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Sample records for prices forecast comparison aeo

  1. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect

    Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

    2008-01-07

    On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and

  2. Comparison of forecasting methodologies using egg price as a test case.

    PubMed

    Ahmad, H A; Mariano, M

    2006-04-01

    Egg price forecasting of shelled eggs is a complex problem. Traditionally, future egg price has been predicted using a combination of regression analysis and experienced-based intuition to build a model, which is then fine-tuned to prevalent market conditions. Even after collecting reliable and expensive data, the subsequent analysis, in many cases, does not produce a high confidence to explain the variations in egg price. In the current project, a different approach using neural networks was used to forecast egg price. A neural network is a mathematical model of an information-processing structure that is loosely based on our present understanding of the working of human brain. An artificial neural network consists of a large number of simple processing elements connected to each other in a network. Urner Barry egg quotes from 1991 to 2002 as well as number of hens, egg storage capacity, and number of eggs placed for hatching from the USDA databases (1993 to 2000) were used to forecast egg price. Regression analysis explained only 37% of the variation in egg price due to the above-mentioned 3 factors. Neural networks, on the other hand, recognize the pattern in previous years' egg prices and then predict the future price more efficiently. The 3 networks used in this research (Ward, back-propagation, and general regression neural networks) fit the forecast line more tightly to the previous year's egg price line than did regression analysis. In the case of general regression neural networks, the R2 value was as high as 60%. Results suggest that neural networks may be a more reliable method of egg price forecasting than simple regression analysis if reliable data are collected and manipulated for such models.

  3. Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models

    EIA Publications

    2003-01-01

    This paper describes the demand responses to changes in energy prices in the Annual Energy Outlook 2003 versions of the Residential and Commercial Demand Modules of the National Energy Modeling System (NEMS). It updates a similar paper completed for the Annual Energy Outlook 1999 version of the NEMS.

  4. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    EIA Publications

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  5. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e

  6. Support vector machine for day ahead electricity price forecasting

    NASA Astrophysics Data System (ADS)

    Razak, Intan Azmira binti Wan Abdul; Abidin, Izham bin Zainal; Siah, Yap Keem; Rahman, Titik Khawa binti Abdul; Lada, M. Y.; Ramani, Anis Niza binti; Nasir, M. N. M.; Ahmad, Arfah binti

    2015-05-01

    Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. SVM that widely used for classification and regression has great generalization ability with structured risk minimization principle rather than empirical risk minimization. Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. The mean absolute percentage error (MAPE) for the proposed model shows that SVM performs well compared to neural network.

  7. Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models

    NASA Astrophysics Data System (ADS)

    Areekul, Phatchakorn; Senjyu, Tomonobu; Urasaki, Naomitsu; Yona, Atsushi

    Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.

  8. Electricity price short-term forecasting using artificial neural networks

    SciTech Connect

    Szkuta, B.R.; Sanabria, L.A.; Dillon, T.S.

    1999-08-01

    This paper presents the System Marginal Price (SMP) short-term forecasting implementation using the Artificial Neural Networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with back-propagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP.

  9. Dynamical behavior of price forecasting in structures of group correlations

    NASA Astrophysics Data System (ADS)

    Lim, Kyuseong; Kim, Soo Yong; Kim, Kyungsik

    2015-07-01

    We investigate the prediction of the future prices from the structures and the networks of the companies in special financial groups. After the financial group network has been constructed from the value of the high cross-correlation, each company in a group is simulated and analyzed how it buys or sells stock is anaylzed and how it makes rational investments is forecasted. In the shortmemory behavior rather than the long-memory behavior, each company among a group can make a rational investment decision by using a stochastic evolution rule in the financial network. In particular, we simulate and analyze the investment situation in connection with the empirical data and the simulated result.

  10. Issues in midterm analysis and forecasting 1998

    SciTech Connect

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  11. Forecasting prices of single family homes using GIS-defined neighborhoods

    NASA Astrophysics Data System (ADS)

    Kaboudan, Mak; Sarkar, Avijit

    2008-03-01

    We estimate spatiotemporal models of average neighborhood single family home prices to use in predicting individual property prices. Average home-price variations are explained in terms of changes in average neighborhood house attributes, spatial attributes, and temporal economic variables. Models adopting three different definitions of neighborhoods are estimated with quarterly cross-sectional data over the period 2000 2004 from four cities in Southern California. Heteroscedasticity and autocorrelation problems are detected and adjusted for via a sequential routine. Results of these models suggest that forecasts obtained using city neighborhood average price equations may have advantage over forecasts obtained using city aggregated price equations.

  12. Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

    PubMed

    Jin, Junghwan; Kim, Jinsoo

    2015-01-01

    Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.

  13. Research on WNN modeling for gold price forecasting based on improved artificial bee colony algorithm.

    PubMed

    Li, Bai

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme.

  14. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

  15. 2007 Wholesale Power Rate Case Initial Proposal : Market Price Forecast Study.

    SciTech Connect

    United States. Bonneville Power Administration.

    2005-11-01

    This chapter presents BPA's market price forecasts, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's rates. AURORA is used as the primary tool for (a) calculation of the demand rate, (b) shaping the PF rate, (c) estimating the forward price for the IOU REP settlement benefits calculation for fiscal years 2008 and 2009, (d) estimating the uncertainty surrounding DSI payments, (e) informing the secondary revenue forecast and (f) providing a price input used for the risk analysis.

  16. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  17. Coal demand and price projections. Volume 2. Forecast tables. Final topical report, January-December 1993

    SciTech Connect

    Hill, F.E.; Watkins, J.A.

    1994-02-01

    Hill and Associates, Inc. performed a series of coal market and price forecasts for the Gas Research Institute (GRI) to determine both the supply constraints on available quantities of coal and the projected coal prices from each U.S. coal supply region into each National Energy Reliability Council (NERC) and GRI demand region. Volume II contains the forecast tables and includes the same set of appendixes as Volume I.

  18. Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price

    NASA Astrophysics Data System (ADS)

    Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John

    2015-02-01

    Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.

  19. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... (constructed export price). 351.414 Section 351.414 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE ANTIDUMPING AND COUNTERVAILING DUTIES Calculation of Export Price, Constructed Export Price, Fair Value, and Normal Value § 351.414 Comparison of normal value with export price...

  20. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... (constructed export price). 351.414 Section 351.414 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE ANTIDUMPING AND COUNTERVAILING DUTIES Calculation of Export Price, Constructed Export Price, Fair Value, and Normal Value § 351.414 Comparison of normal value with export price...

  1. Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks

    PubMed Central

    2015-01-01

    Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency. PMID:26539722

  2. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 16 Commercial Practices 1 2013-01-01 2013-01-01 false Former price comparisons. 233.1 Section 233.1 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of...

  3. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 16 Commercial Practices 1 2012-01-01 2012-01-01 false Former price comparisons. 233.1 Section 233.1 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of...

  4. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Former price comparisons. 233.1 Section 233.1 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of...

  5. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Miscellaneous price comparisons. 233.5 Section 233.5 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set...

  6. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 16 Commercial Practices 1 2012-01-01 2012-01-01 false Miscellaneous price comparisons. 233.5 Section 233.5 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set...

  7. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 16 Commercial Practices 1 2013-01-01 2013-01-01 false Miscellaneous price comparisons. 233.5 Section 233.5 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set...

  8. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Miscellaneous price comparisons. 233.5 Section 233.5 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set...

  9. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 16 Commercial Practices 1 2014-01-01 2014-01-01 false Former price comparisons. 233.1 Section 233.1 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of...

  10. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 16 Commercial Practices 1 2014-01-01 2014-01-01 false Miscellaneous price comparisons. 233.5 Section 233.5 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set...

  11. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Former price comparisons. 233.1 Section 233.1 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES GUIDES AGAINST DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of...

  12. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  13. ARIMA Model Estimated by Particle Swarm Optimization Algorithm for Consumer Price Index Forecasting

    NASA Astrophysics Data System (ADS)

    Wang, Hongjie; Zhao, Weigang

    This paper presents an ARIMA model which uses particle swarm optimization algorithm (PSO) for model estimation. Because the traditional estimation method is complex and may obtain very bad results, PSO which can be implemented with ease and has a powerful optimizing performance is employed to optimize the coefficients of ARIMA. In recent years, inflation and deflation plague the world moreover the consumer price index (CPI) which is a measure of the average price of consumer goods and services purchased by households is usually observed as an important indicator of the level of inflation, so the forecast of CPI has been focused on by both scientific community and relevant authorities. Furthermore, taking the forecast of CPI as a case, we illustrate the improvement of accuracy and efficiency of the new method and the result shows it is predominant in forecasting.

  14. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  15. Traffic flow forecasting: Comparison of modeling approaches

    SciTech Connect

    Smith, B.L.; Demetsky, M.J.

    1997-08-01

    The capability to forecast traffic volume in an operational setting has been identified as a critical need for intelligent transportation systems (ITS). In particular, traffic volume forecasts will support proactive, dynamic traffic control. However, previous attempts to develop traffic volume forecasting models have met with limited success. This research effort focused on developing traffic volume forecasting models for two sites on Northern Virginia`s Capital Beltway. Four models were developed and tested for the freeway traffic flow forecasting problem, which is defined as estimating traffic flow 15 min into the future. They were the historical average, time-series, neural network, and nonparametric regression models. The nonparametric regression model significantly outperformed the other models. A Wilcoxon signed-rank test revealed that the nonparametric regression model experienced significantly lower errors than the other models. In addition, the nonparametric regression model was easy to implement, and proved to be portable, performing well at two distinct sites. Based on its success, research is ongoing to refine the nonparametric regression model and to extend it to produce multiple interval forecasts.

  16. Forecasting of Market Clearing Price by Using GA Based Neural Network

    NASA Astrophysics Data System (ADS)

    Yang, Bo; Chen, Yun-Ping; Zhao, Zun-Lian; Han, Qi-Ye

    Forecasting of Market Clearing Price (MCP) is important to economic benefits of electricity market participants. To accurately forecast MCP, a novel two-stage GA-based neural network model (GA-NN) is proposed. In the first stage, GA chromosome is designed into two parts: boolean coding part for neural network topology and real coding part for connection weights. By hybrid genetic operation of selection, crossover and mutation under the criterion of error minimization between the actual output and the desired output, optimal architecture of neural network is obtained. In the second stage, gradient learning algorithm with momentum rate is imposed on neural network with optimal architecture. After learning process, optimal connection weights are obtained. The proposed model is tested on MCP forecasting in California electricity market. The test results show that GA-NN has self-adaptive ability in its topology and connection weights and can obtain more accurate MCP forecasting values than BP neural network.

  17. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  18. Factors influencing the difference between forecasted and actual drug sales volumes under the price-volume agreement in South Korea.

    PubMed

    Park, Sun-Young; Han, Euna; Kim, Jini; Lee, Eui-Kyung

    2016-08-01

    This study analyzed factors contributing to increases in the actual sales volumes relative to forecasted volumes of drugs under price-volume agreement (PVA) policy in South Korea. Sales volumes of newly listed drugs on the national formulary are monitored under PVA policy. When actual sales volume exceeds the pre-agreed forecasted volume by 30% or more, the drug is subject to price-reduction. Logistic regression assessed the factors related to whether drugs were the PVA price-reduction drugs. A generalized linear model with gamma distribution and log-link assessed the factors influencing the increase in actual volumes compared to forecasted volume in the PVA price-reduction drugs. Of 186 PVA monitored drugs, 34.9% were price-reduction drugs. Drugs marketed by pharmaceutical companies with previous-occupation in the therapeutic markets were more likely to be PVA price-reduction drugs than drugs marketed by firms with no previous-occupation. Drugs of multinational pharmaceutical companies were more likely to be PVA price-reduction drugs than those of domestic companies. Having more alternative existing drugs was significantly associated with higher odds of being PVA price-reduction drugs. Among the PVA price-reduction drugs, the increasing rate of actual volume compared to forecasted volume was significantly higher in drugs with clinical usefulness. By focusing the negotiation efforts on those target drugs, PVA policy can be administered more efficiently with the improved predictability of the drug sales volumes.

  19. Price comparisons on the internet based on computational intelligence.

    PubMed

    Kim, Jun Woo; Ha, Sung Ho

    2014-01-01

    Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner.

  20. Price Comparisons on the Internet Based on Computational Intelligence

    PubMed Central

    Kim, Jun Woo; Ha, Sung Ho

    2014-01-01

    Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner. PMID:25268901

  1. A Comparison of Flare Forecasting Parameters Derived From Photospheric Magnetograms

    NASA Astrophysics Data System (ADS)

    Barnes, G.; Leka, K.

    2007-12-01

    A variety of researchers have proposed parameters for use in forecasting of solar flares. However, the parameters have been calculated from different data sources, and their performance has been judged based on various different criteria. We present here a systematic comparison of a small number of parameters which can be derived from the photospheric magnetic field, some of which characterize the photospheric field itself, and some which characterize the coronal magnetic topology. We compute the parameters for a collection of over 1200 vector magnetograms from the Imaging Vector Magnetograph at Haleakala, and judge their ability to forecast flares based on discriminant analysis, climatological skill scores, and the ability to provide an "all-clear" forecast.

  2. Impact of External Price Referencing on Medicine Prices – A Price Comparison Among 14 European Countries

    PubMed Central

    Leopold, Christine; Mantel-Teeuwisse, Aukje Katja; Seyfang, Leonhard; Vogler, Sabine; de Joncheere, Kees; Laing, Richard Ogilvie; Leufkens, Hubert

    2012-01-01

    Objectives: This study aims to examine the impact of external price referencing (EPR) on on-patent medicine prices, adjusting for other factors that may affect price levels such as sales volume, exchange rates, gross domestic product (GDP) per capita, total pharmaceutical expenditure (TPE), and size of the pharmaceutical industry. Methods: Price data of 14 on-patent products, in 14 European countries in 2007 and 2008 were obtained from the Pharmaceutical Price Information Service of the Austrian Health Institute. Based on the unit ex-factory prices in EURO, scaled ranks per country and per product were calculated. For the regression analysis the scaled ranks per country and product were weighted; each country had the same sum of weights but within a country the weights were proportional to its sales volume in the year (data obtained from IMS Health). Taking the scaled ranks, several statistical analyses were performed by using the program “R”, including a multiple regression analysis (including variables such as GDP per capita and national industry size). Results: This study showed that on average EPR as a pricing policy leads to lower prices. However, the large variation in price levels among countries using EPR confirmed that the price level is not only driven by EPR. The unadjusted linear regression model confirms that applying EPR in a country is associated with a lower scaled weighted rank (p=0.002). This interaction persisted after inclusion of total pharmaceutical expenditure per capita and GDP per capita in the final model. Conclusions: The study showed that for patented products, prices are in general lower in case the country applied EPR. Nevertheless substantial price differences among countries that apply EPR could be identified. Possible explanations could be found through a correlation between pharmaceutical industry and the scaled price ranks. In conclusion, we found that implementing external reference pricing could lead to lower prices. PMID

  3. ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

    PubMed Central

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓp-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ1-norm multiple support vector regression model. PMID:23365561

  4. Forecasting of palm oil price in Malaysia using linear and nonlinear methods

    NASA Astrophysics Data System (ADS)

    Nor, Abu Hassan Shaari Md; Sarmidi, Tamat; Hosseinidoust, Ehsan

    2014-09-01

    The first question that comes to the mind is: "How can we predict the palm oil price accurately?" This question is the authorities, policy makers and economist's question for a long period of time. The first reason is that in the recent years Malaysia showed a comparative advantage in palm oil production and has become top producer and exporter in the world. Secondly, palm oil price plays significant role in government budget and represents important source of income for Malaysia, which potentially can influence the magnitude of monetary policies and eventually have an impact on inflation. Thirdly, knowledge on the future trends would be helpful in the planning and decision making procedures and will generate precise fiscal and monetary policy. Daily data on palm oil prices along with the ARIMA models, neural networks and fuzzy logic systems are employed in this paper. Empirical findings indicate that the dynamic neural network of NARX and the hybrid system of ANFIS provide higher accuracy than the ARIMA and static neural network for forecasting the palm oil price in Malaysia.

  5. Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

    NASA Astrophysics Data System (ADS)

    Teneng, Dean

    2013-09-01

    We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

  6. Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

    PubMed

    Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

    2014-01-01

    As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

  7. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

    PubMed Central

    Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

    2014-01-01

    As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

  8. High Resolution Imaging with AEOS

    SciTech Connect

    Patience, J; Macintosh, B A; Max, C E

    2001-08-27

    The U. S. Air Force Advanced Electro-Optical System (AEOS) which includes a 941 actuator adaptive optics system on a 3.7m telescope has recently been made available for astronomical programs. Operating at a wavelength of 750 nm, the diffraction-limited angular resolution of the system is 0.04 inches; currently, the magnitude limit is V {approx} 7 mag. At the distances of nearby open clusters, diffraction-limited images should resolve companions with separations as small as 4-6 AU--comparable to the Sun-Jupiter distance. The ability to study such close separations is critical, since most companions are expected to have separations in the few AU to tens of AU range. With the exceptional angular resolution of the current AEOS setup, but restricted target magnitude range, we are conducting a companion search of a large, well-defined sample of bright early-type stars in nearby open clusters and in the field. Our data set will both characterize this relatively new adaptive optics system and answer questions in binary star formation and stellar X-ray activity. We will discuss our experience using AEOS, the data analysis involved, and our initial results.

  9. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

    PubMed

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  10. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

    PubMed

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

  11. Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2003-12-18

    For better or worse, natural gas has become the fuel of choice for new power plants being built across the United States. According to the US Energy Information Administration (EIA), natural gas combined-cycle and combustion turbine power plants accounted for 96% of the total generating capacity added in the US between 1999 and 2002--138 GW out of a total of 144 GW. Looking ahead, the EIA expects that gas-fired technology will account for 61% of the 355 GW new generating capacity projected to come on-line in the US up to 2025, increasing the nationwide market share of gas-fired generation from 18% in 2002 to 22% in 2025. While the data are specific to the US, natural gas-fired generation is making similar advances in other countries as well. Regardless of the explanation for (or interpretation of) the empirical findings, however, the basic implications remain the same: one should not blindly rely on gas price forecasts when comparing fixed-price renewable with variable-price gas-fired generation contracts. If there is a cost to hedging, gas price forecasts do not capture and account for it. Alternatively, if the forecasts are at risk of being biased or out of tune with the market, then one certainly would not want to use them as the basis for resource comparisons or investment decisions if a more certain source of data (forwards) existed. Accordingly, assuming that long-term price stability is valued, the most appropriate way to compare the levelized cost of these resources in both cases would be to use forward natural gas price data--i.e. prices that can be locked in to create price certainty--as opposed to uncertain natural gas price forecasts. This article suggests that had utilities and analysts in the US done so over the sample period from November 2000 to November 2003, they would have found gas-fired generation to be at least 0.3-0.6 cents/kWh more expensive (on a levelized cost basis) than otherwise thought. With some renewable resources, in particular wind

  12. Neural network based load and price forecasting and confidence interval estimation in deregulated power markets

    NASA Astrophysics Data System (ADS)

    Zhang, Li

    With the deregulation of the electric power market in New England, an independent system operator (ISO) has been separated from the New England Power Pool (NEPOOL). The ISO provides a regional spot market, with bids on various electricity-related products and services submitted by utilities and independent power producers. A utility can bid on the spot market and buy or sell electricity via bilateral transactions. Good estimation of market clearing prices (MCP) will help utilities and independent power producers determine bidding and transaction strategies with low risks, and this is crucial for utilities to compete in the deregulated environment. MCP prediction, however, is difficult since bidding strategies used by participants are complicated and MCP is a non-stationary process. The main objective of this research is to provide efficient short-term load and MCP forecasting and corresponding confidence interval estimation methodologies. In this research, the complexity of load and MCP with other factors is investigated, and neural networks are used to model the complex relationship between input and output. With improved learning algorithm and on-line update features for load forecasting, a neural network based load forecaster was developed, and has been in daily industry use since summer 1998 with good performance. MCP is volatile because of the complexity of market behaviors. In practice, neural network based MCP predictors usually have a cascaded structure, as several key input factors need to be estimated first. In this research, the uncertainties involved in a cascaded neural network structure for MCP prediction are analyzed, and prediction distribution under the Bayesian framework is developed. A fast algorithm to evaluate the confidence intervals by using the memoryless Quasi-Newton method is also developed. The traditional back-propagation algorithm for neural network learning needs to be improved since MCP is a non-stationary process. The extended Kalman

  13. Comparison of the economic impact of different wind power forecast systems for producers

    NASA Astrophysics Data System (ADS)

    Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

    2014-05-01

    Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a

  14. Comparison of Dst Forecast Models for Intense Geomagnetic Storms

    NASA Technical Reports Server (NTRS)

    Ji, Eun-Young; Moon, Y.-J.; Gopalswamy, N.; Lee, D.-H.

    2012-01-01

    We have compared six disturbance storm time (Dst) forecast models using 63 intense geomagnetic storms (Dst <=100 nT) that occurred from 1998 to 2006. For comparison, we estimated linear correlation coefficients and RMS errors between the observed Dst data and the predicted Dst during the geomagnetic storm period as well as the difference of the value of minimum Dst (Delta Dst(sub min)) and the difference in the absolute value of Dst minimum time (Delta t(sub Dst)) between the observed and the predicted. As a result, we found that the model by Temerin and Li gives the best prediction for all parameters when all 63 events are considered. The model gives the average values: the linear correlation coefficient of 0.94, the RMS error of 14.8 nT, the Delta Dst(sub min) of 7.7 nT, and the absolute value of Delta t(sub Dst) of 1.5 hour. For further comparison, we classified the storm events into two groups according to the magnitude of Dst. We found that the model of Temerin and Lee is better than the other models for the events having 100 <= Dst < 200 nT, and three recent models (the model of Wang et al., the model of Temerin and Li, and the model of Boynton et al.) are better than the other three models for the events having Dst <= 200 nT.

