

    2008-10-01

    This research work investigates a Self-Tuning Proportional Derivative (PD) type Fuzzy Logic Controller (STPDFLC) for a two link robot system. The proposed scheme adjusts on-line the output Scaling Factor (SF) by fuzzy rules according to the current trend of the robot. The rule base for tuning the output scaling factor is defined on the error (e) and change in error (de). The scheme is also based on the fact that the controller always tries to manipulate the process input. The rules are in the familiar if-then format. All membership functions for controller inputs (e and de) and controller output (UN) are defined on the common interval [-1,1]; whereas the membership functions for the gain updating factor (α) is defined on [0,1]. There are various methods to calculate the crisp output of the system. Center of Gravity (COG) method is used in this application due to better results it gives. Performances of the proposed STPDFLC are compared with those of their corresponding PD-type conventional Fuzzy Logic Controller (PDFLC). The proposed scheme shows a remarkably improved performance over its conventional counterpart especially under parameters variation (payload). The two-link results of analysis are simulated. These simulation results are illustrated by using MATLAB® programming.

  15. Identifying Competencies for Volunteer Administrators for the Coming Decade: A National Delphi Study.

    ERIC Educational Resources Information Center

    Boyd, Barry L.

    2003-01-01

    A Delphi panel of 13 experts categorized 33 competencies for volunteer administration into 5 constructs: organizational leadership, systems leadership, organizational culture, personal skills, and management skills. Twelve barriers to acquiring competencies and 21 methods to address them were identified. (Contains 24 references.) (SK)

  16. A proposal of fuzzy connective with learning function and its application to fuzzy retrieval system

    NASA Technical Reports Server (NTRS)

    Hayashi, Isao; Naito, Eiichi; Ozawa, Jun; Wakami, Noboru

    1993-01-01

    A new fuzzy connective and a structure of network constructed by fuzzy connectives are proposed to overcome a drawback of conventional fuzzy retrieval systems. This network represents a retrieval query and the fuzzy connectives in networks have a learning function to adjust its parameters by data from a database and outputs of a user. The fuzzy retrieval systems employing this network are also constructed. Users can retrieve results even with a query whose attributes do not exist in a database schema and can get satisfactory results for variety of thinkings by learning function.

  17. Fuzzy control of power converters based on quasilinear modelling

    NASA Astrophysics Data System (ADS)

    Li, C. K.; Lee, W. L.; Chou, Y. W.

    1995-03-01

    Unlike feedback control by the fuzzy PID method, a new fuzzy control algorithm based on quasilinear modelling of the DC-DC converter is proposed. Investigation is carried out using a buck-boost converter. Simulation results demonstrated that the converter can be regulated with improved performance even when subjected to input disturbance and load variation.

  18. A Delphi Investigation into Future Trends in E-Learning in Israel

    ERIC Educational Resources Information Center

    Aharony, Noa; Bronstein, Jenny

    2014-01-01

    The purpose of this study is to investigate the views and opinions of e-learning experts regarding future trends in the e-learning arena. The Delphi technique was chosen as a method of study. This technique is an efficient and effective group communication process designed to systematically elicit judgments from experts in their selected area of…

  19. Views and Dreams: A Delphi Investigation into Library 2.0 Applications

    ERIC Educational Resources Information Center

    Bronstein, Jenny; Aharony, Noa

    2009-01-01

    The study's purpose was to investigate the views and opinions of librarians about the implementation of Web 2.0 technologies into library operations and services. The Delphi technique was chosen as the method of inquiry in this study, in which a group of panelists graded the desirability and probability of a list of statements. Thirty-nine…

  20. 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.

  1. TRStalker: an efficient heuristic for finding fuzzy tandem repeats.

    PubMed

    Pellegrini, Marco; Renda, M Elena; Vecchio, Alessio

    2010-06-15

    Genomes in higher eukaryotic organisms contain a substantial amount of repeated sequences. Tandem Repeats (TRs) constitute a large class of repetitive sequences that are originated via phenomena such as replication slippage and are characterized by close spatial contiguity. They play an important role in several molecular regulatory mechanisms, and also in several diseases (e.g. in the group of trinucleotide repeat disorders). While for TRs with a low or medium level of divergence the current methods are rather effective, the problem of detecting TRs with higher divergence (fuzzy TRs) is still open. The detection of fuzzy TRs is propaedeutic to enriching our view of their role in regulatory mechanisms and diseases. Fuzzy TRs are also important as tools to shed light on the evolutionary history of the genome, where higher divergence correlates with more remote duplication events. We have developed an algorithm (christened TRStalker) with the aim of detecting efficiently TRs that are hard to detect because of their inherent fuzziness, due to high levels of base substitutions, insertions and deletions. To attain this goal, we developed heuristics to solve a Steiner version of the problem for which the fuzziness is measured with respect to a motif string not necessarily present in the input string. This problem is akin to the 'generalized median string' that is known to be an NP-hard problem. Experiments with both synthetic and biological sequences demonstrate that our method performs better than current state of the art for fuzzy TRs and that the fuzzy TRs of the type we detect are indeed present in important biological sequences. TRStalker will be integrated in the web-based TRs Discovery Service (TReaDS) at bioalgo.iit.cnr.it. Supplementary data are available at Bioinformatics online.

  2. 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

  3. 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.

  4. Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

    PubMed

    Abe, S

    1998-01-01

    In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

  5. Operationalising elaboration theory for simulation instruction design: a Delphi study.

    PubMed

    Haji, Faizal A; Khan, Rabia; Regehr, Glenn; Ng, Gary; de Ribaupierre, Sandrine; Dubrowski, Adam

    2015-06-01

    The aim of this study was to assess the feasibility of incorporating the Delphi process within the simplifying conditions method (SCM) described in elaboration theory (ET) to identify conditions impacting the complexity of procedural skills for novice learners. We generated an initial list of conditions impacting the complexity of lumbar puncture (LP) from key informant interviews (n = 5) and a literature review. Eighteen clinician-educators from six different medical specialties were subsequently recruited as expert panellists. Over three Delphi rounds, these panellists rated: (i) their agreement with the inclusion of the simple version of the conditions in a representative ('epitome') training scenario, and (ii) how much the inverse (complex) version increases LP complexity for a novice. Cronbach's α-values were used to assess inter-rater agreement. All panellists completed Rounds 1 and 2 of the survey and 17 completed Round 3. In Round 1, Cronbach's α-values were 0.89 and 0.94 for conditions that simplify and increase LP complexity, respectively; both values increased to 0.98 in Rounds 2 and 3. With the exception of 'high CSF (cerebral spinal fluid) pressure', panellists agreed with the inclusion of all conditions in the simplest (epitome) training scenario. Panellists rated patient movement, spinal anatomy, patient cooperativeness, body habitus, and the presence or absence of an experienced assistant as having the greatest impact on the complexity of LP. This study demonstrated the feasibility of using expert consensus to establish conditions impacting the complexity of procedural skills, and the benefits of incorporating the Delphi method into the SCM. These data can be used to develop and sequence simulation scenarios in a progressively challenging manner. If the theorised learning gains associated with ET are realised, the methods described in this study may be applied to the design of simulation training for other procedural and non-procedural skills

  6. A Research Study Using the Delphi Method to Define Essential Competencies for a High School Game Art and Design Course Framework at the National Level

    ERIC Educational Resources Information Center

    Mack, Nayo Corenus-Geneva

    2011-01-01

    This research study reports the findings of a Delphi study conducted to determine the essential competencies and objectives for a high school Game Art and Design course framework at the national level. The Delphi panel consisted of gaming, industry and educational experts from all over the world who were members of the International Game…

  7. Fuzzy Analytic Hierarchy Process-based Chinese Resident Best Fitness Behavior Method Research.

    PubMed

    Wang, Dapeng; Zhang, Lan

    2015-01-01

    With explosive development in Chinese economy and science and technology, people's pursuit of health becomes more and more intense, therefore Chinese resident sports fitness activities have been rapidly developed. However, different fitness events popularity degrees and effects on body energy consumption are different, so bases on this, the paper researches on fitness behaviors and gets Chinese residents sports fitness behaviors exercise guide, which provides guidance for propelling to national fitness plan's implementation and improving Chinese resident fitness scientization. The paper starts from the perspective of energy consumption, it mainly adopts experience method, determines Chinese resident favorite sports fitness event energy consumption through observing all kinds of fitness behaviors energy consumption, and applies fuzzy analytic hierarchy process to make evaluation on bicycle riding, shadowboxing practicing, swimming, rope skipping, jogging, running, aerobics these seven fitness events. By calculating fuzzy rate model's membership and comparing their sizes, it gets fitness behaviors that are more helpful for resident health, more effective and popular. Finally, it gets conclusions that swimming is a best exercise mode and its membership is the highest. Besides, the memberships of running, rope skipping and shadowboxing practicing are also relative higher. It should go in for bodybuilding by synthesizing above several kinds of fitness events according to different physical conditions; different living conditions so that can better achieve the purpose of fitness exercises.

  8. A Fuzzy Query Mechanism for Human Resource Websites

    NASA Astrophysics Data System (ADS)

    Lai, Lien-Fu; Wu, Chao-Chin; Huang, Liang-Tsung; Kuo, Jung-Chih

    Users' preferences often contain imprecision and uncertainty that are difficult for traditional human resource websites to deal with. In this paper, we apply the fuzzy logic theory to develop a fuzzy query mechanism for human resource websites. First, a storing mechanism is proposed to store fuzzy data into conventional database management systems without modifying DBMS models. Second, a fuzzy query language is proposed for users to make fuzzy queries on fuzzy databases. User's fuzzy requirement can be expressed by a fuzzy query which consists of a set of fuzzy conditions. Third, each fuzzy condition associates with a fuzzy importance to differentiate between fuzzy conditions according to their degrees of importance. Fourth, the fuzzy weighted average is utilized to aggregate all fuzzy conditions based on their degrees of importance and degrees of matching. Through the mutual compensation of all fuzzy conditions, the ordering of query results can be obtained according to user's preference.

  9. Optimizing the pre-referral workup for gastroenterology and hepatology specialty care: consensus using the Delphi method.