  15. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  16. A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

    SciTech Connect

    Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

    2013-12-18

    This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

  17. Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty

    EIA Publications

    2009-01-01

    It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy-related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the marketclearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities.

  18. Determining the best forecasting method to estimate unitary charges price indexes of PFI data in central region Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Ahmad Kamaruddin, Saadi Bin; Md Ghani, Nor Azura; Mohamed Ramli, Norazan

    2013-04-01

    The concept of Private Financial Initiative (PFI) has been implemented by many developed countries as an innovative way for the governments to improve future public service delivery and infrastructure procurement. However, the idea is just about to germinate in Malaysia and its success is still vague. The major phase that needs to be given main attention in this agenda is value for money whereby optimum efficiency and effectiveness of each expense is attained. Therefore, at the early stage of this study, estimating unitary charges or materials price indexes in each region in Malaysia was the key objective. This particular study aims to discover the best forecasting method to estimate unitary charges price indexes in construction industry by different regions in the central region of Peninsular Malaysia (Selangor, Federal Territory of Kuala Lumpur, Negeri Sembilan, and Melaka). The unitary charges indexes data used were from year 2002 to 2011 monthly data of different states in the central region Peninsular Malaysia, comprising price indexes of aggregate, sand, steel reinforcement, ready mix concrete, bricks and partition, roof material, floor and wall finishes, ceiling, plumbing materials, sanitary fittings, paint, glass, steel and metal sections, timber and plywood. At the end of the study, it was found that Backpropagation Neural Network with linear transfer function produced the most accurate and reliable results for estimating unitary charges price indexes in every states in central region Peninsular Malaysia based on the Root Mean Squared Errors, where the values for both estimation and evaluation sets were approximately zero and highly significant at p < 0.01. Therefore, artificial neural network is sufficient to forecast construction materials price indexes in Malaysia. The estimated price indexes of construction materials will contribute significantly to the value for money of PFI as well as towards Malaysian economical growth.

  19. Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

    PubMed Central

    Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

    2016-01-01

    Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

  20. Forecasting Price Increase Needs for Library Materials: The University of California Experience.

    ERIC Educational Resources Information Center

    Smith, Dennis

    1984-01-01

    Examines steps taken by the University of California to establish an adequate base library book budget and to measure price increase needs to maintain budgeted acquisition rates. The Voigt/Susskind Acquisitions Model, securing adequate funding for price increase needs, and the university's price increase justification are highlighted. (EJS)

  1. Improvements in Satellite-Derived Short-Term Insolation Forecasting: Statistical Comparisons, Challenges for Advection-Based Forecasts, and New Techniques

    NASA Astrophysics Data System (ADS)

    Rogers, M. A.; Miller, S. D.; Haynes, J. M.; Heidinger, A. K.; Haupt, S. E.; Sengupta, M.

    2014-12-01

    Using satellite observations from GOES-E and GOES-W platforms in concert with GFS-derived cloud-level winds and a standalone radiative transfer model, an advection-derived forecast for surface GHI over the continental United States is described. In particular, comparisons from the satellite-derived forecast are shown against several SURFRAD sites, with particular attention to developing meaningful error metrics to better demonstrate forecast skill and identify sources of error. Challenges in advection-based forecast techniques, such as forecasting near regions of non-wind-driven cloud systems such as coastal marine stratocumulus, are described, as are methods integrated into the forecast algorithm to identify and address these challenges. Improvements in the particular algorithm with respect to comparison against surface observations, integration of the forecast technique into blended forecast products such as those described by the 'Public-Private-Academic Partnership to Advance Solar Power Forecasting' project spearheaded by the National Center for Atmospheric Research, and other observations germane to satellite-derived solar forecasting are covered using nearly two years of operational forecasts as background.

  2. Comparison of very short-term load forecasting techniques

    SciTech Connect

    Liu, K.; Kwan, C.; Lewis, F.L.; Subbarayan, S.; Shoults, R.R.; Manry, M.T.; Naccarino, J.

    1996-05-01

    Three practical techniques--Fuzzy Logic (FL), Neural Networks (NN), and Auto-regressive model (AR)--for very short-term load forecasting have been proposed and discussed in this paper. Their performances are evaluated through a simulation study. The preliminary study shows that it is feasible to design a simple, satisfactory dynamic forecaster to predict the very short-term load trends on-line. FL and NN can be good candidates for this application.

  3. World oil market outlook: recent history and forecasts of world oil prices

    SciTech Connect

    Not Available

    1981-08-01

    Recent world oil price trends and pricing behavior by the Organization of Petroleum Exporting Countries (OPEC) are examined. An outlook for consumption, production and prices in the world oil market, both for the short-term horizon through 1982 and for the midterm period from 1985 through 1995 is presented. A historical review focuses on OPEC activity in the period from January 1980 to May 1981. Several sensitivity analyses and the impact of supply disruptions are used to determine projections. The appendix provides data on world crude oil prices for each of 23 countries for January, May, and June of 1980 and May of 1981. 22 tables, 9 figures.

  4. A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

    SciTech Connect

    Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

    2013-07-25

    This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

  5. Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

    NASA Astrophysics Data System (ADS)

    Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

    2009-01-01

    The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

  6. NewsMarket 2.0: Analysis of News for Stock Price Forecasting

    NASA Astrophysics Data System (ADS)

    Barazzetti, Alessandro; Mastronardi, Rosangela

    Most of the existing financial research tools use a stock's historical price and technical indicators to predict future price trends without taking into account the impact of web news. The recent explosion of demand for information on financial investment management is driving the search for alternative methods of quantitative data analysis.

  7. A comparison of GLAS SAT and NMC high resolution NOSAT forecasts from 19 and 11 February 1976

    NASA Technical Reports Server (NTRS)

    Atlas, R.

    1979-01-01

    A subjective comparison of the Goddard Laboratory for Atmospheric Sciences (GLAS) and the National Meteorological Center (NMC) high resolution model forecasts is presented. Two cases where NMC's operational model in 1976 had serious difficulties in forecasting for the United States were examined. For each of the cases, the GLAS model forecasts from initial conditions which included satellite sounding data were compared directly to the NMC higher resolution model forecasts, from initial conditions which excluded the satellite data. The comparison showed that the GLAS satellite forecasts significantly improved upon the current NMC operational model's predictions in both cases.

  8. Comparison of Conventional and ANN Models for River Flow Forecasting

    NASA Astrophysics Data System (ADS)

    Jain, A.; Ganti, R.

    2011-12-01

    Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

  9. Comparison and validation of global and regional ocean forecasting systems for the South China Sea

    NASA Astrophysics Data System (ADS)

    Zhu, Xueming; Wang, Hui; Liu, Guimei; Régnier, Charly; Kuang, Xiaodi; Wang, Dakui; Ren, Shihe; Jing, Zhiyou; Drévillon, Marie

    2016-07-01

    In this paper, the performance of two operational ocean forecasting systems, the global Mercator Océan (MO) Operational System, developed and maintained by Mercator Océan in France, and the regional South China Sea Operational Forecasting System (SCSOFS), by the National Marine Environmental Forecasting Center (NMEFC) in China, have been examined. Both systems can provide science-based nowcast/forecast products of temperature, salinity, water level, and ocean circulations. Comparison and validation of the ocean circulations, the structures of temperature and salinity, and some mesoscale activities, such as ocean fronts, typhoons, and mesoscale eddies, are conducted based on observed satellite and in situ data obtained in 2012 in the South China Sea. The results showed that MO performs better in simulating the ocean circulations and sea surface temperature (SST), and SCSOFS performs better in simulating the structures of temperature and salinity. For the mesoscale activities, the performance of SCSOFS is better than MO in simulating SST fronts and SST decrease during Typhoon Tembin compared with the previous studies and satellite data; but model results from both of SCSOFS and MO show some differences from satellite observations. In conclusion, some recommendations have been proposed for both forecast systems to improve their forecasting performance in the near future based on our comparison and validation.

  10. Regional price targets appropriate for advanced coal extraction. [Forecasting to 1985 and 2000; USA; Regional analysis

    SciTech Connect

    Terasawa, K.L.; Whipple, D.W.

    1980-12-01

    The object of the study is to provide a methodology for predicting coal prices in regional markets for the target time frames 1985 and 2000 that could subsequently be used to guide the development of an advanced coal extraction system. The model constructed for the study is a supply and demand model that focuses on underground mining, since the advanced technology is expected to be developed for these reserves by the target years. The supply side of the model is based on coal reserve data generated by Energy and Environmental Analysis, Inc. (EEA). Given this data and the cost of operating a mine (data from US Department of Energy and Bureau of Mines), the Minimum Acceptable Selling Price (MASP) is obtained. The MASP is defined as the smallest price that would induce the producer to bring the mine into production, and is sensitive to the current technology and to assumptions concerning miner productivity. Based on this information, market supply curves can then be generated. On the demand side of the model, demand by region is calculated based on an EEA methodology that emphasizes demand by electric utilities and demand by industry. The demand and supply curves are then used to obtain the price targets. This last step is accomplished by allocating the demands among the suppliers so that the combined cost of producing and transporting coal is minimized.

  11. Analysis of alternative-fuel price trajectories

    SciTech Connect

    Not Available

    1980-12-31

    Findings are presented from a study to (1) acquire, analyze, and report alternative published price projections including both oil- and coal-price trajectories, and to (2) apply the fixed-annuity formula to the updated primary source projections (Energy Information Administration; Data Resources, Inc.; and Wharton Econometric Forecasting Associates, Inc.) and to the newly acquired price projections. This report also encompasses: comparisons of key assumptions underlying the price projections, and a discussion of the applicability of the fixed-annuity formula as used in the alternative-cost calculation. Section II contains graphic presentations of all updated and newly acquired coal and oil price forecasts and the corresponding calculated annuity equivalents, tabulated presentations and discussions of each forecast and underlying assumptions, and a description of how each forecast price series was transformed into input for the present-value formulas. Section III presents the fixed-annuity formula employed and discusses its appropriateness for this application. Section IV discusses the applicability of the net present value approach for comparing alternate-fuel price trajectories. Appendix A contains a listing of contacts as potential sources of price forecasts. Appendix B contains the raw forecast data from each forecast source and the coal and oil price series derived from the raw data which were actually input into the cost calculation procedure. Appendix C contains a description and listing of the computer program developed to implement the cost calculation procedure. Finally, Appendix D contains tabulations and discussions of other alternative world crude price forecasts that were identified, but for which no corresponding coal-price projections were available. (MCW)

  12. The Second NWRA Flare-Forecasting Comparison Workshop: Methods Compared and Methodology

    NASA Astrophysics Data System (ADS)

    Leka, K. D.; Barnes, G.; the Flare Forecasting Comparison Group

    2013-07-01

    The Second NWRA Workshop to compare methods of solar flare forecasting was held 2-4 April 2013 in Boulder, CO. This is a follow-on to the First NWRA Workshop on Flare Forecasting Comparison, also known as the ``All-Clear Forecasting Workshop'', held in 2009 jointly with NASA/SRAG and NOAA/SWPC. For this most recent workshop, many researchers who are active in the field participated, and diverse methods were represented in terms of both the characterization of the Sun and the statistical approaches used to create a forecast. A standard dataset was created for this investigation, using data from the Solar Dynamics Observatory/ Helioseismic and Magnetic Imager (SDO/HMI) vector magnetic field HARP series. For each HARP on each day, 6 hours of data were used, allowing for nominal time-series analysis to be included in the forecasts. We present here a summary of the forecasting methods that participated and the standardized dataset that was used. Funding for the workshop and the data analysis was provided by NASA/Living with a Star contract NNH09CE72C and NASA/Guest Investigator contract NNH12CG10C.

  13. Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media.

    PubMed

    Goode, Brian J; Krishnan, Siddharth; Roan, Michael; Ramakrishnan, Naren

    2015-01-01

    Online social media activity can often be a precursor to disruptive events such as protests, strikes, and "occupy" movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the "Brazilian Spring" and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media.

  14. Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media.

    PubMed

    Goode, Brian J; Krishnan, Siddharth; Roan, Michael; Ramakrishnan, Naren

    2015-01-01

    Online social media activity can often be a precursor to disruptive events such as protests, strikes, and "occupy" movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the "Brazilian Spring" and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media. PMID:26441072

  15. Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media

    PubMed Central

    Roan, Michael; Ramakrishnan, Naren

    2015-01-01

    Online social media activity can often be a precursor to disruptive events such as protests, strikes, and “occupy” movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the “Brazilian Spring” and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media. PMID:26441072

  16. Study on Comparison of Bidding and Pricing Behavior Distinction between Estimate Methods

    NASA Astrophysics Data System (ADS)

    Morimoto, Emi; Namerikawa, Susumu

    The most characteristic trend on bidding and pricing behavior distinction in recent years is the increasing number of bidders just above the criteria for low-price bidding investigations. The contractor's markup is the difference between the bidding price and the execution price. Therefore, the contractor's markup is the difference between criteria for low-price bidding investigations price and the execution price in the public works bid in Japan. Virtually, bidder's strategies and behavior have been controlled by public engineer's budgets. Estimation and bid are inseparably linked in the Japanese public works procurement system. The trial of the unit price-type estimation method begins in 2004. On another front, accumulated estimation method is one of the general methods in public works. So, there are two types of standard estimation methods in Japan. In this study, we did a statistical analysis on the bid information of civil engineering works for the Ministry of Land, Infrastructure, and Transportation in 2008. It presents several issues that bidding and pricing behavior is related to an estimation method (several estimation methods) for public works bid in Japan. The two types of standard estimation methods produce different results that number of bidders (decide on bid-no bid strategy) and distribution of bid price (decide on mark-up strategy).The comparison on the distribution of bid prices showed that the percentage of the bid concentrated on the criteria for low-price bidding investigations have had a tendency to get higher in the large-sized public works by the unit price-type estimation method, comparing with the accumulated estimation method. On one hand, the number of bidders who bids for public works estimated unit-price tends to increase significantly Public works estimated unit-price is likely to have been one of the factors for the construction companies to decide if they participate in the biddings.

  17. Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

    NASA Astrophysics Data System (ADS)

    Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

    2015-11-01

    One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

  18. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  19. A comparison between a hydro-wind plant and wind speed forecasting using ARIMA models

    NASA Astrophysics Data System (ADS)

    Bayón, L.; Grau, J. M.; Ruiz, M. M.; Suárez, P. M.

    2014-10-01

    In this paper, we will present a comparison between two options for harnessing wind power. We will first analyze the behaviour of a wind farm that goes to the electricity market, having previously made a forecast of wind speed while accepting the deviation penalties that these may incur. Second, we will study the possibility of the wind farm not going to the market individually, but as part of a hydro-wind plant.

  20. A comparison of pay-as-bid and marginal pricing in electricity markets

    NASA Astrophysics Data System (ADS)

    Ren, Yongjun

    This thesis investigates the behaviour of electricity markets under marginal and pay-as-bid pricing. Marginal pricing is believed to yield the maximum social welfare and is currently implemented by most electricity markets. However, in view of recent electricity market failures, pay-as-bid has been extensively discussed as a possible alternative to marginal pricing. In this research, marginal and pay-as-bid pricing have been analyzed in electricity markets with both perfect and imperfect competition. The perfect competition case is studied under both exact and uncertain system marginal cost prediction. The comparison of the two pricing methods is conducted through two steps: (i) identify the best offer strategy of the generating companies (gencos); (ii) analyze the market performance under these optimum genco strategies. The analysis results together with numerical simulations show that pay-as-bid and marginal pricing are equivalent in a perfect market with exact system marginal cost prediction. In perfect markets with uncertain demand prediction, the two pricing methods are also equivalent but in an expected value sense. If we compare from the perspective of second order statistics, all market performance measures exhibit much lower values under pay-as-bid than under marginal pricing. The risk of deviating from the mean is therefore much higher under marginal pricing than under pay-as-bid. In an imperfect competition market with exact demand prediction, the research shows that pay-as-bid pricing yields lower consumer payments and lower genco profits. This research provides quantitative evidence that challenges some common claims about pay-as-bid pricing. One is that under pay-as-bid, participants would soon learn how to offer so as to obtain the same or higher profits than what they would have obtained under marginal pricing. This research however shows that, under pay-as-bid, participants can at best earn the same profit or expected profit as under marginal

  1. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

    2007-01-01

    options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

  2. A Comparison of Flare Forecasting Methods. I. Results from the “All-Clear” Workshop

    NASA Astrophysics Data System (ADS)

    Barnes, G.; Leka, K. D.; Schrijver, C. J.; Colak, T.; Qahwaji, R.; Ashamari, O. W.; Yuan, Y.; Zhang, J.; McAteer, R. T. J.; Bloomfield, D. S.; Higgins, P. A.; Gallagher, P. T.; Falconer, D. A.; Georgoulis, M. K.; Wheatland, M. S.; Balch, C.; Dunn, T.; Wagner, E. L.

    2016-10-01

    Solar flares produce radiation that can have an almost immediate effect on the near-Earth environment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has proliferated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, but have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from the Michelson Doppler Imager, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends toward a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.

  3. An ill-posed problem for the Black-Scholes equation for a profitable forecast of prices of stock options on real market data

    NASA Astrophysics Data System (ADS)

    Klibanov, Michael V.; Kuzhuget, Andrey V.; Golubnichiy, Kirill V.

    2016-01-01

    A new empirical mathematical model for the Black-Scholes equation is proposed to forecast option prices. This model includes new interval for the price of the underlying stock, new initial and new boundary conditions. Conventional notions of maturity time and strike prices are not used. The Black-Scholes equation is solved as a parabolic equation with the reversed time, which is an ill-posed problem. Thus, a regularization method is used to solve it. To verify the validity of our model, real market data for 368 randomly selected liquid options are used. A new trading strategy is proposed. Our results indicates that our method is profitable on those options. Furthermore, it is shown that the performance of two simple extrapolation-based techniques is much worse. We conjecture that our method might lead to significant profits of those financial insitutions which trade large amounts of options. We caution, however, that further studies are necessary to verify this conjecture.

  4. Evaluation and comparison of O3 forecasts of ALARO-CAMx and WRF-Chem

    NASA Astrophysics Data System (ADS)

    Flandorfer, Claudia; Hirtl, Marcus

    2015-04-01

    ZAMG runs two models for Air-Quality forecasts operationally: ALARO-CAMx and WRF-Chem. ALARO-CAMx is a combination of the meteorological model ALARO and the photochemical dispersion model CAMx and is operated at ZAMG by order of the regional governments since 2005. The emphasis of this modeling system is on predicting ozone peaks in the north-east Austrian flatlands. Two modeling domains are used with the highest resolution (5 km) in the alpine region. Various extensions with external data sources have been conducted in the past to improve the daily forecasts of the model, e.g. data assimilation of O3- and PM10 observations from the Austrian measurement network (with optimum interpolation technique); MACC-II boundary conditions; combination of high resolved emission inventories for Austria with TNO and EMEP data. The biogenic emissions are provided by the SMOKE model. The model runs 2 times per day for a period of 48 hours. The second model which is operational is the on-line coupled model WRF-Chem. Meteorology is simulated simultaneously with the emission, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. 2 domains are used for the simulations. The mother domain covers Europe with a resolution of 12 km. The inner domain includes the alpine region with a horizontal resolution of 4km. 45 model levels are used in the vertical. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. The evaluation of both models is conducted for summer 2014 with the main focus on the forecasts of ozone. The measurements of the Air-Quality stations are compared with the punctual forecasts at the sites of the stations and with the area forecasts for every province of Austria. Beside the evaluation a comparison of the forecasts of ALARO-CAMx and WRF-Chem is done. The summer 2014 was the coldest and the dullest in the last 9 years. Due to this only two exceedances of the information threshold were measured (June

  5. Performance comparison of meso-scale ensemble wave forecasting systems for Mediterranean sea states

    NASA Astrophysics Data System (ADS)

    Pezzutto, Paolo; Saulter, Andrew; Cavaleri, Luigi; Bunney, Christopher; Marcucci, Francesca; Torrisi, Lucio; Sebastianelli, Stefano

    2016-08-01

    This paper compares the performance of two wind and wave short range ensemble forecast systems for the Mediterranean Sea. In particular, it describes a six month verification experiment carried out by the U.K. Met Office and Italian Air Force Meteorological Service, based on their respective systems: the Met Office Global-Regional Ensemble Prediction System and the Nettuno Ensemble Prediction System. The latter is the ensemble version of the operational Nettuno forecast system. Attention is focused on the differences between the two implementations (e.g. grid resolution and initial ensemble members sampling) and their effects on the prediction skill. The cross-verification of the two ensemble systems shows that from a macroscopic point of view the differences cancel out, suggesting similar skill. More in-depth analysis indicates that the Nettuno wave forecast is better resolved but, on average, slightly less reliable than the Met Office product. Assessment of the added value of the ensemble techniques at short range in comparison with the deterministic forecast from Nettuno, reveals that adopting the ensemble approach has small, but substantive, advantages.

  6. Daily Peak Load Forecasting of Next Day using Weather Distribution and Comparison Value of Each Nearby Date Data

    NASA Astrophysics Data System (ADS)

    Ito, Shigenobu; Yukita, Kazuto; Goto, Yasuyuki; Ichiyanagi, Katsuhiro; Nakano, Hiroyuki

    By the development of industry, in recent years; dependence to electric energy is growing year by year. Therefore, reliable electric power supply is in need. However, to stock a huge amount of electric energy is very difficult. Also, there is a necessity to keep balance between the demand and supply, which changes hour after hour. Consequently, to supply the high quality and highly dependable electric power supply, economically, and with high efficiency, there is a need to forecast the movement of the electric power demand carefully in advance. And using that forecast as the source, supply and demand management plan should be made. Thus load forecasting is said to be an important job among demand investment of electric power companies. So far, forecasting method using Fuzzy logic, Neural Net Work, Regression model has been suggested for the development of forecasting accuracy. Those forecasting accuracy is in a high level. But to invest electric power in higher accuracy more economically, a new forecasting method with higher accuracy is needed. In this paper, to develop the forecasting accuracy of the former methods, the daily peak load forecasting method using the weather distribution of highest and lowest temperatures, and comparison value of each nearby date data is suggested.