    PubMed

    Ho, Chanda K; Boscardin, Christy K; Gleason, Nathaniel; Collado, Don; Terdiman, Jonathan; Terrault, Norah A; Gonzales, Ralph

    2016-02-01

    Specialty care referrals have doubled in the last decade. Optimization of the pre-referral workup by a primary care doctor can lead to a more efficient first specialty visit with the patient. Guidance regarding pre-referral laboratory testing is a first step towards improving the specialty referral process. Our aim was to establish consensus regarding appropriate pre-referral workup for common gastrointestinal and liver conditions. The Delphi method was used to establish local consensus for recommending certain laboratory tests prior to specialty referral for 13 clinical conditions. Seven conditions from The University of Michigan outpatient referral guidelines were used as a baseline. An expert panel of three PCPs and nine gastroenterologists from three academic hospitals participated in three iterative rounds of electronic surveys. Each panellist ranked each test using a 5-point Likert scale (strongly disagree to strongly agree). Local panellists could recommend additional tests for the initial diagnoses, and also recommended additional diagnoses needing guidelines: iron deficiency anaemia, abdominal pain, irritable bowel syndrome, fatty liver disease, liver mass and cirrhosis. Consensus was defined as ≥70% of experts scoring ≥4 (agree or strongly agree). Applying Delphi methodology to extrapolate externally developed referral guidelines for local implementation resulted in considerable modifications. For some conditions, many tests from the external group were eliminated by the local group (abdominal bloating; iron deficiency anaemia; irritable bowel syndrome). In contrast, for chronic diarrhoea, abnormal liver enzymes and viral hepatitis, all/most original tests were retained with additional tests added. For liver mass, fatty liver disease and cirrhosis, there was high concordance among the panel with few tests added or eliminated. Consideration of externally developed referral guidelines using a consensus-building process leads to significant local

  10. Convergent method of and apparatus for distributed control of robotic systems using fuzzy logic

    DOEpatents

    Feddema, John T.; Driessen, Brian J.; Kwok, Kwan S.

    2002-01-01

    A decentralized fuzzy logic control system for one vehicle or for multiple robotic vehicles provides a way to control each vehicle to converge on a goal without collisions between vehicles or collisions with other obstacles, in the presence of noisy input measurements and a limited amount of compute-power and memory on board each robotic vehicle. The fuzzy controller demonstrates improved robustness to noise relative to an exact controller.

  11. 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.

  12. Patient safety priorities in mental healthcare in Switzerland: a modified Delphi study

    PubMed Central

    Mascherek, Anna C

    2016-01-01

    Objective Identifying patient safety priorities in mental healthcare is an emerging issue. A variety of aspects of patient safety in medical care apply for patient safety in mental care as well. However, specific aspects may be different as a consequence of special characteristics of patients, setting and treatment. The aim of the present study was to combine knowledge from the field and research and bundle existing initiatives and projects to define patient safety priorities in mental healthcare in Switzerland. The present study draws on national expert panels, namely, round-table discussion and modified Delphi consensus method. Design As preparation for the modified Delphi questionnaire, two round-table discussions and one semistructured questionnaire were conducted. Preparative work was conducted between May 2015 and October 2015. The modified Delphi was conducted to gauge experts' opinion on priorities in patient safety in mental healthcare in Switzerland. In two independent rating rounds, experts made private ratings. The modified Delphi was conducted in winter 2015. Results Nine topics were defined along the treatment pathway: diagnostic errors, non-drug treatment errors, medication errors, errors related to coercive measures, errors related to aggression management against self and others, errors in treatment of suicidal patients, communication errors, errors at interfaces of care and structural errors. Conclusions Patient safety is considered as an important topic of quality in mental healthcare among experts, but it has been seriously neglected up until now. Activities in research and in practice are needed. Structural errors and diagnostics were given highest priority. From the topics identified, some are overlapping with important aspects of patient safety in medical care; however, some core aspects are unique. PMID:27496233

  13. Fuzzy Comprehensive Evaluation Method Applied in the Real Estate Investment Risks Research

    NASA Astrophysics Data System (ADS)

    ML(Zhang Minli), Zhang; Wp(Yang Wenpo), Yang

    Real estate investment is a high-risk and high returned of economic activity, the key of real estate analysis is the identification of their types of investment risk and the risk of different types of effective prevention. But, as the financial crisis sweeping the world, the real estate industry also faces enormous risks, how effective and correct evaluation of real estate investment risks becomes the multitudinous scholar concern[1]. In this paper, real estate investment risks were summarized and analyzed, and comparative analysis method is discussed and finally presented fuzzy comprehensive evaluation method, not only in theory has the advantages of science, in the application also has the reliability, for real estate investment risk assessment provides an effective means for investors in real estate investing guidance on risk factors and forecasts.

  14. 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…

  15. A generic method for the evaluation of interval type-2 fuzzy linguistic summaries.

    PubMed

    Boran, Fatih Emre; Akay, Diyar

    2014-09-01

    Linguistic summarization has turned out to be an important knowledge discovery technique by providing the most relevant natural language-based sentences in a human consistent manner. While many studies on linguistic summarization have handled ordinary fuzzy sets [type-1 fuzzy set (T1FS)] for modeling words, only few of them have dealt with interval type-2 fuzzy sets (IT2FS) even though IT2FS is better capable of handling uncertainties associated with words. Furthermore, the existent studies work with the scalar cardinality based degree of truth which might lead to inconsistency in the evaluation of interval type-2 fuzzy (IT2F) linguistic summaries. In this paper, to overcome this shortcoming, we propose a novel probabilistic degree of truth for evaluating IT2F linguistic summaries in the forms of type-I and type-II quantified sentences. We also extend the properties that should be fulfilled by any degree of truth on linguistic summarization with T1FS to IT2F environment. We not only prove that our probabilistic degree of truth satisfies the given properties, but also illustrate by examples that it provides more consistent results when compared to the existing degree of truth in the literature. Furthermore, we carry out an application on linguistic summarization of time series data of Europe Brent Spot Price, along with a comparison of the results achieved with our approach and that of the existing degree of truth in the literature.