  7. Contrail Cirrus Forecasts for the ML-CIRRUS Experiment and Some Comparison Results

    NASA Astrophysics Data System (ADS)

    Schumann, Ulrich; Graf, Kaspar; Bugliaro, Luca; Dörnbrack, Andreas; Giez, Andreas; Jurkat, Tina; Kaufmann, Stefan; Krämer, Martina; Minikin, Andreas; Schäfler, Andreas; Voigt, Christiane; Wirth, Martin; Zahn, Andreas; Ziereis, Helmut

    2015-04-01

    rerun with improved ECMWF-NWP data (at one-hour time resolution). The model results are included in the HALO mission data bank, and the results are available for comparison to in-situ data. The data are useful for identifying aircraft and other sources for measured air properties. The joint analysis of observations and model result has basically just started. Preliminary results from comparisons with lidar-measured extinction profiles, in-situ measured humidity, nitrogen oxides, and aerosol and ice particle concentrations, and with meteorological observations (wind, temperature etc.) illustrate the expected gain in insight. The contrail forecasts have been checked by comparison to available data including satellite data and HALO observations. During the campaign, it became obvious that predicted contrail cirrus cover compared qualitatively mostly well with what was found when HALO reached predicted cirrus regions. From the analysis of the measured data, some examples of significant correlation between model results and observations have been found. However, the quantitative agreement is not uniform. As expected, nature is far more variable than a model can predict. The observed optical properties of cirrus and contrails vary far more in time and space than predicted. Local values were often far higher or lower than mean values. A one-to-one correlation between local observations and model results is not to be expected. This inhomogeneity may have consequences for the climate impact of aviation induced cloud changes.

  8. Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

    NASA Astrophysics Data System (ADS)

    Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

    2012-04-01

    In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

  9. A comparison of the effects of initializing different thermosphere-ionosphere model fields on storm time plasma density forecasts

    NASA Astrophysics Data System (ADS)

    Chartier, Alex T.; Jackson, David R.; Mitchell, Cathryn N.

    2013-11-01

    assimilation has been used successfully for real-time ionospheric specification, but it has not yet proved advantageous for forecasting. The most challenging and important ionospheric events to forecast are storms. The work presented here examines the effectiveness of data assimilation in a storm situation, where the initial conditions are known and the model is considered to be correct but the external solar and geomagnetic drivers are poorly specified. The aim is to determine whether data assimilation could be used to improve storm time forecast accuracy. The results show that, in the case of the storm of Halloween 2003, changes made to the model's initial thermospheric conditions improve electron density forecasts by at least 10% for 18 h, while changes to ionospheric fields alone result in >10% forecast accuracy improvement for less than 4 h. Further examination shows that the neutral composition is especially important to the accuracy of ionospheric electron density forecasts. Updating the neutral composition gives almost all the benefits of updating the complete thermospheric state. A comparison with real, globally distributed observations of vertical total electron content confirms that updating the thermospheric composition can improve forecast accuracy.

  10. RAMS-forecasts comparison of typical summer atmospheric conditions over the Western Mediterranean coast

    NASA Astrophysics Data System (ADS)

    Gómez, I.; Caselles, V.; Estrela, M. J.; Niclòs, R.

    2014-08-01

    The Regional Atmospheric Modeling System (RAMS) has been used in order to perform a high-resolution numerical simulation of two meteorological events related to the most common atmospheric environments during the summer over the Western Mediterranean coast: mesoscale circulations and western synoptic advections. In this regard, we take advantage of the operational RAMS configuration running within the real-time forecasting system environment already implemented over this Mediterranean area, precisely in the Valencia Region and nearby areas. The attention of this paper is especially focused on identifying the main features of both events and the ability of the model in resolving the associated characteristics as well as in performing a comprehensive evaluation of the model by means of diverse meteorological observations available within the selected periods over the area of study. Additionally, as this paper is centred in RAMS-based forecasts, two simulations are operated applying the most two recent versions of the RAMS model implemented in the above-mentioned system: RAMS 4.4 and RAMS 6.0. Therefore, a comparison among both versions of the model has been performed as well. Finally, it is our intention to contrast the RAMS forecasts for two completely different atmospheric conditions common with the area of study in the summer. A main difference between the simulation of both meteorological situations has been found in the humidity. In this sense, whilst the model underestimates this magnitude considering the mesoscale event, especially at night time, the model reproduces the daily humidity properly under the western synoptic advection.

  11. Accounting for fuel price risk when comparing renewable togas-fired generation: the role of forward natural gas prices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2004-07-17

    Unlike natural gas-fired generation, renewable generation (e.g., from wind, solar, and geothermal power) is largely immune to fuel price risk. If ratepayers are rational and value long-term price stability, then--contrary to common practice--any comparison of the levelized cost of renewable to gas-fired generation should be based on a hedged gas price input, rather than an uncertain gas price forecast. This paper compares natural gas prices that can be locked in through futures, swaps, and physical supply contracts to contemporaneous long-term forecasts of spot gas prices. We find that from 2000-2003, forward gas prices for terms of 2-10 years have been considerably higher than most contemporaneous long-term gas price forecasts. This difference is striking, and implies that comparisons between renewable and gas-fired generation based on these forecasts over this period have arguably yielded results that are biased in favor of gas-fired generation.

  12. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations

    SciTech Connect

    Hnilo, J.

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  13. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect

    Hnilo, J J

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  14. A comparison of model short-range forecasts and the ARM Microbase data

    SciTech Connect

    Hnilo, J J

    2006-09-22

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  15. Study on impact of energy price comparison on energy saving benefits of heat pump in North China

    NASA Astrophysics Data System (ADS)

    Dong, X.; Tian, Q.; Zhang, Y. G.; Bai, H. F.

    2016-08-01

    As to the heat pump technology applying in the HVAC engineering, the relationship between energy saving rate (ESR) and electricity cost saving rate (ECSR) of heat pump should be a positive correlation in theory. But in the actual energy price system, due to the fluctuating energy price comparison, the relationship between them is of less coordination. Moreover, despite the high ESR, the economic benefit of ECSR is lost. In this paper, via the case analysis under the condition of average technical and economic parameters in North China, the critical point rate of economic benefit of ECSR in energy price comparison among prices of residential electricity, steam-coal, and residential natural gas is found, which is about 2:3:8. Also, a viewpoint as well as method is suggested to promote the wide usage of heat pump, balance energy supply structure, save energy consumption, and reduce emissions by optimizing the energy price comparison, which is feasible and desirable to raise the price comparison between residential electricity and natural gas, and reduce the price comparison between residential electricity and steam-coal in a certain extent.

  16. Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting

    NASA Astrophysics Data System (ADS)

    Lagomarsino, D.; Segoni, S.; Rosi, A.; Rossi, G.; Battistini, A.; Catani, F.; Casagli, N.

    2015-10-01

    This work proposes a methodology to compare the forecasting effectiveness of different rainfall threshold models for landslide forecasting. We tested our methodology with two state-of-the-art models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds. The first model identifies rainfall intensity-duration thresholds by means of a software program called MaCumBA (MAssive CUMulative Brisk Analyzer) (Segoni et al., 2014a) that analyzes rain gauge records, extracts intensity (I) and duration (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram and identifies the thresholds that define the lower bounds of the I-D values. A back analysis using data from past events is used to identify the threshold conditions associated with the least number of false alarms. The second model (SIGMA) (Sistema Integrato Gestione Monitoraggio Allerta) (Martelloni et al., 2012) is based on the hypothesis that anomalous or extreme values of accumulated rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations. To perform a quantitative and objective comparison, these two models were applied in two different areas, each time performing a site-specific calibration against available rainfall and landslide data. For each application, a validation procedure was carried out on an independent data set and a confusion matrix was built. The results of the confusion matrixes were combined to define a series of indexes commonly used to evaluate model performances in natural hazard assessment. The comparison of these indexes allowed to identify the most effective model in each case study and, consequently, which threshold should be used in the

  17. Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

    NASA Astrophysics Data System (ADS)

    Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

    2014-05-01

    This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

  18. A Comparison of Some Difference Schemes for a Parabolic Problem of Zero-Coupon Bond Pricing

    NASA Astrophysics Data System (ADS)

    Chernogorova, Tatiana; Vulkov, Lubin

    2009-11-01

    This paper describes a comparison of some numerical methods for solving a convection-diffusion equation subjected by dynamical boundary conditions which arises in the zero-coupon bond pricing. The one-dimensional convection-diffusion equation is solved by using difference schemes with weights including standard difference schemes as the monotone Samarskii's scheme, FTCS and Crank-Nicolson methods. The schemes are free of spurious oscillations and satisfy the positivity and maximum principle as demanded for the financial and diffusive solution. Numerical results are compared with analytical solutions.

  19. Who Is the Big Spender? Price Index Effects in Comparisons of Educational Expenditures between Countries and Over Time

    ERIC Educational Resources Information Center

    Arneberg, Marie; Bowitz, Einar

    2006-01-01

    International comparisons of data on expenditure on education use purchasing power parities for currency conversion and adjustment for price differences between countries to allow for volume comparisons. The resulting indicators are commonly interpreted as differences between countries in input volumes to the education sector-teachers, materials,…

  20. Comparison of Wind energy production forecasts, in terms of errors and economic losses

    NASA Astrophysics Data System (ADS)

    Mestre, O.; Texier, O.; Girard, N.; Usaola, J.; Bantegnie, P.

    2009-04-01

    We compare 6 forecasts productions models on two windfarms located in France. The evaluation is made in terms of root mean square errors. The power production forecasts are the products of both physical and statistical models and cover a period of 6 months. We show that the economic performances of those models can be improved using econometric approaches, where we to minimize the cost induced by the forecast error instead of minimizing the forecast error itself. This technique relies on state of the art non-parametric estimators of conditional probability distribution functions (cpdf) of energy production at a wind farm, given the wind speed forecasts of a deterministic meteorological model. In this case, no assumption is made about the shape of the underlying laws. The economical benefits of ensemble versus deterministic wind speed forecasts are also assessed.

  1. A comparison of cloud microphysical quantities with forecasts from cloud prediction models

    SciTech Connect

    Dunn, M.; Jensen, M.; Hogan, R.; O’Connor, E.; Huang, D.

    2010-03-15

    Numerical weather prediction models (ECMWF, NCEP) are evaluated using ARM observational data collected at the Southern Great Plains (SGP) site. Cloud forecasts generated by the models are compared with cloud microphysical quantities, retrieved using a variety of parameterizations. Information gained from this comparison will be utilized during the FASTER project, as models are evaluated for their ability to reproduce fast physical processes detected in the observations. Here the model performance is quantified against the observations through a statistical analysis. Observations from remote sensing instruments (radar, lidar, radiometer and radiosonde) are used to derive the cloud microphysical quantities: ice water content, liquid water content, ice effective radius and liquid effective radius. Unfortunately, discrepancies in the derived quantities arise when different retrieval schemes are applied to the observations. The uncertainty inherent in retrieving the microphysical quantities using various retrievals is estimated from the range of output microphysical values. ARM microphysical retrieval schemes (Microbase, Mace) are examined along with the CloudNet retrieval processing of data from the ARM sites for this purpose. Through the interfacing of CloudNet and “ARM” processing schemes an ARMNET product is produced and employed as accepted observations in the assessment of cloud model predictions.

  2. A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

    ERIC Educational Resources Information Center

    Baker, Bruce D.; Richards, Craig E.

    1999-01-01

    Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

  3. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  4. Comparison of the Effectiveness of Six Models in Forecasting Student Demand on Academic Departments. Final Report.

    ERIC Educational Resources Information Center

    Blake, R. John; Robertson, Leon B.

    An accurate forecast of the student demand by level on the academic departments of an institution is vital for budget and financial planning decisions, for faculty workload scheduling, and for physical facility planning. Many methods have been used to forecast this demand, ranging from "seat of your pants" guessing to highly complex computer…

  5. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... comparisons. 233.2 Section 233.2 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES... charged by others for the same merchandise in the advertiser's trade area (the area in which he does... advertiser or by others in the advertiser's trade area for other merchandise of like grade and...

  6. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... comparisons. 233.2 Section 233.2 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES... charged by others for the same merchandise in the advertiser's trade area (the area in which he does... advertiser or by others in the advertiser's trade area for other merchandise of like grade and...

  7. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... comparisons. 233.2 Section 233.2 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES... charged by others for the same merchandise in the advertiser's trade area (the area in which he does... advertiser or by others in the advertiser's trade area for other merchandise of like grade and...

  8. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... comparisons. 233.2 Section 233.2 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES... charged by others for the same merchandise in the advertiser's trade area (the area in which he does... advertiser or by others in the advertiser's trade area for other merchandise of like grade and...

  9. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... comparisons. 233.2 Section 233.2 Commercial Practices FEDERAL TRADE COMMISSION GUIDES AND TRADE PRACTICE RULES... charged by others for the same merchandise in the advertiser's trade area (the area in which he does... advertiser or by others in the advertiser's trade area for other merchandise of like grade and...

  10. Comparison of outburst danger criteria of coal seams for acoustic spectral and instrumental forecast methods

    NASA Astrophysics Data System (ADS)

    Shadrin, A. V.; Bireva, Yu A.

    2016-10-01

    Outburst danger criteria for the two methods of current coal seam outburst forecast are considered: instrumental - by the initial outgassing rate and chippings outlet during test boreholes drilling, and geo-physical - by relation of high frequency and low frequency components of noise caused by cutting tool of operating equipment probing the face area taking into consideration the outburst criteria correction based on methane concentration at the face area and the coal strength. The conclusion is made on “adjustment” possibility of acoustic spectral forecast method criterion amended by control of methane concentration at the coal face and the coal strength taken from the instrumental method forecast results.

  11. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast. Technical Appendix: Volume 1.

    SciTech Connect

    1994-02-01

    This publication documents the load forecast scenarios and assumptions used to prepare BPA's Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  12. Moving into the Light: The AEOS Telescope in the Daytime Operating Environment

    NASA Astrophysics Data System (ADS)

    Mayo, J.

    Abstract for Coming into the Light: The AEOS Telescope in the Daytime Operating Environment” Interest in daylight operation for the AEOS 3.67-m Telescope first surfaced during the preparation of the AEOS specification documentation in 1991. The author and Lt Rich Elder prepared, edited and combined requirements inputs from AFRL technical staff to create the final RFP document. In this released specification, AEOS daylight performance was limited to best effort, although provisions for adding secondary mirror sky light baffling were to be provided. In 1993, during the AEOS construction phase, AFRL requested that the author prepare a report on special considerations for operating AEOS in the solar illuminated daytime environment. This report was published and briefed to AFRL and Space Command at that time. Interest in this topic at AMOS was rekindled in 2007 by Dr Joe Janni and Lt Col Scott Hunt. The author updated his 1993 report and in June 2007 presented AEOS 1993 Daylight Operation Study Revisited” at AMOS. Subsequently, Dr Stacie Williams spearheaded additional work in this critical technical area. Recent efforts at Tau Technologies LLC have focused on external AEOS telescope baffling and shielding options assessment, solar irradiation effects on optical components, especially the primary mirror, and on modeling the solar illumination on the entire telescope during daylight operation. Solid Works and Illustrator simulation models have been developed and exercised.

  13. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

    2007-01-01

    Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation at the Shuttle Landing Facility is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAF5), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. This study specifically addresses the skill of different model configurations in forecasting warm season convective initiation. Numerous factors influence the development of convection over the Florida peninsula. These factors include sea breezes, river and lake breezes, the prevailing low-level flow, and convergent flow due to convex coastlines that enhance the sea breeze. The interaction of these processes produces the warm season convective patterns seen over the Florida peninsula. However, warm season convection remains one of the most poorly forecast meteorological parameters. To determine which

  14. Comparison of Dst forecast models and their dependence on interplanetary structure

    NASA Astrophysics Data System (ADS)

    Ji, E.; Moon, Y.; Lee, D.

    2010-12-01

    We have investigated 63 intense geomagnetic storms (Dst ≤ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O’Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (△peak), and the difference of Dst minimum time (△peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of △peak of 12.54 nT, and a MAD of △peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of △peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of △peak of SH structure of Temerin and Li model are very lower than those of other models.

  15. A comparison of continental actual evaporation estimates for Africa to improve hydrological drought forecasting

    NASA Astrophysics Data System (ADS)

    Trambauer, Patricia; Maskey, Shreedhar; Werner, Micha

    2013-04-01

    Evaporation is a key process in the development of hydrological and agricultural droughts. Although distributed drought indicators are often calculated using estimates of evaporation or soil moisture, the estimation of continental evaporation fluxes is complex and typically relies on continental-scale hydrological or land-surface models. However, it appears that most global or continental-scale hydrological models underestimate evaporative fluxes in some regions of Africa, and as a result overestimate stream flows. On the other hand, other studies suggest that land-surface models may overestimate evaporative fluxes. In this study, we computed actual evaporation for the African continent using a continental version of the global hydrological model PCR-GLOBWB, which is based on a water balance approach. Results are compared with other independently computed evaporation products; the evaporation results from the HTESSEL model and ERA-Interim (both based on the energy balance approach), both the MOD16 evaporation product (largely derived from MODIS remote sensing images), and the GLEAM product (derived from satellite observations). Three alternative versions of the PCR-GLOBWB hydrological model were also considered. In the first the model structure was amended by introducing an irrigation scheme, while in the second and third forcing data (precipitation and potential evaporation) were modified to assess the impact that the choice of forcing has on the actual evaporation fluxes simulated by the model. This resulted in eight products of actual evaporation, and derived drought indices were compared in distinct regions of the African continent spanning different climatic regimes. Annual totals, spatial patterns and seasonality were studied and compared through visual inspection and using statistical methods. The comparison indicated that the representation of irrigation areas has an insignificant contribution to the actual evaporation at a continental scale with a 0.5

  16. Price controls and international petroleum product prices

    SciTech Connect

    Deacon, R.T.; Mead, W.J.; Agarwal, V.B.

    1980-02-01

    The effects of Federal refined-product price controls upon the price of motor gasoline in the United States through 1977 are examined. A comparison of domestic and foreign gasoline prices is made, based on the prices of products actually moving in international trade. There is also an effort to ascribe US/foreign market price differentials to identifiable cost factors. Primary emphasis is on price comparisons at the wholesale level, although some retail comparisons are presented. The study also examines the extent to which product price controls are binding, and attempts to estimate what the price of motor gasoline would have been in the absence of controls. The time period under consideration is from 1969 through 1977, with primary focus on price relationships in 1970-1971 (just before US controls) and 1976-1977. The foreign-domestic comparisons are made with respect to four major US cities, namely, Boston, New York, New Orleans, and Los Angeles. 20 figures, 14 tables.

  17. Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility

    NASA Astrophysics Data System (ADS)

    Ma, Feng; Wei, Yu; Huang, Dengshi; Chen, Yixiang

    2014-07-01

    In this paper, by taking the 5-min high frequency data of the Shanghai Composite Index as example, we compare the forecasting performance of HAR-RV and Multifractal volatility, Realized volatility, Realized Bipower Variation and their corresponding short memory model with rolling windows forecasting method and the Model Confidence Set which is proved superior to SPA test. The empirical results show that, for six loss functions, HAR-RV outperforms other models. Moreover, to make the conclusions more precise and robust, we use the MCS test to compare the performance of their logarithms form models, and find that the HAR-log(RV) has a better performance in predicting future volatility. Furthermore, by comparing the two models of HAR-RV and HAR-log(RV), we conclude that, in terms of performance forecasting, the HAR-log(RV) model is the best model among models we have discussed in this paper.

  18. Regional Comparisons, Spatial Aggregation, and Asymmetry of Price Pass-Through

    EIA Publications

    2005-01-01

    Spot to retail price pass-through behavior of the U.S. gasoline market was investigated at the national and regional levels, using weekly wholesale and retail motor gasoline prices from January 2000 to the present.

  19. A Comparison of Pricing Strategies for Bibliographical Databases on CDROM and Equivalent Printed Products.

    ERIC Educational Resources Information Center

    Rowley, Jennifer; Butcher, David

    1994-01-01

    Considers comparative prices for bibliographic data on CD-ROM and in print. Topics addressed include differences in the nature of bibliographic data in the two media, the relative complexities of pricing structure, varying policies on network pricing, and standardization of the licensing arrangement. (KRN)

  20. Comparison of Short-term and Long-term Earthquake Forecast Models for Southern California

    NASA Astrophysics Data System (ADS)

    Helmstetter, A.; Kagan, Y. Y.; Jackson, D. D.

    2004-12-01

    Many earthquakes are triggered in part by preceding events. Aftershocks are the most obvious examples, but many large earthquakes are preceded by smaller ones. The large fluctuations of seismicity rate due to earthquake interactions thus provide a way to improve earthquake forecasting significantly. We have developed a model to estimate daily earthquake probabilities in Southern California, using the Epidemic Type Earthquake Sequence model [Kagan and Knopoff, 1987; Ogata, 1988]. The forecasted seismicity rate is the sum of a constant external loading and of the aftershocks of all past earthquakes. The background rate is estimated by smoothing past seismicity. Each earthquake triggers aftershocks with a rate that increases exponentially with its magnitude and which decreases with time following Omori's law. We use an isotropic kernel to model the spatial distribution of aftershocks for small (M≤5.5) mainshocks, and a smoothing of the location of early aftershocks for larger mainshocks. The model also assumes that all earthquake magnitudes follow the Gutenberg-Richter law with a unifom b-value. We use a maximum likelihood method to estimate the model parameters and tests the short-term and long-term forecasts. A retrospective test using a daily update of the forecasts between 1985/1/1 and 2004/3/10 shows that the short-term model decreases the uncertainty of an earthquake occurrence by a factor of about 10.