  16. The Delphi Predictions of Pathology Chairmen: A Six-Year Retrospective View.

    ERIC Educational Resources Information Center

    Hill, Rolla B.; Goodale, Fairfield

    1981-01-01

    A retrospective review is reported of progress in academic pathology since 1974, when the Association of Pathology Chairmen undertook a Delphi study of pathology chairmen's expectations and desires for the future. The Delphi study was useful in alerting academic pathologists to opportunities and in coalescing activities toward achievement of…

  17. Fuzzy compromise: An effective way to solve hierarchical design problems

    NASA Technical Reports Server (NTRS)

    Allen, J. K.; Krishnamachari, R. S.; Masetta, J.; Pearce, D.; Rigby, D.; Mistree, F.

    1990-01-01

    In this paper, we present a method for modeling design problems using a compromise decision support problem (DSP) incorporating the principles embodied in fuzzy set theory. Specifically, the fuzzy compromise decision support problem is used to study hierarchical design problems. This approach has the advantage that although the system modeled has an element of uncertainty associated with it, the solution obtained is crisp and precise. The efficacy of incorporating fuzzy sets into the solution process is discussed in the context of results obtained for a portal frame.

  18. Fuzzy Commitment

    NASA Astrophysics Data System (ADS)

    Juels, Ari

    The purpose of this chapter is to introduce fuzzy commitment, one of the earliest and simplest constructions geared toward cryptography over noisy data. The chapter also explores applications of fuzzy commitment to two problems in data security: (1) secure management of biometrics, with a focus on iriscodes, and (2) use of knowledge-based authentication (i.e., personal questions) for password recovery.

  19. 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

  20. Mining Building Energy Management System Data Using Fuzzy Anomaly Detection and Linguistic Descriptions

    SciTech Connect

    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

  1. 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.

  2. Fuzzy time-series based on Fibonacci sequence for stock price forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

    2007-07-01

    Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

  3. A novel approach for analyzing fuzzy system reliability using different types of intuitionistic fuzzy failure rates of components.

    PubMed

    Kumar, Mohit; Yadav, Shiv Prasad

    2012-03-01

    This paper addresses the fuzzy system reliability analysis using different types of intuitionistic fuzzy numbers. Till now, in the literature, to analyze the fuzzy system reliability, it is assumed that the failure rates of all components of a system follow the same type of fuzzy set or intuitionistic fuzzy set. However, in practical problems, such type of situation rarely occurs. Therefore, in the present paper, a new algorithm has been introduced to construct the membership function and non-membership function of fuzzy reliability of a system having components following different types of intuitionistic fuzzy failure rates. Functions of intuitionistic fuzzy numbers are calculated to construct the membership function and non-membership function of fuzzy reliability via non-linear programming techniques. Using the proposed algorithm, membership functions and non-membership functions of fuzzy reliability of a series system and a parallel systems are constructed. Our study generalizes the various works of the literature. Numerical examples are given to illustrate the proposed algorithm. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Defining a Bobath clinical framework - A modified e-Delphi study.

    PubMed

    Vaughan-Graham, Julie; Cott, Cheryl

    2016-11-01

    To gain consensus within the expert International Bobath Instructors Training Association (IBITA) on a Bobath clinical framework on which future efficacy studies can be based. A three-round modified e-Delphi approach was used with 204 full members of the IBITA. Twenty-one initial statements were generated from the literature. Consensus was defined a priori as at least 80% of the respondents with a level of agreement on a Likert scale of 4 or 5. The Delphi questionnaire for each round was available online for two weeks. Summary reports and subsequent questionnaires were posted within four weeks. Ninety-four IBITA members responded, forming the Delphi panel, of which 68 and 66 responded to Rounds Two and Three, respectively. The 21 initial statements were revised to 17 statements and five new statements in Round Two in which eight statements were accepted and two statements were eliminated. Round Three presented 12 revised statements, all reaching consensus. The Delphi was successful in gaining consensus on a Bobath clinical framework in a geographically diverse expert association, identifying the unique components of Bobath clinical practice. Discussion throughout all three Rounds revolved primarily around the terminology of atypical and compensatory motor behavior and balance.

  5. Trends that FCS Education Should Address: A Delphi Study Reveals Top 16

    ERIC Educational Resources Information Center

    Alexander, Karen L.; Davis, Kimberlee

    2011-01-01

    This study used the Delphi method to identify trends of importance to family and consumer sciences (FCS) education. A panel of 21 FCS education experts identified 16 trends and evaluated them by importance, desirability, feasibility, and confidence in validity of the trend. Nutrition appeared as a top priority, followed by consumer economics. The…

  6. 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.

  7. On the Normed Space of Equivalence Classes of Fuzzy Numbers

    PubMed Central

    Lu, Chongxia; Zhang, Wei

    2013-01-01

    We study the norm induced by the supremum metric on the space of fuzzy numbers. And then we propose a method for constructing a norm on the quotient space of fuzzy numbers. This norm is very natural and works well with the induced metric on the quotient space. PMID:24072984

  8. Fuzzy model-based servo and model following control for nonlinear systems.

    PubMed

    Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

    2009-12-01

    This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

  9. Effect of defuzzification method of fuzzy modeling

    NASA Astrophysics Data System (ADS)

    Lapohos, Tibor; Buchal, Ralph O.