  1. A comparison of the domestic satellite communications forecast to the year 2000

    NASA Technical Reports Server (NTRS)

    Poley, W. A.; Lekan, J. F.; Salzman, J. A.; Stevenson, S. M.

    1983-01-01

    The methodologies and results of three NASA-sponsored market demand assessment studies are presented and compared. Forecasts of future satellite addressable traffic (both trunking and customer premises services) were developed for the three main service categories of voice, data and video and subcategories thereof for the benchmark years of 1980, 1990 and 2000. The contractor results are presented on a service by service basis in two formats: equivalent 36 MHz transponders and basic transmission units (voice: half-voice circuits, data: megabits per second and video: video channels). It is shown that while considerable differences exist at the service category level, the overall forecasts by the two contractors are quite similar. ITT estimates the total potential satellite market to be 3594 transponders in the year 2000 with data service comprising 54 percent of this total. The WU outlook for the same time period is 2779 transponders with voice services accounting for 66 percent of the total.

  2. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.

    2007-01-01

    This report describes the work done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting warm season convection over East-Central Florida. The Weather Research and Forecasting Environmental Modeling System (WRF EMS) software allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Besides model core and initialization options, the WRF model can be run with one- or two-way nesting. Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. This project assessed three different model intializations available to determine which configuration best predicts warm season convective initiation in East-Central Florida. The project also examined the use of one- and two-way nesting in predicting warm season convection.

  3. Comparison of cross-validation and bootstrap aggregating for building a seasonal streamflow forecast model

    NASA Astrophysics Data System (ADS)

    Schick, Simon; Rössler, Ole; Weingartner, Rolf

    2016-10-01

    Based on a hindcast experiment for the period 1982-2013 in 66 sub-catchments of the Swiss Rhine, the present study compares two approaches of building a regression model for seasonal streamflow forecasting. The first approach selects a single "best guess" model, which is tested by leave-one-out cross-validation. The second approach implements the idea of bootstrap aggregating, where bootstrap replicates are employed to select several models, and out-of-bag predictions provide model testing. The target value is mean streamflow for durations of 30, 60 and 90 days, starting with the 1st and 16th day of every month. Compared to the best guess model, bootstrap aggregating reduces the mean squared error of the streamflow forecast by seven percent on average. Thus, if resampling is anyway part of the model building procedure, bootstrap aggregating seems to be a useful strategy in statistical seasonal streamflow forecasting. Since the improved accuracy comes at the cost of a less interpretable model, the approach might be best suited for pure prediction tasks, e.g. as in operational applications.

  4. A quantitative comparison of precipitation forecasts between the storm-scale numerical weather prediction model and auto-nowcast system in Jiangsu, China

    NASA Astrophysics Data System (ADS)

    Wang, Gaili; Yang, Ji; Wang, Dan; Liu, Liping

    2016-11-01

    Extrapolation techniques and storm-scale Numerical Weather Prediction (NWP) models are two primary approaches for short-term precipitation forecasts. The primary objective of this study is to verify precipitation forecasts and compare the performances of two nowcasting schemes: a Beijing Auto-Nowcast system (BJ-ANC) based on extrapolation techniques and a storm-scale NWP model called the Advanced Regional Prediction System (ARPS). The verification and comparison takes into account six heavy precipitation events that occurred in the summer of 2014 and 2015 in Jiangsu, China. The forecast performances of the two schemes were evaluated for the next 6 h at 1-h intervals using gridpoint-based measures of critical success index, bias, index of agreement, root mean square error, and using an object-based verification method called Structure-Amplitude-Location (SAL) score. Regarding gridpoint-based measures, BJ-ANC outperforms ARPS at first, but then the forecast accuracy decreases rapidly with lead time and performs worse than ARPS after 4-5 h of the initial forecast. Regarding the object-based verification method, most forecasts produced by BJ-ANC focus on the center of the diagram at the 1-h lead time and indicate high-quality forecasts. As the lead time increases, BJ-ANC overestimates precipitation amount and produces widespread precipitation, especially at a 6-h lead time. The ARPS model overestimates precipitation at all lead times, particularly at first.

  5. Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and model forecasts

    NASA Astrophysics Data System (ADS)

    Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; McQueen, J.; Tang, Y.; Langel, T.; McKeen, S.; Williams, E. J.; Brown, S. S.

    2015-05-01

    Air quality forecast models typically predict large summertime ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin and as predicted by the Community Multiscale Air Quality (CMAQ) model. From 2008 to 2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008 to 2010 measurements of ambient ozone were conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI, and Muskegon, MI, up to six times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha, with little dependence on position of the ferry or temperature and with greatest differences during evening and night. Concurrent 1-48 h forecasts from the CMAQ model in the upper Midwestern region surrounding Lake Michigan were compared to ferry ozone measurements, shoreline DOAS measurements and Environmental Protection Agency (EPA) station measurements. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. Trends in the bias with respect to location and time of day were explored showing non-uniformity in model bias over the lake. Model ozone bias was consistently high over the lake in comparison to land-based measurements, with highest biases for 25-48 h after initialization.

  6. The evolving price of household LED lamps: Recent trends and historical comparisons for the US market

    SciTech Connect

    Gerke, Brian F.; Ngo, Allison T.; Alstone, Andrea L.; Fisseha, Kibret S.

    2014-10-14

    In recent years, household LED light bulbs (LED A lamps) have undergone a dramatic price decline. Since late 2011, we have been collecting data, on a weekly basis, for retail offerings of LED A lamps on the Internet. The resulting data set allows us to track the recent price decline in detail. LED A lamp prices declined roughly exponentially with time in 2011-2014, with decline rates of 28percent to 44percent per year depending on lumen output, and with higher-lumen lamps exhibiting more rapid price declines. By combining the Internet price data with publicly available lamp shipments indices for the US market, it is also possible to correlate LED A lamp prices against cumulative production, yielding an experience curve for LED A lamps. In 2012-2013, LED A lamp prices declined by 20-25percent for each doubling in cumulative shipments. Similar analysis of historical data for other lighting technologies reveals that LED prices have fallen significantly more rapidly with cumulative production than did their technological predecessors, which exhibited a historical decline of 14-15percent per doubling of production.

  7. Annual energy outlook 1995, with projections to 2010

    SciTech Connect

    1995-01-01

    The Annual Energy Outlook 1995 (AEO95) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projections and analyses of energy supply, demand, and prices through 2010, based on results from the National Energy Modeling System (NEMS). Quarterly forecasts of energy supply and demand for 1995 and 1996 are published in the Short-Term Energy Outlook (February 1995). Forecast tables for the five cases examined in the AEO95 are provided in Appendixes A through C. Appendix A gives historical data and forecasts for selected years from 1992 through 2010 for the reference case. Appendix B presents two additional cases, which assume higher and lower economic growth than the reference case. Appendix C presents two cases that assume higher and lower world oil prices. Appendix D presents a summary of the forecasts in units of oil equivalence. Appendix E presents a summary of household energy expenditures. Appendix F provides detailed comparisons of the AEO95 forecasts with those of other organizations. Appendix G briefly describes NEMS and the major AEO95 forecast assumptions. Appendix H presents a stand-alone high electricity demand case. Appendix 1 provides a table of energy conversion factors and a table of metric conversion factors. 89 figs., 23 tabs.

  8. Forecasting forecast skill

    NASA Technical Reports Server (NTRS)

    Kalnay, Eugenia; Dalcher, Amnon

    1987-01-01

    It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

  9. Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

    NASA Astrophysics Data System (ADS)

    Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

    2014-12-01

    Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of

  10. A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric

    SciTech Connect

    Hnilo, J.

    2006-09-19

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the “Microbase” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  11. Numerical ragweed pollen forecasts using different source maps: a comparison for France

    NASA Astrophysics Data System (ADS)

    Zink, Katrin; Kaufmann, Pirmin; Petitpierre, Blaise; Broennimann, Olivier; Guisan, Antoine; Gentilini, Eros; Rotach, Mathias W.

    2016-06-01

    One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably.

  12. Probabilistic streamflow forecasting for hydroelectricity production: A comparison of two non-parametric system identification algorithms

    NASA Astrophysics Data System (ADS)

    Pande, Saket; Sharma, Ashish

    2014-05-01

    This study is motivated by the need to robustly specify, identify, and forecast runoff generation processes for hydroelectricity production. It atleast requires the identification of significant predictors of runoff generation and the influence of each such significant predictor on runoff response. To this end, we compare two non-parametric algorithms of predictor subset selection. One is based on information theory that assesses predictor significance (and hence selection) based on Partial Information (PI) rationale of Sharma and Mehrotra (2014). The other algorithm is based on a frequentist approach that uses bounds on probability of error concept of Pande (2005), assesses all possible predictor subsets on-the-go and converges to a predictor subset in an computationally efficient manner. Both the algorithms approximate the underlying system by locally constant functions and select predictor subsets corresponding to these functions. The performance of the two algorithms is compared on a set of synthetic case studies as well as a real world case study of inflow forecasting. References: Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 49, doi:10.1002/2013WR013845. Pande, S. (2005), Generalized local learning in water resource management, PhD dissertation, Utah State University, UT-USA, 148p.

  13. 76 FR 18425 - Energy Conservation Program: Data Collection and Comparison With Forecasted Unit Sales of Five...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-04

    ... incandescent lamps, 2,601-3,300 lumen general service incandescent lamps, and shatter-resistant lamps), which.... Shatter-Resistant Lamps III. Comparison Methodology IV. Comparison Results A. Rough Service Lamps B... Lamps E. Shatter-Resistant Lamps V. Conclusion I. Background The Energy Independence and Security Act...

  14. 77 FR 16183 - Energy Conservation Program: Data Collection and Comparison With Forecasted Unit Sales of Five...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-20

    ... glass envelope breaks. Shatter-resistant lamps incorporate a coating compliant with industry standard... incandescent lamps, 2,601-3,300 lumen general service incandescent lamps, and shatter-resistant lamps), which... Service Incandescent Lamps E. Shatter-Resistant Lamps III. Comparison Methodology IV. Comparison Results...

  15. A price comparison of recently launched proprietary pharmaceuticals in the UK and the US

    PubMed Central

    Jørgensen, Jesper; Kefalas, Panos

    2016-01-01

    Objective To explore the relationship between prices charged by manufacturers of proprietary pharmaceuticals in the US and in the UK in recent years (2013–2016), expressed as a multiplier, and to detail to what extent this relationship differs for high-cost therapies used in smaller patient populations, as compared to lower-cost drugs. Methodology Therapies assessed by the Scottish Medicines Consortium (SMC) in the UK between 1 January 2013 and 1 June 2016 were identified; only in-patent therapies were included in the analysis (to avoid the impact of price erosion post patent expiry); results were grouped according to annual cost per patient (whether considered high-cost, i.e., >£2,500 per patient per year, or not) and the size of the UK target population [whether considered orphan (<32,000 patients per year), ultra-orphan (<1,000 patients per year), or not]. Publicly listed prices were obtained in the US and UK and were adjusted where necessary to estimate the prices charged by manufacturers in the respective countries. The difference in price (per unit of the same strength and formulation) was calculated as a multiplier between the US and UK prices for each of the therapies identified. Results Based on the methodological approach described, 88 therapies were identified and included in the analysis. The multiplier between the US and UK prices was 3.64 for therapies with an estimated annual cost <£2,500; this was reduced to 1.90 for higher-cost therapies. A downward trend was also evident in the subgroup analysis of the higher-cost therapies; as the estimated target patient populations reduced from >32,000 down to <1,000, the US/UK price multipliers reduced from 2.13 for the former to 1.48 for the latter. Conclusion Although pharmaceutical prices have been found to be on average substantially higher in the US compared to the UK, our findings suggest that this price discrepancy is smaller for higher-cost therapies targeting small patient populations

  16. A price comparison of recently launched proprietary pharmaceuticals in the UK and the US

    PubMed Central

    Jørgensen, Jesper; Kefalas, Panos

    2016-01-01

    Objective To explore the relationship between prices charged by manufacturers of proprietary pharmaceuticals in the US and in the UK in recent years (2013–2016), expressed as a multiplier, and to detail to what extent this relationship differs for high-cost therapies used in smaller patient populations, as compared to lower-cost drugs. Methodology Therapies assessed by the Scottish Medicines Consortium (SMC) in the UK between 1 January 2013 and 1 June 2016 were identified; only in-patent therapies were included in the analysis (to avoid the impact of price erosion post patent expiry); results were grouped according to annual cost per patient (whether considered high-cost, i.e., >£2,500 per patient per year, or not) and the size of the UK target population [whether considered orphan (<32,000 patients per year), ultra-orphan (<1,000 patients per year), or not]. Publicly listed prices were obtained in the US and UK and were adjusted where necessary to estimate the prices charged by manufacturers in the respective countries. The difference in price (per unit of the same strength and formulation) was calculated as a multiplier between the US and UK prices for each of the therapies identified. Results Based on the methodological approach described, 88 therapies were identified and included in the analysis. The multiplier between the US and UK prices was 3.64 for therapies with an estimated annual cost <£2,500; this was reduced to 1.90 for higher-cost therapies. A downward trend was also evident in the subgroup analysis of the higher-cost therapies; as the estimated target patient populations reduced from >32,000 down to <1,000, the US/UK price multipliers reduced from 2.13 for the former to 1.48 for the latter. Conclusion Although pharmaceutical prices have been found to be on average substantially higher in the US compared to the UK, our findings suggest that this price discrepancy is smaller for higher-cost therapies targeting small patient populations

  17. Empirical comparison of various methods for training feed-Forward neural networks for salinity forecasting

    NASA Astrophysics Data System (ADS)

    Maier, Holger R.; Dandy, Graeme C.

    1999-08-01

    Feed-forward artificial neural networks (ANNs) are being used increasingly to model water resources variables. In this technical note, six methods for optimizing the connection weights of feedforward ANNs are investigated in terms of generalization ability, parsimony, and training speed. These include the generalized delta (GD) rule, the normalized cumulative delta (NCD) rule, the delta-bar-delta (DBD) algorithm, the extended-delta-bar-delta (EDBD) algorithm, the QuickProp (QP) algorithm, and the MaxProp (MP) algorithm. Each of these algorithms is applied to a particular case study, the forecasting of salinity in the River Murray at Murray Bridge, South Australia. Thirty models are developed for each algorithm, starting from different positions in weight space. The results obtained indicate that the generalization ability of the first-order methods investigated (i.e., GD, NCD, DBD, and EDBD) is better than that of the second-order algorithms (i.e., QP and MP). When the prediction errors are averaged over the 30 trials carried out, the performance of the first-order methods in which the size of the steps taken in weight space is automatically adjusted in response to changes in the error surface (i.e., DBD and EDBD) is better than that obtained when predetermined step sizes are used (i.e., GD and NCD). However, the reverse applies when the best forecasts of the 30 trials are considered. The results obtained indicate that the EDBD algorithm is the most parsimonious and the MP algorithm is the least parsimonious. It was found that any impact different learning rules have on training speed is masked by the effect of epoch size and the number of hidden nodes required for optimal model performance.

  18. Annual energy outlook 1994: With projections to 2010

    SciTech Connect

    Not Available

    1994-01-01

    The Annual Energy Outlook 1994 (AEO94) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projects and analyses of energy supply, demand, and prices through 2010, based for the first time on results from the National Energy Modeling System (NEMS). NEMS is the latest in a series of computer-based energy modeling systems used over the past 2 decades by EIA and its predecessor organization, the Federal Energy Administration, to analyze and forecast energy consumption and supply in the midterm period (about 20 years). Quarterly forecasts of energy supply and demand for 1994 and 1995 are published in the Short-Term Energy Outlook (February 1994). Forecast tables for 2000, 2005, and 2010 for each of the five scenarios examined in the AEO94 are provided in Appendices A through E. The five scenarios include a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. Appendix F provides detailed comparisons of the AEO94 forecasts with those of other organizations. Appendix G briefly described the NEMS and the major AEO94 forecast assumptions. Appendix H summarizes the key results for the five scenarios.

  19. Comparison of a Bayesian network with a logistic regression model to forecast IgA nephropathy.

    PubMed

    Ducher, Michel; Kalbacher, Emilie; Combarnous, François; Finaz de Vilaine, Jérome; McGregor, Brigitte; Fouque, Denis; Fauvel, Jean Pierre

    2013-01-01

    Models are increasingly used in clinical practice to improve the accuracy of diagnosis. The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN) from simple clinical and biological criteria. Retrospectively, we pooled the results of all biopsies (n = 155) performed by nephrologists in a specialist clinical facility between 2002 and 2009. Two groups were constituted at random. The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC) curves. IgAN was found (on pathology) in 44 patients. Areas under the ROC curves provided by both methods were highly significant but not different from each other. Based on the highest Youden indices, sensitivity reached (100% versus 67%) and specificity (73% versus 95%) using the Bayesian network and logistic regression, respectively. A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation.

  20. Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy

    PubMed Central

    Ducher, Michel; Kalbacher, Emilie; Combarnous, François; Finaz de Vilaine, Jérome; McGregor, Brigitte; Fouque, Denis; Fauvel, Jean Pierre

    2013-01-01

    Models are increasingly used in clinical practice to improve the accuracy of diagnosis. The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN) from simple clinical and biological criteria. Retrospectively, we pooled the results of all biopsies (n = 155) performed by nephrologists in a specialist clinical facility between 2002 and 2009. Two groups were constituted at random. The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC) curves. IgAN was found (on pathology) in 44 patients. Areas under the ROC curves provided by both methods were highly significant but not different from each other. Based on the highest Youden indices, sensitivity reached (100% versus 67%) and specificity (73% versus 95%) using the Bayesian network and logistic regression, respectively. A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation. PMID:24328031

  1. 78 FR 15891 - Energy Conservation Program: Data Collection and Comparison With Forecasted Unit Sales of Five...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-13

    ... lamp's glass envelope breaks. Shatter-resistant lamps incorporate a coating compliant with industry... incandescent lamps, 2,601-3,300 lumen general service incandescent lamps, and shatter-resistant lamps), which... General Service Incandescent Lamps E. Shatter-Resistant Lamps III. Comparison Methodology IV....

  2. Comparison of two milk pricing systems and their effect on milk price and milk revenue of dairy farms in the Central region of Thailand.

    PubMed

    Rhone, J A; Ward, R; De Vries, A; Koonawootrittriron, S; Elzo, M A

    2008-06-01

    A study was conducted to investigate determinates of how milk pricing system, farm location, farm size, and month and year affected farm milk price (FMP), farm milk revenue (FMR) and loss in FMR of dairy farms in the Central region of Thailand. A total of 58,575 milk price and 813,636 milk yield records from 1034 farms were collected from November of 2004 to June of 2006. Farms were located in the districts of Muaklek, Pak Chong, Wang Muang, and Kaeng Khoi. A fixed linear model was used to analyze milk price of farms. Two pricing systems were defined as 1 = base price plus additions/deductions for milk fat percentage, solids-non-fat, and bacterial score, and 2 = same as 1 plus bulk tank somatic cell count (BTSCC). Farm size (small, medium, and large) was based on the number of cows milked per day of farms. Results showed that FMP were lower (P < 0.05) in pricing system 1 than pricing system 2. Most small farms had higher (P < 0.05) milk prices than medium and large farms across both pricing systems. Large farms lost more milk revenue due to deductions from bacterial score and BTSCC than small and medium farms.

  3. Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts

    NASA Astrophysics Data System (ADS)

    Parisi, Daniel R.; Sornette, Didier; Helbing, Dirk

    2013-01-01

    We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.

  4. A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

    NASA Astrophysics Data System (ADS)

    Zack, J. W.

    2015-12-01

    Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

  5. Chemical Weather Forecasting using the online fully integrated modeling system RAMS/ICLAMS - Comparison with the offline approach

    NASA Astrophysics Data System (ADS)

    Kushta, Jonilda; Astitha, Marina; Solomos, Stavros; Kallos, George

    2013-04-01

    In the framework of chemical weather forecasting, the online approach consists of the coupled treatment of chemical parameters, simultaneously with the meteorological parameters, in a single integrated modelling system. This approach offers the possibility to simulate the links and feedbacks between atmospheric processes that are traditionally neglected in air quality models. These links include direct and indirect effects of gases and aerosols on radiation, clouds and precipitation that in turn re-modify atmospheric composition in a two way interactive pattern. Both meteorological and chemical components are expected to benefit from this approach. The extend to which this improvement can justify a thorough migration to integrated systems is the subject of the current work. In this study we discuss the performance of the online Integrated Community Limited Area Modelling System (RAMS/ICLAMS) and compare the results with the offline use with CAMx model, for a month long summertime text period. The area under consideration is Europe and the Greater Mediterranean Region (GMR). In both on and off line simulations the same meteorological driver has been used (RAMS). The comparability of the two models is achieved with the implementation of same chemical mechanisms, meteorological fields, emissions, initial and boundary conditions. The differences in the model configurations are also taken into account in the comparison of the two modelling approaches. In this presentation, the advantages and disadvantages of simulating the regional atmospheric chemical composition by using the online versus the offline approach are analyzed and discussed.