    1994-10-01

    Imprecision can arise in fuzzy relational modeling as a result of fuzzification, inference and defuzzification. These three sources of imprecision are difficult to separate. We have determined through numerical studies that an important source of imprecision is the defuzzification stage. This imprecision adversely affects the quality of the model output. The most widely used defuzzification algorithm is known by the name of `center of area' (COA) or `center of gravity' (COG). In this paper, we show that this algorithm not only maps the near limit values of the variables improperly but also introduces errors for middle domain values of the same variables. Furthermore, the behavior of this algorithm is a function of the shape of the reference sets. We compare the COA method to the weighted average of cluster centers (WACC) procedure in which the transformation is carried out based on the values of the cluster centers belonging to each of the reference membership functions instead of using the functions themselves. We show that this procedure is more effective and computationally much faster than the COA. The method is tested for a family of reference sets satisfying certain constraints, that is, for any support value the sum of reference membership function values equals one and the peak values of the two marginal membership functions project to the boundaries of the universe of discourse. For all the member sets of this family of reference sets the defuzzification errors do not get bigger as the linguistic variables tend to their extreme values. In addition, the more reference sets that are defined for a certain linguistic variable, the less the average defuzzification error becomes. In case of triangle shaped reference sets there is no defuzzification error at all. Finally, an alternative solution is provided that improves the performance of the COA method.

  10. 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.

  11. 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,...

  12. Determining content for a simulation-based curriculum in pediatric emergency medicine: results from a national Delphi process.

    PubMed

    Bank, Ilana; Cheng, Adam; McLeod, Peter; Bhanji, Farhan

    2015-11-01

    By the end of residency training, pediatric emergency medicine (PEM) residents are expected to have developed the confidence and abilities required to manage acutely ill children. Acquisition of competence requires exposure and/or supplemental formal education for critical and noncritical medical clinical presentations. Simulation can provide experiential learning and can improve trainees' knowledge, skills, and attitudes. The primary objective of this project was to identify the content for a simulation-based national curriculum for PEM training. We recruited participants for the Delphi study by contacting current PEM program directors and immediate past program directors as well as simulation experts at all of the Canadian PEM fellowship sites. We determined the appropriate core content for the Delphi study by combining the PEM core content requirements of the Royal College of Physicians and Surgeons of Canada (RCPSC) and the American Board of Pediatrics (ABP). Using the Delphi method, we achieved consensus amongst the national group of PEM and simulation experts. The participants completed a three-round Delphi (using a four-point Likert scale). Response rates for the Delphi were 85% for the first round and 77% for second and third rounds. From the initial 224 topics, 53 were eliminated (scored <2). Eighty-five topics scored between 2 and 3, and 87 scored between 3 and 4. The 48 topics, which were scored between 3.5 and 4.0, were labeled as "key curriculum topics." We have iteratively identified a consensus for the content of a national simulation-based curriculum.

  13. Acne severity grading: determining essential clinical components and features using a Delphi consensus.

    PubMed

    Tan, Jerry; Wolfe, Barat; Weiss, Jonathan; Stein-Gold, Linda; Bikowski, Joseph; Del Rosso, James; Webster, Guy F; Lucky, Anne; Thiboutot, Diane; Wilkin, Jonathan; Leyden, James; Chren, Mary-Margaret

    2012-08-01

    There are multiple global scales for acne severity grading but no singular standard. Our objective was to determine the essential clinical components (content items) and features (property-related items) for an acne global grading scale for use in research and clinical practice using an iterative method, the Delphi process. Ten acne experts were invited to participate in a Web-based Delphi survey comprising 3 iterative rounds of questions. In round 1, the experts identified the following clinical components (primary acne lesions, number of lesions, extent, regional involvement, secondary lesions, and patient experiences) and features (clinimetric properties, ease of use, categorization of severity based on photographs or text, and acceptance by all stakeholders). In round 2, consensus for inclusion in the scale was established for primary lesions, number, sites, and extent; as well as clinimetric properties and ease of use. In round 3, consensus for inclusion was further established for categorization and acceptance. Patient experiences were excluded and no consensus was achieved for secondary lesions. The Delphi panel consisted solely of the United States (U.S.)-based acne experts. Using an established method for achieving consensus, experts in acne vulgaris concluded that an ideal acne global grading scale would comprise the essential clinical components of primary acne lesions, their quantity, extent, and facial and extrafacial sites of involvement; with features of clinimetric properties, categorization, efficiency, and acceptance. Copyright © 2011 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

  14. Measuring uncertainty by extracting fuzzy rules using rough sets

    NASA Technical Reports Server (NTRS)

    Worm, Jeffrey A.

    1991-01-01

    Despite the advancements in the computer industry in the past 30 years, there is still one major deficiency. Computers are not designed to handle terms where uncertainty is present. To deal with uncertainty, techniques other than classical logic must be developed. The methods are examined of statistical analysis, the Dempster-Shafer theory, rough set theory, and fuzzy set theory to solve this problem. The fundamentals of these theories are combined to possibly provide the optimal solution. By incorporating principles from these theories, a decision making process may be simulated by extracting two sets of fuzzy rules: certain rules and possible rules. From these rules a corresponding measure of how much these rules is believed is constructed. From this, the idea of how much a fuzzy diagnosis is definable in terms of a set of fuzzy attributes is studied.