  6. A comparison of alternative medicare reimbursement policies under optimal hospital pricing.

    PubMed Central

    Dittman, D A; Morey, R C

    1983-01-01

    This paper applies and extends the use of a nonlinear hospital pricing model, recently posited in the literature by Dittman and Morey [1]. That model applied a hospital profit-maximizing behavior and studied the effects of optimal pricing of hospital ancillary services on the incidence of payment by private insurance companies and the Medicare trust fund. Here, we examine variations of the above model where both hospital profit-maximizing and profit-satisficing postures are of interest. We apply the model to three types of Medicare reimbursement policies currently in use or under legislative mandate to implement. The policies differ according to hospital size and whether cross-subsidies are allowed. We are interested in determining the effects of profit-maximizing and -satisficing behaviors of these three reimbursement policies on the levels of profits received, and on the respective implications for private payors and the Medicare trust fund. PMID:6347973

  7. A Comparison of Hourly Typhoon Rainfall Forecasting Models Based on Support Vector Machines and Random Forests with Different Predictor Sets

    NASA Astrophysics Data System (ADS)

    Lin, Kun-Hsiang; Tseng, Hung-Wei; Kuo, Chen-Min; Yang, Tao-Chang; Yu, Pao-Shan

    2016-04-01

    Typhoons with heavy rainfall and strong wind often cause severe floods and losses in Taiwan, which motivates the development of rainfall forecasting models as part of an early warning system. Thus, this study aims to develop rainfall forecasting models based on two machine learning methods, support vector machines (SVMs) and random forests (RFs), and investigate the performances of the models with different predictor sets for searching the optimal predictor set in forecasting. Four predictor sets were used: (1) antecedent rainfalls, (2) antecedent rainfalls and typhoon characteristics, (3) antecedent rainfalls and meteorological factors, and (4) antecedent rainfalls, typhoon characteristics and meteorological factors to construct for 1- to 6-hour ahead rainfall forecasting. An application to three rainfall stations in Yilan River basin, northeastern Taiwan, was conducted. Firstly, the performance of the SVMs-based forecasting model with predictor set #1 was analyzed. The results show that the accuracy of the models for 2- to 6-hour ahead forecasting decrease rapidly as compared to the accuracy of the model for 1-hour ahead forecasting which is acceptable. For improving the model performance, each predictor set was further examined in the SVMs-based forecasting model. The results reveal that the SVMs-based model using predictor set #4 as input variables performs better than the other sets and a significant improvement of model performance is found especially for the long lead time forecasting. Lastly, the performance of the SVMs-based model using predictor set #4 as input variables was compared with the performance of the RFs-based model using predictor set #4 as input variables. It is found that the RFs-based model is superior to the SVMs-based model in hourly typhoon rainfall forecasting. Keywords: hourly typhoon rainfall forecasting, predictor selection, support vector machines, random forests

  8. Draft forecast of the final report for the comparison to 40 CFR Part 191, Subpart B, for the Waste Isolation Pilot Plant

    SciTech Connect

    Bertram-Howery, S.G.; Marietta, M.G.; Anderson, D.R.; Gomez, L.S.; Rechard, R.P. ); Brinster, K.F.; Guzowski, R.V. )

    1989-12-01

    The United States Department of Energy is planning to dispose of transuranic wastes, which have been generated by defense programs, at the Waste Isolation Pilot Plant. The WIPP Project will assess compliance with the requirements of the United States Environmental Protection Agency. This report forecasts the planned 1992 document, Comparison to 40 CFR, Part 191, Subpart B, for the Waste Isolation Pilot Plant (WIPP). 130 refs., 36 figs., 11 tabs.

  9. The Frozen Price Game

    ERIC Educational Resources Information Center

    Alden, Lori

    2003-01-01

    In this article, the author discusses the educational frozen price game she developed to teach the basic economic principle of price allocation. In addition to demonstrating the advantages of price allocation, the game also illustrates such concepts as opportunity costs, cost benefit comparisons, and the trade-off between efficiency and equity.…

  10. Simulations of Tropospheric NO2 by the Global Modeling Initiative (GMI) Model Utilizing Assimilated and Forecast Meteorological Fields: Comparison to Ozone Monitoring Instrument (OMI) Measurements

    NASA Technical Reports Server (NTRS)

    Rodriquez, J. M.; Yoshida, Y.; Duncan, B. N.; Bucsela, E. J.; Gleason, J. F.; Allen, D.; Pickering, K. E.

    2007-01-01

    We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

  11. Comparison of acoustic doppler current profiler and Price AA mechanical current meter measurements made during the 2011 Mississippi River Flood

    USGS Publications Warehouse

    O'Brien, Patrick; Mueller, David; Pratt, Thad

    2012-01-01

    The Mississippi River and Tributaries project performed as designed during the historic 2011 Mississippi River flood, with many of the operational decisions based on discharge targets as opposed to stage. Measurement of discharge at the Tarbert Landing, Mississippi range provides critical information used in operational decisions for the floodways located in Louisiana. Historically, discharge measurements have been made using a Price AA current meter and the mid-section method, and a long record exists based on these types of measurements, including historical peak discharges. Discharge measurements made using an acoustic Doppler current profiler from a moving boat have been incorporated into the record since the mid 1990's, and are used along with the Price AA mid-section measurements. During the 2011 flood event, both methods were used and appeared to provide different results at times. The apparent differences between the measurement techniques are due to complex hydrodynamics at this location that created large spatial and temporal fluctuations in the flow. The data and analysis presented herein show the difference between the two methods to be within the expected accuracy of the measurements when the measurements are made concurrently. The observed fluctuations prevent valid comparisons of data collected sequentially or even with different observation durations.

  12. The price of a drink: levels of consumption and price paid per unit of alcohol by Edinburgh's ill drinkers with a comparison to wider alcohol sales in Scotland

    PubMed Central

    Black, Heather; Gill, Jan; Chick, Jonathan

    2011-01-01

    Aim To compare alcohol purchasing and consumption by ill drinkers in Edinburgh with wider alcohol sales in Scotland. Design Cross-sectional. Setting Two hospitals in Edinburgh in 2008/09. Participants A total of 377 patients with serious alcohol problems; two-thirds were in-patients with medical, surgical or psychiatric problems due to alcohol; one-third were out-patients. Measurements Last week's or typical weekly consumption of alcohol: type, brand, units (1 UK unit 8 g ethanol), purchase place and price. Findings Patients consumed mean 197.7 UK units/week. The mean price paid per unit was £0.43 (lowest £0.09/unit) (£1 = 1.6 US$ or 1.2€), which is below the mean unit price, £0.71 paid in Scotland in 2008. Of units consumed, 70.3% were sold at or below £0.40/unit (mid-range of price models proposed for minimum pricing legislation by the Scottish Government), and 83% at or below £0.50/unit proposed by the Chief Medical Officer of England. The lower the price paid per unit, the more units a patient consumed. A continuous increase in unit price from lower to higher social status, ranked according to the Scottish Index of Multiple Deprivation (based on postcode), was not seen; patients residing in postcodes in the mid-quintile paid the highest price per unit. Cheapness was quoted commonly as a reason for beverage choice; ciders, especially ‘white’ cider, and vodka were, at off-sales, cheapest per unit. Stealing alcohol or drinking alcohol substitutes was only very rarely reported. Conclusions Because patients with serious alcohol problems tend to purchase very cheap alcohol, elimination of the cheapest sales by minimum price or other legislation might reduce their consumption. It is unknown whether proposed price legislation in Scotland will encourage patients with serious alcohol problems to start stealing alcohol or drinking substitutes or will reduce the recruitment of new drinkers with serious alcohol problems and produce predicted longer-term gains in

  13. Real time probabilistic precipitation forecasts in the Milano urban area: comparison between a physics and pragmatic approach

    NASA Astrophysics Data System (ADS)

    Ceppi, Alessandro; Ravazzani, Giovanni; Lombardi, Gabriele; Amengual, Arnau; Homar, Victor; Romero, Romu; Mancini, Marco

    2016-04-01

    Precipitation forecasts from mesoscale numerical weather prediction (NWP) models often contain features that are not deterministically predictable. In particular, accurate forecasts of deep moist convection and extreme rainfall are arduous to be predicted in terms of amount, time and target over small hydrological basins due to uncertainties arising from the numerical weather prediction (NWP), physical parameterizations and high sensitivity to misrepresentation of the atmospheric state, therefore they require a probabilistic forecast approach. Here, we examine some hydro-meteorological episodes that affected the Milano urban watersheds using a flood forecasting system which comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models. The first approach is based on a hydrological ensemble prediction system (HEPS) designed to explicitly cope with uncertainties in the initial and lateral boundary conditions (IC/LBCs) and physical parameterizations of the NWP model. The second involves a pragmatic post-processing procedure by randomly shifting in space the precipitation field provided by the deterministic WRF model run in order to get a cluster of different simulations. Although the physics-based approach needs a high computational cost, it outperforms the pragmatic set of configurations, which, however, turns out to be an acceptable low-budget alternative for real time flood forecasts over small urban basins when a single deterministic run is available.

  14. 76 FR 22324 - Energy Conservation Program: Energy Conservation Standards for Residential Clothes Dryers and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-21

    ... utilize forecasts of energy prices and housing starts from the AEO2010 Reference case, Low Economic Growth... energy prices and housing starts from the AEO2010 Reference case, Low Economic Growth case, and High...; ] DEPARTMENT OF ENERGY 10 CFR Part 430 RIN 1904-AA89 Energy Conservation Program: Energy Conservation...

  15. The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory

    SciTech Connect

    Bolinger, Mark A; Wiser, Ryan

    2008-09-15

    gas in the United States over a relatively brief period. Perhaps of most concern is that this dramatic price increase was largely unforeseen. Figure 2 compares the EIA's natural gas wellhead price forecast from each year's Annual Energy Outlook (AEO) going back to 1985 against the average US wellhead price that actually transpired. As shown, our forecasting abilities have proven rather dismal over time, as over-forecasts made in the late 1980's eventually yielded to under-forecasts that have persisted to this day. This historical experience demonstrates that little weight should be placed on any one forecast of future natural gas prices, and that a broad range of future price conditions ought to be considered in planning and investment decisions. Against this backdrop of high, volatile, and unpredictable natural gas prices, increasing the market penetration of renewable generation such as wind, solar, and geothermal power may provide economic benefits to ratepayers by displacing gas-fired generation. These benefits may manifest themselves in several ways. First, the displacement of natural gas-fired generation by increased renewable generation reduces ratepayer exposure to natural gas price risk--i.e., the risk that future gas prices (and by extension future electricity prices) may end up markedly different than expected. Second, this displacement reduces demand for natural gas among gas-fired generators, which, all else equal, will put downward pressure on natural gas prices. Lower natural gas prices in turn benefit both electric ratepayers and other end-users of natural gas. Using analytic approaches that build upon, yet differ from, the past work of others, including Awerbuch (1993, 1994, 2003), Kahn and Stoft (1993), and Humphreys and McClain (1998), this chapter explores each of these two potential 'hedging' benefits of renewable electricity. Though we do not seek to judge whether these two specific benefits outweigh any incremental cost of renewable energy

  16. Comparison of forecasts of mean monthly water level in the Paraguay River, Brazil, from two fractionally differenced models

    NASA Astrophysics Data System (ADS)

    Prass, Taiane S.; Bravo, Juan Martin; Clarke, Robin T.; Collischonn, Walter; Lopes, SíLvia R. C.

    2012-05-01

    The paper compares forecasts of mean monthly water levels up to six months ahead at Ladário, on the Upper Paraguay River, Brazil, estimated from two long-range dependence models. In one of them, the marked seasonal cycle was removed and a fractionally differenced model was fitted to the transformed series. In the other, a seasonal fractionally differenced model was fitted to water levels without transformation. Forecasts from both models for periods up to six months ahead were compared with forecasts given by simpler "short-range dependence" Box-Jenkins models, one fitted to the transformed series, the other a seasonal autoregressive moving average (ARMA) model. Estimates of parameters in the four models (two "long-range dependence", two "short-range dependence") were updated at six-monthly intervals over a 20 year period, and forecasts were compared using root mean square errors (rmse) between water-level forecasts and observed levels. As judged by rmse, performances of the two long-range dependence models, and of the ARMA (1,1) short-range dependence model, were very similar; all three out-performed the seasonal short-range dependence ARMA model. There was evidence that all models performed better during recession periods, than on the hydrograph rising limb.

  17. Alternative configurations of Quantile Regression for estimating predictive uncertainty in water level forecasts for the Upper Severn River: a comparison

    NASA Astrophysics Data System (ADS)

    Lopez, Patricia; Verkade, Jan; Weerts, Albrecht; Solomatine, Dimitri

    2014-05-01

    Hydrological forecasting is subject to many sources of uncertainty, including those originating in initial state, boundary conditions, model structure and model parameters. Although uncertainty can be reduced, it can never be fully eliminated. Statistical post-processing techniques constitute an often used approach to estimate the hydrological predictive uncertainty, where a model of forecast error is built using a historical record of past forecasts and observations. The present study focuses on the use of the Quantile Regression (QR) technique as a hydrological post-processor. It estimates the predictive distribution of water levels using deterministic water level forecasts as predictors. This work aims to thoroughly verify uncertainty estimates using the implementation of QR that was applied in an operational setting in the UK National Flood Forecasting System, and to inter-compare forecast quality and skill in various, differing configurations of QR. These configurations are (i) 'classical' QR, (ii) QR constrained by a requirement that quantiles do not cross, (iii) QR derived on time series that have been transformed into the Normal domain (Normal Quantile Transformation - NQT), and (iv) a piecewise linear derivation of QR models. The QR configurations are applied to fourteen hydrological stations on the Upper Severn River with different catchments characteristics. Results of each QR configuration are conditionally verified for progressively higher flood levels, in terms of commonly used verification metrics and skill scores. These include Brier's probability score (BS), the continuous ranked probability score (CRPS) and corresponding skill scores as well as the Relative Operating Characteristic score (ROCS). Reliability diagrams are also presented and analysed. The results indicate that none of the four Quantile Regression configurations clearly outperforms the others.

  18. Performance comparison of the Prophecy (forecasting) Algorithm in FFT form for unseen feature and time-series prediction

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James

    2013-06-01

    We introduce a generalized numerical prediction and forecasting algorithm. We have previously published it for malware byte sequence feature prediction and generalized distribution modeling for disparate test article analysis. We show how non-trivial non-periodic extrapolation of a numerical sequence (forecast and backcast) from the starting data is possible. Our ancestor-progeny prediction can yield new options for evolutionary programming. Our equations enable analytical integrals and derivatives to any order. Interpolation is controllable from smooth continuous to fractal structure estimation. We show how our generalized trigonometric polynomial can be derived using a Fourier transform.

  19. Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method

    NASA Astrophysics Data System (ADS)

    Bitter, Christopher; Mulligan, Gordon F.; Dall'Erba, Sandy

    2007-04-01

    Hedonic house price models typically impose a constant price structure on housing characteristics throughout an entire market area. However, there is increasing evidence that the marginal prices of many important attributes vary over space, especially within large markets. In this paper, we compare two approaches to examine spatial heterogeneity in housing attribute prices within the Tucson, Arizona housing market: the spatial expansion method and geographically weighted regression (GWR). Our results provide strong evidence that the marginal price of key housing characteristics varies over space. GWR outperforms the spatial expansion method in terms of explanatory power and predictive accuracy.

  20. ASSESSMENT OF ETA-CMAQ FORECASTS OF PARTICULATE MATTER DISTRIBUTIONS THROUGH COMPARISONS WITH SURFACE NETWORK AND SPECIALIZED MEASUREMENTS

    EPA Science Inventory

    An air-quality forecasting (AQF) system based on the National Weather Service (NWS) National Centers for Environmental Prediction's (NCEP's) Eta model and the U.S. EPA's Community Multiscale Air Quality (CMAQ) Modeling System is used to simulate the distributions of tropospheric ...

  1. Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China

    PubMed Central

    Wu, Wei; Guo, Junqiao; An, Shuyi; Guan, Peng; Ren, Yangwu; Xia, Linzi; Zhou, Baosen

    2015-01-01

    Background Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. Methods Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model. Results The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve. Conclusion Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS. PMID:26270814

  2. Verification and comparison of probabilistic precipitation forecasts using the TIGGE data in the upriver of Huaihe Basin

    NASA Astrophysics Data System (ADS)

    Zhao, L.-N.; Tian, F.-Y.; Wu, H.; Qi, D.; di, J.-Y.; Wang, Z.

    2011-03-01

    The precipitation forecasts of three ensemble prediction systems (EPS) and two multi-model ensemble prediction systems (MM EPS) were assessed by comparing with observations from 19 rain gauge stations located in the Dapoling-Wangjiaba sub-catchment of Huaihe Basin for the period from 1 July to 6 August 2008. The sample Probabilistic Distribution Functions (PDF) of gamma distribution, the Relative Operating Characteristic (ROC) diagrams, the percentile precipitation and a heavy rainfall event are analyzed to evaluate the performances of the single and multi-model ensemble prediction system (EPS). The three EPS were from the China Meteorological Administration (CMA); the United States National Centre for Environment Predictions (NCEP); and the European Centre for Medium-Range Weather Forecasts (ECMWF), all were obtained from the TIGGE-CMA archiving centre (THORPEX Interactive Grand Global Ensemble, TIGGE). The MM EPS were created using the equal weighting method for every ensemble member over the test area, the first ( MM-1) consisted of all three EPS, the second (MM-2) consisted of the ECMWF and NCEP EPS. The results demonstrate the level of correspondence between deterioration in predictive skill and extended lead time. Compared with observations and with a lead time of one day, ECMWF performs a little better than other centre's. With over five days in advance, all the three EPS and the two MM EPS don't give reliable probabilistic precipitation forecasts. Both MM EPS can outperform CMA and NCEP for most of the forecasted days, but still perform a little worse than ECMWF. Though variation of daily percentile precipitation and ROC areas show MM-2 outperforms MM-1, gamma distribution indicates much similar performances for all 10-day forecast, and neither is superior to ECMWF.

  3. Arima model and exponential smoothing method: A comparison

    NASA Astrophysics Data System (ADS)

    Wan Ahmad, Wan Kamarul Ariffin; Ahmad, Sabri

    2013-04-01

    This study shows the comparison between Autoregressive Moving Average (ARIMA) model and Exponential Smoothing Method in making a prediction. The comparison is focused on the ability of both methods in making the forecasts with the different number of data sources and the different length of forecasting period. For this purpose, the data from The Price of Crude Palm Oil (RM/tonne), Exchange Rates of Ringgit Malaysia (RM) in comparison to Great Britain Pound (GBP) and also The Price of SMR 20 Rubber Type (cents/kg) with three different time series are used in the comparison process. Then, forecasting accuracy of each model is measured by examinethe prediction error that producedby using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute deviation (MAD). The study shows that the ARIMA model can produce a better prediction for the long-term forecasting with limited data sources, butcannot produce a better prediction for time series with a narrow range of one point to another as in the time series for Exchange Rates. On the contrary, Exponential Smoothing Method can produce a better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while itcannot produce a better prediction for a longer forecasting period.

  4. The mirage of higher petroleum prices

    SciTech Connect

    Lynch, M.C.

    1996-02-01

    Most petroleum industry price forecasters do not possess a record of which they can be proud. Long-term petroleum market forecasting has been so inaccurate that it has often been described as virtually impossible. To avoid criticism of their performance, many organizations no longer circulate their forecasts. Why have the forecasts been so wrong? Because of failure to predict supply. This paper reviews the erroneous methods used to predict price trends in the oil and gas industry and identifies methods to correct the problem.

  5. An Experiment in Probabilistic Forecasting.

    ERIC Educational Resources Information Center

    Brown, Thomas A.

    Students were asked to make forecasts of fourteen quantities where true values would not become known for five or six months. The quantities were selected to be typical of the subjects which would be of interest to a decisionmaker in business or government, and included GNP, consumer prices, draft calls, deaths in South Vietnam, and election…

  6. Numerical forecasting of radiation fog. Part II: A comparison of model simulation with several observed fog events

    SciTech Connect

    Guedalia, D.; Bergot, T. )

    1994-06-01

    A 1D model adapted for forecasting the formation and development of fog, and forced with mesoscale parameters derived from a 3D limited-area model, was used to simulate three fog event observations made during the Lille 88 campaign. The model simulation correctly reproduced the time of fog formation and its vertical development when forcing terms derived from observations were used. It determined the influence of different physical processes and in particular that of dew deposition. The initial conditions deduced from the 3D model proved to be correct in two of the three events. On the other hand, the prediction of advection terms necessary for forecasting the vertical growth of fog was a more delicate matter. 15 refs., 21 figs.

  7. Comparison between genetic programming and an ensemble Kalman filter as data assimilation techniques for probabilistic flood forecasting

    NASA Astrophysics Data System (ADS)

    Mediero, L.; Garrote, L.; Requena, A.; Chávez, A.

    2012-04-01

    Flood events are among the natural disasters that cause most economic and social damages in Europe. Information and Communication Technology (ICT) developments in last years have enabled hydrometeorological observations available in real-time. High performance computing promises the improvement of real-time flood forecasting systems and makes the use of post processing techniques easier. This is the case of data assimilation techniques, which are used to develop an adaptive forecast model. In this paper, a real-time framework for probabilistic flood forecasting is presented and two data assimilation techniques are compared. The first data assimilation technique uses genetic programming to adapt the model to the observations as new information is available, updating the estimation of the probability distribution of the model parameters. The second data assimilation technique uses an ensemble Kalman filter to quantify errors in both hydrologic model and observations, updating estimates of system states. Both forecast models take the result of the hydrologic model calibration as a starting point and adapts the individuals of this first population to the new observations in each operation time step. Data assimilation techniques have great potential when are used in hydrological distributed models. The distributed RIBS (Real-time Interactive Basin Simulator) rainfall-runoff model was selected to simulate the hydrological process in the basin. The RIBS model is deterministic, but it is run in a probabilistic way through Monte Carlo simulations over the probability distribution functions that best characterise the most relevant model parameters, which were identified by a probabilistic multi-objective calibration developed in a previous work. The Manzanares River basin was selected as a case study. Data assimilation processes are computationally intensive. Therefore, they are well suited to test the applicability of the potential of the Grid technology to

  8. A Satellite Driven Real-time Forecasting Platform in the Upper Zambezi Basin: A Multi-model Comparison

    NASA Astrophysics Data System (ADS)

    Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Demaria, E. M.; Durcik, M.