  15. Evaluating supplier quality performance using fuzzy analytical hierarchy process

    NASA Astrophysics Data System (ADS)

    Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

    2014-12-01

    Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

  16. 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

  17. Fuzzy multiobjective models for optimal operation of a hydropower system

    NASA Astrophysics Data System (ADS)

    Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

    2013-06-01

    Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

  18. Application of neuro-fuzzy methods to gamma spectroscopy

    NASA Astrophysics Data System (ADS)

    Grelle, Austin L.

    Nuclear non-proliferation activities are an essential part of national security activities both domestic and abroad. The safety of the public in densely populated environments such as urban areas or large events can be compromised if devices using special nuclear materials are present. Therefore, the prompt and accurate detection of these materials is an important topic of research, in which the identification of normal conditions is also of importance. With gamma-ray spectroscopy, these conditions are identified as the radiation background, which though being affected by a multitude of factors is ever present. Therefore, in nuclear non-proliferation activities the accurate identification of background is important. With this in mind, a method has been developed to utilize aggregate background data to predict the background of a location through the use of an Artificial Neural Network (ANN). After being trained on background data, the ANN is presented with nearby relevant gamma-ray spectroscopy data---as identified by a Fuzzy Inference System - to create a predicted background spectra to compare to a measured spectra. If a significant deviation exists between the predicted and measured data, the method alerts the user such that a more thorough investigation can take place. Research herein focused on data from an urban setting in which the number of false positives was observed to be 28 out of a total of 987, representing 2.94% error. The method therefore currently shows a high rate of false positives given the current configuration, however there are promising steps that can be taken to further minimize this error. With this in mind, the method stands as a potentially significant tool in urban nuclear nonproliferation activities.

  19. 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.

  20. Development of criteria for evaluating clinical response in thyroid eye disease using a modified Delphi technique.

    PubMed

    Douglas, Raymond S; Tsirbas, Angelo; Gordon, Mark; Lee, Diana; Khadavi, Nicole; Garneau, Helene Chokron; Goldberg, Robert A; Cahill, Kenneth; Dolman, Peter J; Elner, Victor; Feldon, Steve; Lucarelli, Mark; Uddin, Jimmy; Kazim, Michael; Smith, Terry J; Khanna, Dinesh

    2009-09-01

    To identify components of a provisional clinical response index for thyroid eye disease using a modified Delphi technique. The International Thyroid Eye Disease Society conducted a structured, 3-round Delphi exercise establishing consensus for a core set of measures for clinical trials in thyroid eye disease. The steering committee discussed the results in a face-to-face meeting (nominal group technique) and evaluated each criterion with respect to its feasibility, reliability, redundancy, and validity. Redundant measures were consolidated or excluded. Criteria were parsed into 11 domains for the Delphi surveys. Eighty-four respondents participated in the Delphi 1 survey, providing 220 unique items. Ninety-two members (100% of the respondents from Delphi 1 plus 8 new participants) responded in Delphi 2 and rated the same 220 items. Sixty-four members (76% of participants) rated 153 criteria in Delphi 3 (67 criteria were excluded because of redundancy). Criteria with a mean greater than 6 (1 = least appropriate to 9 = most appropriate) were further evaluated by the nominal group technique and provisional core measures were chosen. Using a Delphi exercise, we developed provisional core measures for assessing disease activity and severity in clinical trials of therapies for thyroid eye disease. These measures will be iteratively refined for use in multicenter clinical trials.

  1. Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.

    PubMed

    Wu, Chunsheng; Liu, Gaohuan; Huang, Chong; Liu, Qingsheng; Guan, Xudong

    2018-04-25

    The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures. The aim of this study was to obtain the spatial distribution of the ecological vulnerability (EV) in YRD based on 21 indicators selected from underwater status, soil condition, land use, landform, vegetation cover, meteorological conditions, ocean influence, and social economy. In addition, the fuzzy analytic hierarchy process (FAHP) method was used to obtain the weights of the selected indicators, and a fuzzy logic model was constructed to obtain the result. The result showed that the spatial distribution of the EV grades was regular, while the fuzzy membership of EV decreased gradually from the coastline to inland area, especially around the river crossing, where it had the lowest EV. Along the coastline, the dikes had an obviously protective effect for the inner area, while the EV was higher in the area where no dikes were built. This result also showed that the soil condition and groundwater status were highly related to the EV spatially, with the correlation coefficients −0.55 and −0.74 respectively, and human activities had exerted considerable pressure on the ecological environment.