    2015-12-01

    In large basins such as the Upper Zambezi where concentration times are of many days or even weeks, satellite precipitation products available in real-time become a key component enabling - with the use of hydrologic models - streamflow forecasts for downstream locations with enough lead time to inform decision-making. We present a real-time streamflow forecasting application based on this concept, using the TMPA and CMORPH rainfall products (which we bias-correct using the CHIRPS product) to force four distributed hydrologic models (VIC, HyMod, HBV, Sacramento) covering a variety of levels of model complexity. This study aims at establishing a multi-model satellite-based streamflow forecasting platform as a tool that can inform water management in real-time. This work is part of the efforts of the SERVIR Applied Sciences Team to bring NASA Earth Observation Applications into decision support tools for managing water resources in the Upper Zambezi, in collaboration with the Southern African Development Community Climate Services Center and the Zambezi Watercourse Commission.

  9. IT Enabled Risk Management for Taxation and Customs: The Case of AEO Assessment in the Netherlands

    NASA Astrophysics Data System (ADS)

    Liu, Jianwei; Tan, Yao-Hua; Hulstijn, Joris

    Building collaborative relationships with trusted businesses is a long-term strategy for EU governments. Recently, for the EU Tax and Customs Administration (TCA), the realization of this goal has become more visible with the emerging concept of the Authorized Economic Operator (AEO). Businesses in the member states can apply for the AEO certificate. When it is being granted, simplified control procedures and trade facilitation will be provided by the TCA. A possible “win-win situation” can be achieved, with increased trade efficiency and lowered administrative burden. However, without proper selection of trusted business partners, governments may be worse off due to the adverse selection problem caused by information asymmetry. In this paper, we analyze the cause and effect of the adverse selection in the Government-to-Business relationship building. Further, we show that an IT enabled risk assessment approach can effectively eliminate the G2B information asymmetry and solve the adverse selection problem. The AEO assessment approach of DutchTCA is analysed to give a real life application on how IT is enabling the general risk management approach of the DutchTCA.

  10. Comparison of streamflow prediction skills from NOAH-MP/RAPID, VIC/RAPID and SWAT toward an ensemble flood forecasting framework over large scales

    NASA Astrophysics Data System (ADS)

    Rajib, M. A.; Tavakoly, A. A.; Du, L.; Merwade, V.; Lin, P.

    2015-12-01

    Considering the differences in how individual models represent physical processes for runoff generation and streamflow routing, use of ensemble output is desirable in an operational streamflow estimation and flood forecasting framework. To enable the use of ensemble streamflow, comparison of multiple hydrologic models at finer spatial resolution over a large domain is yet to be explored. The objective of this work is to compare streamflow prediction skills from three different land surface/hydrologic modeling frameworks: NOAH-MP/RAPID, VIC/RAPID and SWAT, over the Ohio River Basin with a drainage area of 491,000 km2. For a uniform comparison, all the three modeling frameworks share the same setup with common weather inputs, spatial resolution, and gauge stations being employed in the calibration procedure. The runoff output from NOAH-MP and VIC land surface models is routed through a vector-based river routing model named RAPID, that is set up on the high resolution NHDPlus reaches and catchments. SWAT model is used with its default tightly coupled surface-subsurface hydrology and channel routing components to obtain streamflow for each NHDPlus reach. Model simulations are performed in two modes, including: (i) hindcasting/calibration mode in which the models are calibrated against USGS daily streamflow observations at multiple locations, and (ii) validation mode in which the calibrated models are executed at 3-hourly time interval for historical flood events. In order to have a relative assessment on the model-specific nature of biases during storm events as well as dry periods, time-series of surface runoff and baseflow components at the specific USGS gauging locations are extracted from corresponding observed/simulated streamflow data using a recursive digital filter. The multi-model comparison presented here provides insights toward future model improvements and also serves as the first step in implementing an operational ensemble flood forecasting framework

  11. High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

    Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

  12. Availability, price and affordability of cardiovascular medicines: A comparison across 36 countries using WHO/HAI data

    PubMed Central

    2010-01-01

    Background The global burden of cardiovascular disease (CVD) continues to rise. Successful treatment of CVD requires adequate pharmaceutical management. The aim was to examine the availability, pricing and affordability of cardiovascular medicines in developing countries using the standardized data collected according to the World Health Organization/Health Action International methodology. Methods The following medicines were included: atenolol, captopril, hydrochlorothiazide, losartan and nifedipine. Data from 36 countries were analyzed. Outcome measures were percentage availability, price ratios to international reference prices and number of day's wages needed by the lowest-paid unskilled government worker to purchase one month of chronic treatment. Patient prices were adjusted for inflation and purchasing power, procurement prices only for inflation. Data were analyzed for both generic and originator brand products and the public and private sector and summarized by World Bank Income Groups. Results For all measures, there was great variability across surveys. The overall availability of cardiovascular medicines was poor (mean 26.3% in public sector, 57.3% private sector). Procurement prices were very competitive in some countries, whereas others consistently paid high prices. Patient prices were generally substantially higher than international references prices; some countries, however, performed well. Chronic treatment with anti-hypertensive medication cost more than one day's wages in many cases. In particular when monotherapy is insufficient, treatment became unaffordable. Conclusions The results of this study emphasize the need of focusing attention and financing on making chronic disease medicines accessible, in particular in the public sector. Several policy options are suggested to reach this goal. PMID:20534118

  13. A comparison of limited-area energetic processes between observations and primitive equation model predictions. [cyclone Numerical Weather Forecasting

    NASA Technical Reports Server (NTRS)

    Alpert, J. C.; Chen, T.-C.

    1979-01-01

    Energetic analyses of the NMC initial conditions and NMC six-layer primitive equation operational prediction model 12-hr forecast for a developing cyclone are presented. Consideration is given to the total kinetic energy, the energetics of the divergent and nondivergent flows and the baroclinic (vertical shear flow) and barotropic (vertical mean flow) components of the kinetic energy. It is found that the model initial conditions lose 10-15% of the kinetic energy at various levels compared to a limited-area multivariate statistical analysis of the observational data, leading to a decrease in the horizontal kinetic energy flux, a misrepresentation of the synoptic scale wave system in the 12-hr forecast. Similar results are obtained for the nondivergent flow, while the divergent flow energetics are not reproduced accurately by the model. The horizontal flux terms of the vertical mean and vertical shear energetics are also not found to be reproduced in the upper levels, although horizontal flux contributions to the baroclinic component are improved at middle and lower levels. Finally, vertical shear kinetic energy generation is found to be well represented in the model prediction, however kinetic energy conversion between vertical shear and mean flow is not reproduced in the lower layer.

  14. Long-term Industrial Energy Forecasting (LIEF) model (18-sector version)

    SciTech Connect

    Ross, M.H. . Dept. of Physics); Thimmapuram, P.; Fisher, R.E.; Maciorowski, W. )

    1993-05-01

    The new 18-sector Long-term Industrial Energy Forecasting (LIEF) model is designed for convenient study of future industrial energy consumption, taking into account the composition of production, energy prices, and certain kinds of policy initiatives. Electricity and aggregate fossil fuels are modeled. Changes in energy intensity in each sector are driven by autonomous technological improvement (price-independent trend), the opportunity for energy-price-sensitive improvements, energy price expectations, and investment behavior. Although this decision-making framework involves more variables than the simplest econometric models, it enables direct comparison of an econometric approach with conservation supply curves from detailed engineering analysis. It also permits explicit consideration of a variety of policy approaches other than price manipulation. The model is tested in terms of historical data for nine manufacturing sectors, and parameters are determined for forecasting purposes. Relatively uniform and satisfactory parameters are obtained from this analysis. In this report, LIEF is also applied to create base-case and demand-side management scenarios to briefly illustrate modeling procedures and outputs.

  15. Eta-CMAQ Air Quality Forecasts for O3 and Related Species Using Three Different Photochemical Mechanisms (CB4, CB05, SAPRC-99): Comparisons with Measurements During the 2004 ICARTT Study

    EPA Science Inventory

    In this study, we compare the CB4, CB05 and SAPRC-99 mechanisms by examining the impact of these different chemical mechanisms on the Eta-CMAQ air quality forecast model simulations for O3 and its related precursors over the eastern US through comparisons with the inte...

  16. Fishing Forecasts

    NASA Technical Reports Server (NTRS)

    1988-01-01

    ROFFS stands for Roffer's Ocean Fishing Forecasting Service, Inc. Roffer combines satellite and computer technology with oceanographic information from several sources to produce frequently updated charts sometimes as often as 30 times a day showing clues to the location of marlin, sailfish, tuna, swordfish and a variety of other types. Also provides customized forecasts for racing boats and the shipping industry along with seasonal forecasts that allow the marine industry to formulate fishing strategies based on foreknowledge of the arrival and departure times of different fish. Roffs service exemplifies the potential for benefits to marine industries from satellite observations. Most notable results are reduced search time and substantial fuel savings.

  17. Trend estimation and univariate forecast of the sunspot numbers: Development and comparison of ARMA, ARIMA and Autoregressive Neural Network models

    NASA Astrophysics Data System (ADS)

    Chattopadhyay, Surajit; Jhajharia, Deepak; Chattopadhyay, Goutami

    2011-07-01

    In the present study, a prominent 11-year cycle, supported by the pattern of the autocorrelation function and measures of Euclidean distances, in the mean annual sunspot number time series has been observed by considering the sunspot series for the duration of 1749 to 2007. The trend in the yearly sunspot series, which is found to be non-normally distributed, is examined through the Mann-Kendall non-parametric test. A statistically significant increasing trend is observed in the sunspot series in annual duration. The results indicate that the performance of the autoregressive neural network-based model is much better than the autoregressive moving average and autoregressive integrated moving average-based models for the univariate forecast of the yearly mean sunspot numbers.

  18. Climate Time Series Analysis and Forecasting

    NASA Astrophysics Data System (ADS)

    Young, P. C.; Fildes, R.

    2009-04-01

    This paper will discuss various aspects of climate time series data analysis, modelling and forecasting being carried out at Lancaster. This will include state-dependent parameter, nonlinear, stochastic modelling of globally averaged atmospheric carbon dioxide; the computation of emission strategies based on modern control theory; and extrapolative time series benchmark forecasts of annual average temperature, both global and local. The key to the forecasting evaluation will be the iterative estimation of forecast error based on rolling origin comparisons, as recommended in the forecasting research literature. The presentation will conclude with with a comparison of the time series forecasts with forecasts produced from global circulation models and a discussion of the implications for climate modelling research.

  19. Explaining high health care spending in the United States: an international comparison of supply, utilization, prices, and quality.

    PubMed

    Squires, David A

    2012-05-01

    This analysis uses data from the Organization for Economic Cooperation and Development and other sources to compare health care spending, supply, utilization, prices, and quality in 13 industrialized countries: Australia, Canada, Denmark, France, Germany, Japan, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States. The U.S. spends far more on health care than any other country. However this high spending cannot be attributed to higher income, an older population, or greater supply or utilization of hospitals and doctors. Instead, the findings suggest the higher spending is more likely due to higher prices and perhaps more readily accessible technology and greater obesity. Health care quality in the U.S. varies and is not notably superior to the far less expensive systems in the other study countries. Of the countries studied, Japan has the lowest health spending, which it achieves primarily through aggressive price regulation. PMID:22582452

  20. Explaining high health care spending in the United States: an international comparison of supply, utilization, prices, and quality.

    PubMed

    Squires, David A

    2012-05-01

    This analysis uses data from the Organization for Economic Cooperation and Development and other sources to compare health care spending, supply, utilization, prices, and quality in 13 industrialized countries: Australia, Canada, Denmark, France, Germany, Japan, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States. The U.S. spends far more on health care than any other country. However this high spending cannot be attributed to higher income, an older population, or greater supply or utilization of hospitals and doctors. Instead, the findings suggest the higher spending is more likely due to higher prices and perhaps more readily accessible technology and greater obesity. Health care quality in the U.S. varies and is not notably superior to the far less expensive systems in the other study countries. Of the countries studied, Japan has the lowest health spending, which it achieves primarily through aggressive price regulation. PMID:22619775

  1. Explaining high health care spending in the United States: an international comparison of supply, utilization, prices, and quality.

    PubMed

    Squires, David A

    2012-05-01

    This analysis uses data from the Organization for Economic Cooperation and Development and other sources to compare health care spending, supply, utilization, prices, and quality in 13 industrialized countries: Australia, Canada, Denmark, France, Germany, Japan, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States. The U.S. spends far more on health care than any other country. However this high spending cannot be attributed to higher income, an older population, or greater supply or utilization of hospitals and doctors. Instead, the findings suggest the higher spending is more likely due to higher prices and perhaps more readily accessible technology and greater obesity. Health care quality in the U.S. varies and is not notably superior to the far less expensive systems in the other study countries. Of the countries studied, Japan has the lowest health spending, which it achieves primarily through aggressive price regulation.

  2. Probabilistic Downscaling Methods for Developing Categorical Streamflow Forecasts using Climate Forecasts

    NASA Astrophysics Data System (ADS)

    Mazrooei, A. H.

    2015-12-01

    Statistical information from climate forecast ensembles can be utilized in developing probabilistic streamflow forecasts for providing the uncertainty in streamflow forecast potential. This study examines the use of Multinomial Logistic Regression (MLR) in downscaling the probabilistic information from the large-scale climate forecast ensembles into a point-scale categorical streamflow forecasts. Performance of MLR in developing one-month lead categorical forecasts is evaluated for various river basins over the US Sunbelt. Comparison of MLR with the estimated categorical forecasts from Principle Component Regression (PCR) method under both cross-validation and split-sampling validation reveals that in general the forecasts from MLR has better performance and lower Rank Probability Score (RPS) compared to the PCR forecasts. In addition, MLR performs better than PCR method particularly in arid basins that exhibit strong skewness in seasonal flows with records of distinct dry years. A theoretical underpinning for this improved performance of MLR is also provided.

  3. Bayesian change-point analysis in hydrometeorological time series. Part 2. Comparison of change-point models and forecasting

    NASA Astrophysics Data System (ADS)

    Perreault, L.; Bernier, J.; Bobée, B.; Parent, E.

    2000-08-01

    This paper provides a methodology to test existence, type, and strength of changes in the distribution of a sequence of hydrometeorological random variables. Unlike most published work on change-point analysis, which consider a single structure of change occurring with certainty, it allows for the consideration in the inference process of the no change hypothesis and various possible situations that may occur. The approach is based on Bayesian model selection and is illustrated using univariate normal models. Four univariate normal models are considered: the no change hypothesis, a single change in the mean level only, a single change in the variance only, and a simultaneous change in both the mean and the variance. First, inference analysis of posterior distributions via Gibbs sampling for a given change-point model is recalled. This scientific reporting framework is then generalized to the problem of selecting among different configurations of a single change and the no change hypothesis. The important operational issue of forecasting a future observation, often neglected in the literature on change-point analysis, is also treated in the previous model selection perspective. To illustrate the approach, a case study involving annual energy inflows for eight large hydropower systems situated in Québec is detailed.

  4. Comparison of the Effects of RAS vs. Kain-Fritsch Convective Schemes on Katrina Forecasts with GEOS-5

    NASA Technical Reports Server (NTRS)

    Miller, Timothy L.; Cohen, Charles; Paxton, Jessica; Robertson, F. R. (Pete)

    2009-01-01

    Global forecasts were made with the 0.25-degree latitude version of GEOS-5, with the RAS scheme and with the Kain-Fritsch scheme. Examination was made of the Katrina (2005) hurricane simulation. Replacement of the RAS convective scheme with the K-F scheme results in a much more vigorous Katrina, closer to reality. Still, the result is not as vigorous as reality. In terms of wind maximum, the gap was closed by 50%. The result seems to be due to the RAS scheme drying out the boundary layer, thus hampering the grid-scale secondary circulation and attending cyclone development. The RAS case never developed a full warm core, whereas the K-F case did. Not shown here: The K-F scheme also resulted in a more vigorous storm than when GEOS-5 is run with no convective parameterization. Also not shown: An experiment in which the RAS firing level was moved up by 3 model levels resulted in a stronger, warm-core storm, though not as strong as the K-F case. Effects on storm track were noticed, but not studied.

  5. EU pharmaceutical expenditure forecast

    PubMed Central

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Method In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012–2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. Results According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (−€9,367 million), France

  6. Long-range forecast of all India summer monsoon rainfall using adaptive neuro-fuzzy inference system: skill comparison with CFSv2 model simulation and real-time forecast for the year 2015

    NASA Astrophysics Data System (ADS)

    Chaudhuri, S.; Das, D.; Goswami, S.; Das, S. K.

    2016-02-01

    All India summer monsoon rainfall (AISMR) characteristics play a vital role for the policy planning and national economy of the country. In view of the significant impact of monsoon system on regional as well as global climate systems, accurate prediction of summer monsoon rainfall has become a challenge. The objective of this study is to develop an adaptive neuro-fuzzy inference system (ANFIS) for long range forecast of AISMR. The NCEP/NCAR reanalysis data of temperature, zonal and meridional wind at different pressure levels have been taken to construct the input matrix of ANFIS. The membership of the input parameters for AISMR as high, medium or low is estimated with trapezoidal membership function. The fuzzified standardized input parameters and the de-fuzzified target output are trained with artificial neural network models. The forecast of AISMR with ANFIS is compared with non-hybrid multi-layer perceptron model (MLP), radial basis functions network (RBFN) and multiple linear regression (MLR) models. The forecast error analyses of the models reveal that ANFIS provides the best forecast of AISMR with minimum prediction error of 0.076, whereas the errors with MLP, RBFN and MLR models are 0.22, 0.18 and 0.73 respectively. During validation with observations, ANFIS shows its potency over the said comparative models. Performance of the ANFIS model is verified through different statistical skill scores, which also confirms the aptitude of ANFIS in forecasting AISMR. The forecast skill of ANFIS is also observed to be better than Climate Forecast System version 2. The real-time forecast with ANFIS shows possibility of deficit (65-75 cm) AISMR in the year 2015.

  7. Comparison of Nutrient Content and Cost of Home-Packed Lunches to Reimbursable School Lunch Nutrient Standards and Prices

    ERIC Educational Resources Information Center

    Johnson, Cara M.; Bednar, Carolyn; Kwon, Junehee; Gustof, Alissa

    2009-01-01

    Purpose: The purpose of this study was to compare nutrient content and cost of home-packed lunches to nutrient standards and prices for reimbursable school lunches. Methods: Researchers observed food and beverage contents of 333 home packed lunches at four north Texas elementary schools. Nutritionist Pro was used to analyze lunches for calories,…

  8. Practical overview of ARIMA models for time-series forecasting

    SciTech Connect

    Pack, D.J.

    1980-01-01

    Single series analysis methodology is illustrated. The commentary summarizes the Box-Jenkins philosophy and the ARIMA model structure, with particular emphasis on practical aspects of application, forecast interpretation, strengths weaknesses, and comparison to other time series forecasting approaches. (GHT)

  9. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect

    Wegley, H.L.; Formica, W.J.

    1983-07-01

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  10. Reasonable Forecasts

    ERIC Educational Resources Information Center

    Taylor, Kelley R.

    2010-01-01

    This article presents a sample legal battle that illustrates school officials' "reasonable forecasts" of substantial disruption in the school environment. In 2006, two students from a Texas high school came to school carrying purses decorated with images of the Confederate flag. The school district has a zero-tolerance policy for clothing or…

  11. Short-Termed Integrated Forecasting System: 1993 Model documentation report

    SciTech Connect

    Not Available

    1993-05-01

    The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

  12. Recently released EIA report presents international forecasting data

    SciTech Connect

    1995-05-01

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

  13. Online Pricing.

    ERIC Educational Resources Information Center

    Garman, Nancy; And Others

    1990-01-01

    The first of four articles describes the move by the European Space Agency to eliminate connect time charges on its online retrieval system. The remaining articles describe the pricing structure of DIALOG, compare the two pricing schemes, and discuss online pricing from the user's point of view. (CLB)

  14. National hospital input price index.

    PubMed

    Freeland, M S; Anderson, G; Schendler, C E

    1979-01-01

    The national community hospital input price index presented here isolates the effects of prices of goods and services required to produce hospital care and measures the average percent change in prices for a fixed market basket of hospital inputs. Using the methodology described in this article, weights for various expenditure categories were estimated and proxy price variables associated with each were selected. The index is calculated for the historical period 1970 through 1978 and forecast for 1979 through 1981. During the historical period, the input price index increased an average of 8.0 percent a year, compared with an average rate of increase of 6.6 percent for overall consumer prices. For the period 1979 through 1981, the average annual increase is forecast at between 8.5 and 9.0 per cent. Using the index to deflate growth in expenses, the level of real growth in expenditures per inpatient day (net service intensity growth) averaged 4.5 percent per year with considerable annual variation related to government and hospital industry policies. PMID:10309052

  15. National hospital input price index.

    PubMed

    Freeland, M S; Anderson, G; Schendler, C E

    1979-01-01

    The national community hospital input price index presented here isolates the effects of prices of goods and services required to produce hospital care and measures the average percent change in prices for a fixed market basket of hospital inputs. Using the methodology described in this article, weights for various expenditure categories were estimated and proxy price variables associated with each were selected. The index is calculated for the historical period 1970 through 1978 and forecast for 1979 through 1981. During the historical period, the input price index increased an average of 8.0 percent a year, compared with an average rate of increase of 6.6 percent for overall consumer prices. For the period 1979 through 1981, the average annual increase is forecast at between 8.5 and 9.0 per cent. Using the index to deflate growth in expenses, the level of real growth in expenditures per inpatient day (net service intensity growth) averaged 4.5 percent per year with considerable annual variation related to government and hospital industry policies.