  2. A novel segmentation method for uneven lighting image with noise injection based on non-local spatial information and intuitionistic fuzzy entropy

    NASA Astrophysics Data System (ADS)

    Yu, Haiyan; Fan, Jiulun

    2017-12-01

    Local thresholding methods for uneven lighting image segmentation always have the limitations that they are very sensitive to noise injection and that the performance relies largely upon the choice of the initial window size. This paper proposes a novel algorithm for segmenting uneven lighting images with strong noise injection based on non-local spatial information and intuitionistic fuzzy theory. We regard an image as a gray wave in three-dimensional space, which is composed of many peaks and troughs, and these peaks and troughs can divide the image into many local sub-regions in different directions. Our algorithm computes the relative characteristic of each pixel located in the corresponding sub-region based on fuzzy membership function and uses it to replace its absolute characteristic (its gray level) to reduce the influence of uneven light on image segmentation. At the same time, the non-local adaptive spatial constraints of pixels are introduced to avoid noise interference with the search of local sub-regions and the computation of local characteristics. Moreover, edge information is also taken into account to avoid false peak and trough labeling. Finally, a global method based on intuitionistic fuzzy entropy is employed on the wave transformation image to obtain the segmented result. Experiments on several test images show that the proposed method has excellent capability of decreasing the influence of uneven illumination on images and noise injection and behaves more robustly than several classical global and local thresholding methods.

  3. Fuzzy self-learning control for magnetic servo system

    NASA Technical Reports Server (NTRS)

    Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

    1994-01-01

    It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

  4. Fuzzy jets

    SciTech Connect

    Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel

    Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variablesmore » in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.« less

  5. Fuzzy jets

    DOE PAGES

    Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel; ...

    2016-06-01

    Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variablesmore » in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.« less

  6. Complex fuzzy soft expert sets

    NASA Astrophysics Data System (ADS)

    Selvachandran, Ganeshsree; Hafeed, Nisren A.; Salleh, Abdul Razak

    2017-04-01

    Complex fuzzy sets and its accompanying theory although at its infancy, has proven to be superior to classical type-1 fuzzy sets, due its ability in representing time-periodic problem parameters and capturing the seasonality of the fuzziness that exists in the elements of a set. These are important characteristics that are pervasive in most real world problems. However, there are two major problems that are inherent in complex fuzzy sets: it lacks a sufficient parameterization tool and it does not have a mechanism to validate the values assigned to the membership functions of the elements in a set. To overcome these problems, we propose the notion of complex fuzzy soft expert sets which is a hybrid model of complex fuzzy sets and soft expert sets. This model incorporates the advantages of complex fuzzy sets and soft sets, besides having the added advantage of allowing the users to know the opinion of all the experts in a single model without the need for any additional cumbersome operations. As such, this model effectively improves the accuracy of representation of problem parameters that are periodic in nature, besides having a higher level of computational efficiency compared to similar models in literature.

  7. Research Priorities for YouTube and Video-Sharing Technologies: A Delphi Study

    ERIC Educational Resources Information Center

    Snelson, Chareen; Rice, Kerry; Wyzard, Constance

    2012-01-01

    Online video-sharing services, particularly YouTube, have gained an audience of billions of users including educators and scholars. While the academic literature provides some evidence that YouTube has been studied and written about, little is known about priorities for YouTube research. The study employed the Delphi method to obtain a consensus…

  8. Collaborating Fuzzy Reinforcement Learning Agents

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1997-01-01

    Earlier, we introduced 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 Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

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

    SciTech Connect

    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

  10. Performance Degradation Assessment of Rolling Element Bearings using Improved Fuzzy Entropy

    NASA Astrophysics Data System (ADS)

    Zhu, Keheng; Jiang, Xiaohui; Chen, Liang; Li, Haolin

    2017-10-01

    Rolling element bearings are an important unit in the rotating machines, and their performance degradation assessment is the basis of condition-based maintenance. Targeting the non-linear dynamic characteristics of faulty signals of rolling element bearings, a bearing performance degradation assessment approach based on improved fuzzy entropy (FuzzyEn) is proposed in this paper. FuzzyEn has less dependence on data length and achieves more freedom of parameter selection and more robustness to noise. However, it neglects the global trend of the signal when calculating similarity degree of two vectors, and thus cannot reflect the running state of the rolling element bearings accurately. Based on this consideration, the algorithm of FuzzyEn is improved in this paper and the improved FuzzyEn is utilized as an indicator for bearing performance degradation evaluation. The vibration data from run-to-failure test of rolling element bearings are used to validate the proposed method. The experimental results demonstrate that, compared with the traditional kurtosis and root mean square, the proposed method can detect the incipient fault in advance and can reflect the whole performance degradation process more clearly.

  11. 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.

  12. 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

  13. A fuzzy automated object classification by infrared laser camera

    NASA Astrophysics Data System (ADS)

    Kanazawa, Seigo; Taniguchi, Kazuhiko; Asari, Kazunari; Kuramoto, Kei; Kobashi, Syoji; Hata, Yutaka

    2011-06-01

    Home security in night is very important, and the system that watches a person's movements is useful in the security. This paper describes a classification system of adult, child and the other object from distance distribution measured by an infrared laser camera. This camera radiates near infrared waves and receives reflected ones. Then, it converts the time of flight into distance distribution. Our method consists of 4 steps. First, we do background subtraction and noise rejection in the distance distribution. Second, we do fuzzy clustering in the distance distribution, and form several clusters. Third, we extract features such as the height, thickness, aspect ratio, area ratio of the cluster. Then, we make fuzzy if-then rules from knowledge of adult, child and the other object so as to classify the cluster to one of adult, child and the other object. Here, we made the fuzzy membership function with respect to each features. Finally, we classify the clusters to one with the highest fuzzy degree among adult, child and the other object. In our experiment, we set up the camera in room and tested three cases. The method successfully classified them in real time processing.

  14. Group Decision Making Based on Heronian Aggregation Operators of Intuitionistic Fuzzy Numbers.

    PubMed

    Liu, Peide; Chen, Shyi-Ming

    2017-09-01

    Archimedean t -conorm and t -norm provide the general operational rules for intuitionistic fuzzy numbers (IFNs). The aggregation operators based on them can generalize most of the existing aggregation operators. At the same time, the Heronian mean (HM) has a significant advantage of considering interrelationships between the attributes. Therefore, it is very necessary to extend the HM based on IFNs and to construct intuitionistic fuzzy HM operators based on the Archimedean t -conorm and t -norm. In this paper, we first discuss intuitionistic fuzzy operational rules based on the Archimedean t -conorm and t -norm. Then, we propose the intuitionistic fuzzy Archimedean Heronian aggregation (IFAHA) operator and the intuitionistic fuzzy weight Archimedean Heronian aggregation (IFWAHA) operator. We also further discuss some properties and some special cases of these new operators. Moreover, we also propose a new multiple attribute group decision making (MAGDM) method based on the proposed IFAHA operator and the proposed IFWAHA operator. Finally, we use an illustrative example to show the MAGDM processes and to illustrate the effectiveness of the developed method.

  15. a New Method for Fmeca Based on Fuzzy Theory and Expert System

    NASA Astrophysics Data System (ADS)

    Byeon, Yoong-Tae; Kim, Dong-Jin; Kim, Jin-O.

    2008-10-01

    Failure Mode Effects and Criticality Analysis (FMECA) is one of most widely used methods in modern engineering system to investigate potential failure modes and its severity upon the system. FMECA evaluates criticality and severity of each failure mode and visualize the risk level matrix putting those indices to column and row variable respectively. Generally, those indices are determined subjectively by experts and operators. However, this process has no choice but to include uncertainty. In this paper, a method for eliciting expert opinions considering its uncertainty is proposed to evaluate the criticality and severity. In addition, a fuzzy expert system is constructed in order to determine the crisp value of risk level for each failure mode. Finally, an illustrative example system is analyzed in the case study. The results are worth considering in deciding the proper policies for each component of the system.

  16. 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.

  17. 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.

  18. Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning

    NASA Astrophysics Data System (ADS)

    Zhou, Huan; Wang, Jian-qiang; Zhang, Hong-yu; Chen, Xiao-hong

    2016-01-01

    Linguistic hesitant fuzzy sets (LHFSs), which can be used to represent decision-makers' qualitative preferences as well as reflect their hesitancy and inconsistency, have attracted a great deal of attention due to their flexibility and efficiency. This paper focuses on a multi-criteria decision-making approach that combines LHFSs with the evidential reasoning (ER) method. After reviewing existing studies of LHFSs, a new order relationship and Hamming distance between LHFSs are introduced and some linguistic scale functions are applied. Then, the ER algorithm is used to aggregate the distributed assessment of each alternative. Subsequently, the set of aggregated alternatives on criteria are further aggregated to get the overall value of each alternative. Furthermore, a nonlinear programming model is developed and genetic algorithms are used to obtain the optimal weights of the criteria. Finally, two illustrative examples are provided to show the feasibility and usability of the method, and comparison analysis with the existing method is made.

  19. Establishing key components of yoga interventions for musculoskeletal conditions: a Delphi survey

    PubMed Central

    2014-01-01

    Background Evidence suggests yoga is a safe and effective intervention for the management of physical and psychosocial symptoms associated with musculoskeletal conditions. However, heterogeneity in the components and reporting of clinical yoga trials impedes both the generalization of study results and the replication of study protocols. The aim of this Delphi survey was to address these issues of heterogeneity, by developing a list of recommendations of key components for the design and reporting of yoga interventions for musculoskeletal conditions. Methods Recognised experts involved in the design, conduct, and teaching of yoga for musculoskeletal conditions were identified from a systematic review, and invited to contribute to the Delphi survey. Forty-one of the 58 experts contacted, representing six countries, agreed to participate. A three-round Delphi was conducted via electronic surveys. Round 1 presented an open-ended question, allowing panellists to individually identify components they considered key to the design and reporting of yoga interventions for musculoskeletal conditions. Thematic analysis of Round 1 identified items for quantitative rating in Round 2; items not reaching consensus were forwarded to Round 3 for re-rating. Results Thirty-six panellists (36/41; 88%) completed the three rounds of the Delphi survey. Panellists provided 348 comments to the Round 1 question. These comments were reduced to 49 items, grouped under five themes, for rating in subsequent rounds. A priori group consensus of ≥80% was reached on 28 items related to five themes concerning defining the yoga intervention, types of yoga practices to include in an intervention, delivery of the yoga protocol, domains of outcome measures, and reporting of yoga interventions for musculoskeletal conditions. Additionally, a priori consensus of ≥50% was reached on five items relating to minimum values for intervention parameters. Conclusions Expert consensus has provided a non

  20. Fuzzy decision analysis for integrated environmental vulnerability assessment of the mid-Atlantic Region.

    PubMed

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

    2002-06-01

    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, air pollution, and topography of the Mid-Atlantic region, we were able to point out areas that were in relatively poor condition and/or vulnerable to future deterioration. The method offered an easy and comprehensive way to combine the strengths of fuzzy set theory and the AHP for ecological assessment. Furthermore, the suggested method can serve as a building block for the evaluation of environmental policies.