  16. TRAVEL FORECASTER

    NASA Technical Reports Server (NTRS)

    Mauldin, L. E.

    1994-01-01

    Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of

  17. Combining forecast weights: Why and how?

    NASA Astrophysics Data System (ADS)

    Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

    2012-09-01

    This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

  18. Short-Term Energy Outlook Model Documentation: Petroleum Product Prices Module

    EIA Publications

    2015-01-01

    The petroleum products price module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. average wholesale and retail price forecasts for motor gasoline, diesel fuel, heating oil, and jet fuel.

  19. Short-Term Energy Outlook Model Documentation: Regional Residential Propane Price Model

    EIA Publications

    2009-01-01

    The regional residential propane price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 Census regions: Northeast, South, Midwest, and West.

  20. Short-Term Energy Outlook Model Documentation: Regional Residential Heating Oil Price Model

    EIA Publications

    2009-01-01

    The regional residential heating oil price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 census regions: Northeast, South, Midwest, and West.

  1. Comparison of hourly solar radiation from ground-based station, remote sensing sensors and weather forecast models: A preliminary study, in a coastal site of South Italy (Lamezia Terme).

    NASA Astrophysics Data System (ADS)

    Lo Feudo, Teresa; Avolio, Elenio; Gullì, Daniel; Federico, Stefano; Sempreviva, Annamaria; Calidonna, Claudia Roberta

    2015-04-01

    The solar radiation is a very complex parameter to cope with due to its random and nonlinear characteristics depending on changeable weather conditions and complex orography. Therefore it is a critical input parameter to address many climatic, meteorological, and solar energy issues. In this preliminary study we made an intercomparison between the hourly solar MSG SEVIRI (Meteosat Second Generation Spinning Enhanced Visible and Infrared) data product DSSF(Down-welling Surface Short-wave Flux) developed by LSA SAF( Land Surface Analysis Satellite Application Facility), a pyranometer sensor (CNR 4 Net Radiometer - Kipp&Zonen) and two weather forecast models. The solar radiation datasets were obtained from a pyranometer sensor situated in Weather Station of CNR ISAC Lamezia Terme(38,88 LAT 16,24 LON), a satellite based product DSSF with spatial resolution of 3km and outputs of two weather forecast models. Models adopted are WRF(Weather Research and Forecasting) and Rams( Regional Atmospheric Modeling System)running operatively with a 3Km horizontal resolution. Both DSSF and model outputs are extracted at Latitude and Longitude previously defined. The solar radiation performance and accuracy are evaluated for datasets segmented into two atmospheric conditions clear and cloudy sky, and both conditions, additionally, for a quantitative analysis the exact acquisition times of satellite measurements was taken into account. The RMSE and BIAS for hourly, daily and monthly - averaged solar radiation are estimated including clear and sky conditions and snow or ice cover. Comparison between DSSF product, Solar Radiation ground based pyranometer measurements and output of two weather forecast models, made over the period June2013-December2013, showed a good agreement in this costal site and we demonstrated that the forecast models generally overestimate solar radiation respect the ground based sensor and DSSF product. As results in general the RMSE monthly-averaged are

  2. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    EIA Publications

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  3. Intermediate-term forecasting techniques for management. Master's thesis

    SciTech Connect

    Herring, D.L.

    1984-06-01

    In this thesis autoregressive Integrated Moving Average (ARIMA) forecasts are made for the prices of a variety of commodities one year into the future in an attempt to determine if improved budget accuracy is possible for small businesses dependent upon commodities for the production of goods or services. An average forecast error of less than 7% is obtained using commonly available ARIMA computer software employable on inexpensive microcomputers. It is concluded small businesses can affordably obtain more accurate commodity price budgets through the use of ARIMA forecasts.

  4. Flood Forecasting in Wales: Challenges and Solutions

    NASA Astrophysics Data System (ADS)

    How, Andrew; Williams, Christopher

    2015-04-01

    With steep, fast-responding river catchments, exposed coastal reaches with large tidal ranges and large population densities in some of the most at-risk areas; flood forecasting in Wales presents many varied challenges. Utilising advances in computing power and learning from best practice within the United Kingdom and abroad have seen significant improvements in recent years - however, many challenges still remain. Developments in computing and increased processing power comes with a significant price tag; greater numbers of data sources and ensemble feeds brings a better understanding of uncertainty but the wealth of data needs careful management to ensure a clear message of risk is disseminated; new modelling techniques utilise better and faster computation, but lack the history of record and experience gained from the continued use of more established forecasting models. As a flood forecasting team we work to develop coastal and fluvial forecasting models, set them up for operational use and manage the duty role that runs the models in real time. An overview of our current operational flood forecasting system will be presented, along with a discussion on some of the solutions we have in place to address the challenges we face. These include: • real-time updating of fluvial models • rainfall forecasting verification • ensemble forecast data • longer range forecast data • contingency models • offshore to nearshore wave transformation • calculation of wave overtopping

  5. Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.

    1984-01-01

    Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

  6. Short-term forecasting regional model to predict M(3000)F2 over the European sector: Comparisons with the IRI model during moderate, disturbed, and very disturbed geomagnetic conditions

    NASA Astrophysics Data System (ADS)

    Pietrella, M.

    2014-07-01

    The hourly measurements of M(3000)F2 (M(3000)F2meas) and the hourly quiet-time values of M(3000)F2 (M(3000)F2QT) relative to the ionospheric observatories of Poitiers, Lannion, Dourbes, Slough, Rome, Juliusruh, Kaliningrad, Uppsala, Lyckesele, Sodankyla, and Kiruna as well as the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap (ap(τ), were considered during the period January 1957-December 2003 and used for the development of 11 short-term forecasting local models (STFLM) of M(3000)F2. Under the assumption that the ionospheric disturbance index ln(M(3000)F2meas/M(3000)F2QT) is correlated to the integrated geomagnetic index ap(τ), a set of regression coefficients were established over 12 months and 24 h for each of the 11 observatories under consideration and used as input to calculate the short-term ionospheric forecasting of M(3000)F2 for three different ranges of geomagnetic activity. The 11 short-term forecasting local models all together constitute a single short-term forecasting regional model (STFRM) of M(3000)F2. The monthly median predictions of M(3000)F2 provided by the IRI model at the 11 local stations were used to make some comparisons with the predictions of M(3000)F2 carried out by the STFRM. The results showed that: (1) under moderate geomagnetic activity there are no significantly differences between STFRM and IRI performance because quiet geomagnetic conditions are not so diverse from moderate geomagnetic conditions; (2) under disturbed geomagnetic activity, performances of STFRM significantly better than IRI emerge only in some cases; (3) the STFRM's performances are always significantly better than those provided by IRI under very disturbed geomagnetic activity, consequently the operative use of the STFRM could be valuable in providing short-term forecasting maps of M(3000)F2 over the European area during very disturbed geomagnetic conditions.

  7. Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions

    NASA Astrophysics Data System (ADS)

    Žabkar, R.; Honzak, L.; Skok, G.; Forkel, R.; Rakovec, J.; Ceglar, A.; Žagar, N.

    2015-07-01

    An integrated modelling system based on the regional online coupled meteorology-atmospheric chemistry WRF-Chem model configured with two nested domains with horizontal resolutions of 11.1 and 3.7 km has been applied for numerical weather prediction and for air quality forecasts in Slovenia. In the study, an evaluation of the air quality forecasting system has been performed for summer 2013. In the case of ozone (O3) daily maxima, the first- and second-day model predictions have been also compared to the operational statistical O3 forecast and to the persistence. Results of discrete and categorical evaluations show that the WRF-Chem-based forecasting system is able to produce reliable forecasts which, depending on monitoring site and the evaluation measure applied, can outperform the statistical model. For example, the correlation coefficient shows the highest skill for WRF-Chem model O3 predictions, confirming the significance of the non-linear processes taken into account in an online coupled Eulerian model. For some stations and areas biases were relatively high due to highly complex terrain and unresolved local meteorological and emission dynamics, which contributed to somewhat lower WRF-Chem skill obtained in categorical model evaluations. Applying a bias correction could further improve WRF-Chem model forecasting skill in these cases.

  8. Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir

    NASA Astrophysics Data System (ADS)

    Valipour, Mohammad; Banihabib, Mohammad Ebrahim; Behbahani, Seyyed Mahmood Reza

    2013-01-01

    SummaryThe goal of the present research is forecasting the inflow of Dez dam reservoir by using Auto Regressive Moving Average (ARMA) and Auto Regressive Integrated Moving Average (ARIMA) models while increasing the number of parameters in order to increase the forecast accuracy to four parameters and comparing them with the static and dynamic artificial neural networks. In this research, monthly discharges from 1960 to 2007 were used. The statistics related to first 42 years were used to train the models and the 5 past years were used to forecast. In ARMA and ARIMA models, the polynomial was derived respectively with four and six parameters to forecast the inflow. In the artificial neural network, the radial and sigmoid activity functions were used with several different neurons in the hidden layers. By comparing root mean square error (RMSE) and mean bias error (MBE), dynamic artificial neural network model with sigmoid activity function and 17 neurons in the hidden layer was chosen as the best model for forecasting inflow of the Dez dam reservoir. Inflow of the dam reservoir in the 12 past months shows that ARIMA model had a less error compared with the ARMA model. Static and Dynamic autoregressive artificial neural networks with activity sigmoid function can forecast the inflow to the dam reservoirs from the past 60 months.

  9. Comparison of the performance and reliability of 18 lumped hydrological models driven by ECMWF rainfall ensemble forecasts: a case study on 29 French catchments

    NASA Astrophysics Data System (ADS)

    Velázquez, Juan Alberto; Anctil, François; Ramos, Maria-Helena; Perrin, Charles

    2010-05-01

    An ensemble forecasting system seeks to assess and to communicate the uncertainty of hydrological predictions by proposing, at each time step, an ensemble of forecasts from which one can estimate the probability distribution of the predictant (the probabilistic forecast), in contrast with a single estimate of the flow, for which no distribution is obtainable (the deterministic forecast). In the past years, efforts towards the development of probabilistic hydrological prediction systems were made with the adoption of ensembles of numerical weather predictions (NWPs). The additional information provided by the different available Ensemble Prediction Systems (EPS) was evaluated in a hydrological context on various case studies (see the review by Cloke and Pappenberger, 2009). For example, the European ECMWF-EPS was explored in case studies by Roulin et al. (2005), Bartholmes et al. (2005), Jaun et al. (2008), and Renner et al. (2009). The Canadian EC-EPS was also evaluated by Velázquez et al. (2009). Most of these case studies investigate the ensemble predictions of a given hydrological model, set up over a limited number of catchments. Uncertainty from weather predictions is assessed through the use of meteorological ensembles. However, uncertainty from the tested hydrological model and statistical robustness of the forecasting system when coping with different hydro-meteorological conditions are less frequently evaluated. The aim of this study is to evaluate and compare the performance and the reliability of 18 lumped hydrological models applied to a large number of catchments in an operational ensemble forecasting context. Some of these models were evaluated in a previous study (Perrin et al. 2001) for their ability to simulate streamflow. Results demonstrated that very simple models can achieve a level of performance almost as high (sometimes higher) as models with more parameters. In the present study, we focus on the ability of the hydrological models to

  10. Pricing Options.

    ERIC Educational Resources Information Center

    Tenopir, Carol

    1998-01-01

    Presents results of a recent survey of over 100 public and academic libraries about pricing options from online companies. Most options fall into three categories: pay-as-you-go, fixed-rate, and user-based. Results are discussed separately for public and academic libraries and for consortial discounts. Trends in pricing options preferred by…

  11. 18 CFR Appendix A 1 to Part 281 - Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976...

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... steam electric plants. Prices paid for No. 6 fuel oil include prices paid for minor amounts of No. 4 and No. 5 fuel oil, crude and topped crude. Type of fuel FPC form No. 423 price data 1 1976 1977 1978... 194.8 97.2 131.9 154.1 201.8 237.3 Actual price difference (fuel oil and coal versus natural gas)...

  12. Forecast Mekong

    USGS Publications Warehouse

    Turnipseed, D. Phil

    2011-01-01

    Forecast Mekong is part of the U.S. Department of State's Lower Mekong Initiative, which was launched in 2009 by Secretary Hillary Clinton and the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam to enhance partnerships between the U.S. and the Lower Mekong River countries in the areas of environment, health, education, and infrastructure. The U.S. Geological Survey (USGS) is working in close cooperation with the U.S. Department of State to use research and data from the Lower Mekong Basin to provide hands-on results that will help decision makers in Lower Mekong River countries in the planning and design for restoration, conservation, and management efforts in the basin.

  13. Adaptive use of technical indicators for the prediction of intra-day stock prices

    NASA Astrophysics Data System (ADS)

    Tanaka-Yamawaki, Mieko; Tokuoka, Seiji

    2007-09-01

    We examine the effectiveness of frequently used technical indicators for intra-day forecast by applying them on the tick data of various stock prices. We show that the optimal combination of a few indicators chosen for each stock by using evolutional computation provides us a good forecast on the level of the future price at several ticks ahead.

  14. Comparison of three different methods of perturbing the potential vorticity field in mesoscale forecasts of Mediterranean heavy precipitation events: PV-gradient, PV-adjoint and PV-satellite

    NASA Astrophysics Data System (ADS)

    Vich, M.; Romero, R.; Richard, E.; Arbogast, P.; Maynard, K.

    2010-09-01

    a forecast with the corresponding perturbed initial state (PV-satellite). The non hydrostatic MM5 mesoscale model has been used to run all forecasts. The simulations are performed for a two-day period with a 22.5 km resolution domain (Domain 1 in http://mm5forecasts.uib.es) nested in the ECMWF large-scale forecast fields. The MEDEX cyclone of 10 June 2000, also known as the Montserrat Case, is a suitable testbed to compare the performance of each ensemble and the PV-satellite method. This case is characterized by an Atlantic upper-level trough and low-level cold front which generated a stationary mesoscale cyclone over the Spanish Mediterranean coast, advecting warm and moist air toward Catalonia from the Mediterranean Sea. The consequences of the resulting mesoscale convective system were 6-h accumulated rainfall amounts of 180 mm with estimated material losses to exceed 65 million euros by media. The performace of both ensemble forecasting systems and PV-satellite technique for our case study is evaluated through the verification of the rainfall field. Since the EPSs are probabilistic forecasts and the PV-satellite is deterministic, their comparison is done using the individual ensemble members. Therefore the verification procedure uses deterministic scores, like the ROC curve, the Taylor diagram or the Q-Q plot. These scores cover the different quality attributes of the forecast such as reliability, resolution, uncertainty and sharpness. The results show that the PV-satellite technique performance lies within the performance range obtained by both ensembles; it is even better than the non-perturbed ensemble member. Thus, perturbing randomly using the PV error climatology and introducing the perturbations in the zones given by each EPS captures the mismatch between PV and WV fields better than manual perturbations made by an expert forecaster, at least for this case study.

  15. Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada

    NASA Astrophysics Data System (ADS)

    Adamowski, Jan; Fung Chan, Hiu; Prasher, Shiv O.; Ozga-Zielinski, Bogdan; Sliusarieva, Anna

    2012-01-01

    Daily water demand forecasts are an important component of cost-effective and sustainable management and optimization of urban water supply systems. In this study, a method based on coupling discrete wavelet transforms (WA) and artificial neural networks (ANNs) for urban water demand forecasting applications is proposed and tested. Multiple linear regression (MLR), multiple nonlinear regression (MNLR), autoregressive integrated moving average (ARIMA), ANN and WA-ANN models for urban water demand forecasting at lead times of one day for the summer months (May to August) were developed, and their relative performance was compared using the coefficient of determination, root mean square error, relative root mean square error, and efficiency index. The key variables used to develop and validate the models were daily total precipitation, daily maximum temperature, and daily water demand data from 2001 to 2009 in the city of Montreal, Canada. The WA-ANN models were found to provide more accurate urban water demand forecasts than the MLR, MNLR, ARIMA, and ANN models. The results of this study indicate that coupled wavelet-neural network models are a potentially promising new method of urban water demand forecasting that merit further study.

  16. Supplement to the annual energy outlook 1994

    SciTech Connect

    1994-03-01

    This report is a companion document to the Annual Energy Outlook 1994 (AEO94), (DOE/EIA-0383(94)), released in Jan. 1994. Part I of the Supplement presents the key quantitative assumptions underlying the AEO94 projections, responding to requests by energy analysts for additional information on the forecasts. In Part II, the Supplement provides regional projections and other underlying details of the reference case projections in the AEO94. The AEO94 presents national forecasts of energy production, demand and prices through 2010 for five scenarios, including a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. These forecasts are used by Federal, State, and local governments, trade associations, and other planners and decisionmakers in the public and private sectors.

  17. Retrospective Evaluation of Appliance Price Trends

    SciTech Connect

    Dale, Larry; Antinori, Camille; McNeil, Michael; McMahon, James E.; Fujita, K. Sydny

    2008-07-20

    Real prices of major appliances (refrigerators, dishwashers, heating and cooling equipment) have been falling since the late 1970s despite increases in appliance efficiency and other quality variables. This paper demonstrates that historic increases in efficiency over time, including those resulting from minimum efficiency standards, incur smaller price increases than were expected by Department of Energy (DOE) forecasts made in conjunction with standards. This effect can be explained by technological innovation, which lowers the cost of efficiency, and by market changes contributing to lower markups and economies of scale in production of higher efficiency units. We reach four principal conclusions about appliance trends and retail price setting: 1. For the past several decades, the retail price of appliances has been steadily falling while efficiency has been increasing. 2. Past retail price predictions made by DOE analyses of efficiency standards, assuming constant prices over time, have tended to overestimate retail prices. 3. The average incremental price to increase appliance efficiency has declined over time. DOE technical support documents have typically overestimated this incremental price and retail prices. 4. Changes in retail markups and economies of scale in production of more efficient appliances may have contributed to declines in prices of efficient appliances.

  18. Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

    NASA Astrophysics Data System (ADS)

    Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

    2014-05-01

    Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

  19. Ozone Production in the Boston Urban Area and Transport Downwind: Computation from Lidar Measurements and Comparison with Air Quality Forecast Models

    NASA Astrophysics Data System (ADS)

    Hardesty, R. M.; Senff, C. J.; Alvarez, R. J.; Sandberg, S. P.; McKeen, S. A.; Wilczak, J. M.; Djalalova, I. V.; White, A. B.

    2005-12-01

    An important element in understanding and successfully forecasting local air quality events is accurate characterization of production of pollutants in urban regions and advection to areas downwind. During the 2004 New England Air Quality Study (NEAQS), which was conducted within the framework of the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field experiment, NOAA deployed its airborne ozone and aerosol lidar to characterize the 3-dimensional structure of ozone and aerosol fields in the New England region. We have used the data set gathered with the lidar to compute ozone production in the Boston urban plume and to investigate transport and mixing processes for several days of the study. One of the few high ozone events in northern New England during the summer of 2004 occurred on July 30, when ozone levels exceeded 100 ppbv on Appledore Island just east of Portsmouth, NH. On this day, trajectories computed from wind profiler data showed that the New York plume was transported directly over Boston and then north-northeastwards along the New Hampshire and Maine coasts. By flying across the plume upstream and downwind of Boston and computing the horizontal ozone flux within the plume, we were able to estimate that the ozone flux downwind of Boston increased by 36 percent, concentrating the pollutants and likely playing a role in the high ozone observed. We also examined transport on August 3, when a shallow plume of high ozone was observed near Bar Harbor, ME. Trajectories indicated that this was a piece of the previous day's Boston plume, which was likely transported overnight across the Gulf of Maine in a very shallow layer. Later in the day, another plume was observed further south near Portland, ME. Trajectories showed that this was the Boston plume emitted on the morning of August 3, which followed a different transport path due to changes in the wind field over the period. On August 9, we mapped out the Boston

  20. Comparison of the performance and reliability of 18 lumped hydrological models driven by ECMWF rainfall ensemble forecasts: a case study on 29 French catchments

    NASA Astrophysics Data System (ADS)

    Velázquez, Juan Alberto; Anctil, François; Ramos, Maria-Helena; Perrin, Charles

    2010-05-01

    An ensemble forecasting system seeks to assess and to communicate the uncertainty of hydrological predictions by proposing, at each time step, an ensemble of forecasts from which one can estimate the probability distribution of the predictant (the probabilistic forecast), in contrast with a single estimate of the flow, for which no distribution is obtainable (the deterministic forecast). In the past years, efforts towards the development of probabilistic hydrological prediction systems were made with the adoption of ensembles of numerical weather predictions (NWPs). The additional information provided by the different available Ensemble Prediction Systems (EPS) was evaluated in a hydrological context on various case studies (see the review by Cloke and Pappenberger, 2009). For example, the European ECMWF-EPS was explored in case studies by Roulin et al. (2005), Bartholmes et al. (2005), Jaun et al. (2008), and Renner et al. (2009). The Canadian EC-EPS was also evaluated by Velázquez et al. (2009). Most of these case studies investigate the ensemble predictions of a given hydrological model, set up over a limited number of catchments. Uncertainty from weather predictions is assessed through the use of meteorological ensembles. However, uncertainty from the tested hydrological model and statistical robustness of the forecasting system when coping with different hydro-meteorological conditions are less frequently evaluated. The aim of this study is to evaluate and compare the performance and the reliability of 18 lumped hydrological models applied to a large number of catchments in an operational ensemble forecasting context. Some of these models were evaluated in a previous study (Perrin et al. 2001) for their ability to simulate streamflow. Results demonstrated that very simple models can achieve a level of performance almost as high (sometimes higher) as models with more parameters. In the present study, we focus on the ability of the hydrological models to

  1. STATUS AND PROGRESS IN PARTICULATE MATTER FORECASTING: INITIAL APPLICATION OF THE ETA- CMAQ FORECAST MODEL

    EPA Science Inventory

    This presentation reviews the status and progress in forecasting particulate matter distributions. The shortcomings in representation of particulate matter formation in current atmospheric chemistry/transport models are presented based on analyses and detailed comparisons with me...

  2. Forecasting Three-Month Outcomes in a Laboratory School Comparison of Mixed Amphetamine Salts Extended Release (Adderall XR) and Atomoxetine (Strattera) in School-Aged Children with ADHD

    ERIC Educational Resources Information Center

    Faraone, Stephen V.; Wigal, Sharon B.; Hodgkins, Paul

    2007-01-01

    Objective: Compare observed and forecasted efficacy of mixed amphetamine salts extended release (MAS-XR; Adderall) with atomoxetine (Strattera) in ADHD children. Method: The authors analyze data from a randomized, double-blind, multicenter, parallel-group, forced-dose-escalation laboratory school study of children ages 6 to 12 with ADHD combined…

  3. Enhancing medicine price transparency through price information mechanisms

    PubMed Central

    2014-01-01

    Background Medicine price information mechanisms provide an essential tool to countries that seek a better understanding of product availability, market prices and price compositions of individual medicines. To be effective and contribute to cost savings, these mechanisms need to consider prices in their particular contexts when comparing between countries. This article discusses in what ways medicine price information mechanisms can contribute to increased price transparency and how this may affect access to medicines for developing countries. Methods We used data collected during the course of a WHO project focusing on the development of a vaccine price and procurement information mechanism. The project collected information from six medicine price information mechanisms and interviewed data managers and technical experts on key aspects as well as observed market effects of these mechanisms. The reviewed mechanisms were broken down into categories including objective and target audience, as well as the sources, types and volumes of data included. Information provided by the mechanisms was reviewed according to data available on medicine prices, product characteristics, and procurement modalities. Results We found indications of positive effects on access to medicines resulting from the utilization of the reviewed mechanisms. These include the uptake of higher quality medicines, more favorable results from contract negotiations, changes in national pricing policies, and the decrease of prices in certain segments for countries participating in or deriving data from the various mechanisms. Conclusion The reviewed mechanisms avoid the methodological challenges observed for medicine price comparisons that only use national price databases. They work with high quality data and display prices in the appropriate context of procurement modalities as well as the peculiarities of purchasing countries. Medicine price information mechanisms respond to the need for increased

  4. AQA - Air Quality model for Austria: comparison of ALADIN and ALARO forecasts with observed meteorological profiles and PM10 predictions with CAMx

    NASA Astrophysics Data System (ADS)

    Hirtl, M.; Krüger, B. C.; Kaiser, A.

    2009-09-01

    In AQA, Air Quality model for Austria, the regional weather forecast model ALADIN-Austria of the Central Institute for Meteorology and Geodynamics (ZAMG) is used in combination with the chemical transport model CAMx (www.camx.com) to conduct forecasts of gaseous and particulate air pollutants over Austria. The forecasts which are done in cooperation with the University of Natural Resources and Applied Life Sciences in Vienna (BOKU) are supported by the regional governments since 2005. In the current model version AQA uses the operational meteorological forecasts conducted with ALADIN which has a horizontal resolution of 9.7 km. Since 2008 the higher resolved ALARO is also available at the ZAMG. It has a horizontal resolution of 4.9 km and models the PBL with more vertical layers than ALADIN. ALARO also uses more complex algorithms to calculate precipitation, radiation and TKE. Another advantage of ALARO concerning the chemical modelling with CAMx is that additionally to the higher resolved meteorological forecasts it is possible to use finer emission inventories which are available for Austria. From 2006 to 2007 a SODAR-RASS of the ZAMG was operated in the north-eastern Austrian flat lands (Kittsee). In this study the measured vertical profiles of wind and temperature are compared with the model predictions. The evaluation is conducted for an episode in January 2007 when high PM10 concentrations were measured at the air quality station Kittsee. Analysis of the RASS-temperature-profiles show that during this episode a strong nocturnal inversion developed at the investigated area. The ability of the models ALADIN and ALARO to predict this complex meteorological condition is investigated. Both models are also used as meteorological driver for the chemical dispersion model CAMx and the results of predicted PM10 concentrations are compared to air quality measurements.

  5. Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and air quality forecast models

    NASA Astrophysics Data System (ADS)

    Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; Langel, T.; Williams, E. J.; Brown, S. S.

    2014-09-01

    Air quality forecast models typically predict large ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline Differential Optical Absorption Spectroscopy (DOAS) observations in southeastern Wisconsin, and as predicted by the National Air Quality Forecast System. From 2008-2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008-2010 measurements of ambient ozone conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI and Muskegon, MI up to 6 times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha with little dependence on position of the ferry or temperature but with highest differences during evening and night. Concurrent ozone forecast images from National Weather System's National Air Quality Forecast System in the upper Midwestern region surrounding Lake Michigan were saved over the ferry ozone sampling period in 2009. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. The model 1 and 8 h ozone mean biases were both 12 ppb higher than observed ozone, and maximum daily 1 h ozone mean bias was 10 ppb, indicating substantial ozone over-prediction over water. Trends in the bias with respect to location and time of day or month were also explored showing non-uniformity in model bias. Extreme ozone events were predicted by the model but not observed by ferry measurements.

  6. 22 CFR 518.45 - Cost and price analysis.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 22 Foreign Relations 2 2011-04-01 2009-04-01 true Cost and price analysis. 518.45 Section 518.45... Requirements Procurement Standards § 518.45 Cost and price analysis. Some form of cost or price analysis shall... analysis may be accomplished in various ways, including the comparison of price quotations...

  7. 49 CFR 19.45 - Cost and price analysis.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 49 Transportation 1 2013-10-01 2013-10-01 false Cost and price analysis. 19.45 Section 19.45... Requirements Procurement Standards § 19.45 Cost and price analysis. Some form of cost or price analysis shall... analysis may be accomplished in various ways, including the comparison of price quotations...

  8. 49 CFR 19.45 - Cost and price analysis.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 1 2011-10-01 2011-10-01 false Cost and price analysis. 19.45 Section 19.45... Requirements Procurement Standards § 19.45 Cost and price analysis. Some form of cost or price analysis shall... analysis may be accomplished in various ways, including the comparison of price quotations...

  9. Improved Anvil Forecasting

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred C.

    2000-01-01

    This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

  10. 1991 forecast: the year of restructuring.

    PubMed

    Bartlett, M

    1990-01-01

    How is the foodservice industry faring under the clouds of three big uncertainties--oil prices, recession and war? All things considered, its doing quite well. This annual status report of commercial and institutional business shows fast food, catering, nursing homes and employee feeding with growth percentages on the good, left side of the decimal point. Our forecast includes business trends to watch, food trends to guide menu planning and pricing, and interior- and kitchen-design trends that can be a blueprint for a successful new year.

  11. Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

    NASA Technical Reports Server (NTRS)

    Wang, Yao; Sridhar, Banavar

    2010-01-01

    intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

  12. How much are you prepared to PAY for a forecast?

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

    2015-04-01

    Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

  13. Reply to "Comment on 'Nonparametric forecasting of low-dimensional dynamical systems' ".

    PubMed

    Berry, Tyrus; Giannakis, Dimitrios; Harlim, John

    2016-03-01

    In this Reply we provide additional results which allow a better comparison of the diffusion forecast and the "past-noise" forecasting (PNF) approach for the El Niño index. We remark on some qualitative differences between the diffusion forecast and PNF, and we suggest an alternative use of the diffusion forecast for the purposes of forecasting the probabilities of extreme events. PMID:27078491

  14. Pricing Policies And Control of Tobacco in Europe (PPACTE) project: cross-national comparison of smoking prevalence in 18 European countries.

    PubMed

    Gallus, Silvano; Lugo, Alessandra; La Vecchia, Carlo; Boffetta, Paolo; Chaloupka, Frank J; Colombo, Paolo; Currie, Laura; Fernandez, Esteve; Fischbacher, Colin; Gilmore, Anna; Godfrey, Fiona; Joossens, Luk; Leon, Maria E; Levy, David T; Nguyen, Lien; Rosenqvist, Gunnar; Ross, Hana; Townsend, Joy; Clancy, Luke

    2014-05-01

    Limited data on smoking prevalence allowing valid between-country comparison are available in Europe. The aim of this study is to provide data on smoking prevalence and its determinants in 18 European countries. In 2010, within the Pricing Policies And Control of Tobacco in Europe (PPACTE) project, we conducted a face-to-face survey on smoking in 18 European countries (Albania, Austria, Bulgaria, Czech Republic, Croatia, England, Finland, France, Greece, Hungary, Ireland, Italy, Latvia, Poland, Portugal, Romania, Spain and Sweden) on a total of 18 056 participants, representative for each country of the population aged 15 years or older. Overall, 27.2% of the participants were current smokers (30.6% of men and 24.1% of women). Smoking prevalence was highest in Bulgaria (40.9%) and Greece (38.9%) and lowest in Italy (22.0%) and Sweden (16.3%). Smoking prevalence ranged between 15.7% (Sweden) and 44.3% (Bulgaria) for men and between 11.6% (Albania) and 38.1% (Ireland) for women. Multivariate analysis showed a significant inverse trend between smoking prevalence and the level of education in both sexes. Male-to-female smoking prevalence ratios ranged from 0.85 in Spain to 3.47 in Albania and current-to-ex prevalence ratios ranged from 0.68 in Sweden to 4.28 in Albania. There are considerable differences across Europe in smoking prevalence, and male-to-female and current-to-ex smoking prevalence ratios. Eastern European countries, lower income countries and those with less advanced tobacco control policies have less favourable smoking patterns and are at an earlier stage of the tobacco epidemic.

  15. 48 CFR 570.110 - Cost or pricing data and information other than cost or pricing data.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... competition. For price analysis of offered rental rates, the contracting officer may use a market survey, an... comparison, or other relevant market research data. For price analysis of offered tenant improvement...

  16. Load forecasting by ANN

    SciTech Connect

    Highley, D.D.; Hilmes, T.J. )

    1993-07-01

    This article discusses the use and training of artificial neural networks (ANNs) for load forecasting. The topics of the article include a brief overview of neural networks, interest in ANNs, training of neural networks, a case study in load forecasting, and the potential for using an artificial neural network to perform short-term load forecasting.

  17. Forecast `97

    SciTech Connect

    Williams, D.

    1996-12-01

    Many lawmakers and environmental professionals would probably like to leave memories of the last year behind them. It would be remembered as the year of daunted expectations -- the year politics derailed the business of the environment. The Republican-controlled Congress had just come roaring out of 1995, the ``revolutionary`` year, only to find itself stymied by a funding stalemate in the first half of 1996. The Clinton/Gore administration found itself labeled ineffectual on the environment by some critics, and intractable on it by others. Luckily, after staring into the budget abyss through the winter of 1995, the political combatants seem to have had a change of heart. Funding for the US Environmental Protection Agency (EPA) was approved with an almost genteel lack of confrontation. If for no other reason, 1997 should seem like a cake walk by comparison. Without many major casting changes after the November elections, the political drama surrounding the environment nonetheless will seem less like a tragedy. Perhaps the issue most emblematic of the problems facing the industry, and the 105th Congress, is Superfund reform. There are few laws as divisive as Superfund that are, at the same time, so critically important to the way an industry does business. Many of the stakeholders in the Superfund reauthorization process think this is the year something will actually get done.

  18. HI-CLASS on AEOS: a large-aperture laser radar for space surveillance/situational awareness investigations

    NASA Astrophysics Data System (ADS)

    Kovacs, Mark A.; Dryden, Gordon L.; Pohle, Richard H.; Ayers, Kirstie; Carreras, Richard A.; Crawford, Linda L.; Taft, Russell

    2001-12-01

    The Air Force Research Laboratory/Directed Energy Directorate (AFRL/DE) via the ALVA (Applications of Lidars for Vehicles with Analysis) program installed in late 2000 a wideband, 12 J 15 Hz CO2 laser radar (ladar) on the 3.67 meter aperture AEOS (Advanced Electro-Optics System) telescope. This system is part of the Maui Space Surveillance System (MSSS), on the summit of Haleakala, Maui, HI. This ladar adopts the technology successfully demonstrated by the first generation HI-CLASS (High Performance CO2) Ladar Surveillance Sensor) operating on the nearby 0.6 meter aperture Laser Beam Director (LBD) and developed under the Field Ladar Demonstration program, jointly sponsored by AFRL/DE and the Army's Space and Missile Defense Command. The moderate power (approximately 180 watts) HI-CLASS/AEOS system generates multiple, coherent waveforms for precision satellite tracking and characterization of space objects for 1 m2 targets at ranges out to 10,000 km. This system also will be used to track space objects smaller than30 cm at ranges to 2,000 km. A third application of this system is to provide data for developing satellite identification, characterization, health and status techniques. This paper will discuss the operating characteristics and innovative features of the new system. The paper will also review recent results in support of AF needs, demonstrations, experiments, as well as planned activities that directly support applications in the DoD, scientific, and commercial arenas.

  19. Novel methodology for pharmaceutical expenditure forecast

    PubMed Central

    Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and objective The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the ‘EU Pharmaceutical expenditure forecast’; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. Results This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and

  20. Short-Term Energy Outlook Model Documentation: Natural Gas Consumption and Prices

    EIA Publications

    2015-01-01

    The natural gas consumption and price modules of the Short-Term Energy Outlook (STEO) model are designed to provide consumption and end-use retail price forecasts for the residential, commercial, and industrial sectors in the nine Census districts and natural gas working inventories in three regions. Natural gas consumption shares and prices in each Census district are used to calculate an average U.S. retail price for each end-use sector.

  1. A Scenario Is A Projection Is A Forecast: And All Should Be Verified

    NASA Astrophysics Data System (ADS)

    Briggs, W. M.

    2014-12-01

    Bray and von Storch (2009) showed that there is considerable confusion among scientists in differentiating forecasts, projections, and scenarios, and that this confusion is echoed by the IPCC. These misunderstandings are not only found in making predictions, and in classifying which future-statements count as predictions, but also under which circumstances predictions must be verified. There is general recognition that good models produce good forecasts, but there is no escape from the implication that a bad forecast arises from a flawed model by claiming a forecast wasn't a forecast (or prediction) but a projection or scenario (see e.g. Risbey, 2014). We show forecasts, projections, and scenarios (when used prospectively) are equivalent, and that all face the same burden of verification. Any model M, statistical or physical, is a complex mixture of past data, time, and external evidence which specifies the model form. Forecasts f about some observable y are conditional on M and on a guess "x" about what the future holds. (Confusingly, sometimes x is called a "scenario" and sometimes the whole forecast is called a "scenario".) The simplest x is that the future comes in discrete time points, e.g. f(yt+1 |M, t+1...). Assuming its components are probative of y, x may be compound. E.g., suppose a climate model is built so that it is sensitive to oil price, thus x = "Price of oil > p and t+1". If at t+1 the price of oil was not <= p, then the forecast is null: no forecast has been made, because the conditions x were not met. At this point, some might call this forecast a "projection" and ignore its verification. But since this x is probative of y, the model also implies the forecast f(y | Price <= p, t+1), which should be (after-the-fact) computed and then verified. Examples where predictions which have "escaped" verification, as well as strategies of verification, will be given.

  2. Seasonal hydrological ensemble forecasts over Europe

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Wetterhall, Fredrik; Stephens, Elisabeth; Cloke, Hannah; Pappenberger, Florian

    2016-04-01

    This study investigates the limits of predictability in dynamical seasonal discharge forecasting, in both space and time, over Europe. Seasonal forecasts have an important socioeconomic value. Applications are numerous and cover hydropower management, spring flood prediction, low flow prediction for navigation and agricultural water demands. Additionally, the constant increase in NWP skill for longer lead times and the predicted increase in the intensity and frequency of hydro-meteorological extremes, have amplified the incentive to promote and further improve hydrological forecasts on sub-seasonal to seasonal timescales. In this study, seasonal hydrological forecasts (SEA), driven by the ECMWF's System 4 in hindcast mode, were analysed against an Ensemble Streamflow Prediction (ESP) benchmark. The ESP was forced with an ensemble of resampled historical meteorological observations and started with perfect initial conditions. Both forecasts were produced by the LISFLOOD model, run on the pan-European scale with a spatial resolution of 5 by 5 km. The forecasts were issued monthly on a daily time step, from 1990 until the current time, up to a lead time of 7 months. The seasonal discharge forecasts were analysed against the ESP on a catchment scale in terms of their accuracy, skill and sharpness, using a diverse set of verification metrics (e.g. KGE, CRPSS and ROC). Additionally, a reverse-ESP was constructed by forcing the LISFLOOD model with a single perfect meteorological set of observations and initiated from an ensemble of resampled historical initial conditions. The comparison of the ESP with the reverse-ESP approach enabled the identification of the respective contribution of meteorological forcings and hydrologic initial conditions errors to seasonal discharge forecasting uncertainties in Europe. These results could help pinpoint target elements of the forecasting chain which, after being improved, could lead to substantial increase in discharge predictability

  3. Accurate Weather Forecasting for Radio Astronomy

    NASA Astrophysics Data System (ADS)

    Maddalena, Ronald J.

    2010-01-01

    The NRAO Green Bank Telescope routinely observes at wavelengths from 3 mm to 1 m. As with all mm-wave telescopes, observing conditions depend upon the variable atmospheric water content. The site provides over 100 days/yr when opacities are low enough for good observing at 3 mm, but winds on the open-air structure reduce the time suitable for 3-mm observing where pointing is critical. Thus, to maximum productivity the observing wavelength needs to match weather conditions. For 6 years the telescope has used a dynamic scheduling system (recently upgraded; www.gb.nrao.edu/DSS) that requires accurate multi-day forecasts for winds and opacities. Since opacity forecasts are not provided by the National Weather Services (NWS), I have developed an automated system that takes available forecasts, derives forecasted opacities, and deploys the results on the web in user-friendly graphical overviews (www.gb.nrao.edu/ rmaddale/Weather). The system relies on the "North American Mesoscale" models, which are updated by the NWS every 6 hrs, have a 12 km horizontal resolution, 1 hr temporal resolution, run to 84 hrs, and have 60 vertical layers that extend to 20 km. Each forecast consists of a time series of ground conditions, cloud coverage, etc, and, most importantly, temperature, pressure, humidity as a function of height. I use the Liebe's MWP model (Radio Science, 20, 1069, 1985) to determine the absorption in each layer for each hour for 30 observing wavelengths. Radiative transfer provides, for each hour and wavelength, the total opacity and the radio brightness of the atmosphere, which contributes substantially at some wavelengths to Tsys and the observational noise. Comparisons of measured and forecasted Tsys at 22.2 and 44 GHz imply that the forecasted opacities are good to about 0.01 Nepers, which is sufficient for forecasting and accurate calibration. Reliability is high out to 2 days and degrades slowly for longer-range forecasts.

  4. Forecaster priorities for improving probabilistic flood forecasts

    NASA Astrophysics Data System (ADS)

    Wetterhall, Fredrik; Pappenberger, Florian; Alfieri, Lorenzo; Cloke, Hannah; Thielen, Jutta

    2014-05-01

    Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

  5. Weather forecasting expert system study

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

  6. Weather assessment and forecasting

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

  7. Advanced chaos forecasting

    NASA Astrophysics Data System (ADS)

    Doerner, R.; Hübinger, B.; Martienssen, W.

    1994-07-01

    The exponential separation of initially adjacent trajectories restricts the predictability of deterministic chaotic motions. The predictability depends on the initial state from where the trajectory starts that shall be forecasted. By calculating the predictability simultaneously with the forecast, we are able to reject forecasts with low reliability immediately, thereby decreasing drastically the average forecast error. We test this scheme experimentally on Chua's circuit [Komuro, Tokunaga, Matsumoto, Chua, and Hotta, Int. J. Bifurc. Chaos 1, 139 (1991)], basing all calculations only on a time series of a single scalar variable.

  8. Some Evidence on the Importance of Sticky Prices.

    ERIC Educational Resources Information Center

    Bils, Mark; Klenow, Peter J.

    2004-01-01

    We examine the frequency of price changes for 350 categories of goods and services covering about 70 percent of consumer spending, on the basis of unpublished data from the Bureau of Labor Statistics for 1995-97. In comparison with previous studies, we find much more frequent price changes, with haft of prices lasting less than 4.3 months. Even…

  9. An Ensemble Approach for Forecasting Net Interchange Schedule

    SciTech Connect

    Vlachopoulou, Maria; Gosink, Luke J.; Pulsipher, Trenton C.; Ferryman, Thomas A.; Zhou, Ning; Tong, Jianzhong

    2013-09-01

    The net interchange schedule (NIS) is the sum of the transactions (MW) between an ISO/RTO and its neighbors. Effective forecasting of the submitted NIS can improve grid operation efficiency. This paper applies a Bayesian model averaging (BMA) technique to forecast submitted NIS. As an ensemble approach, the BMA method aggregates different forecasting models in order to improve forecasting accuracy and consistency. In this study, the BMA method is compared to two alternative approaches: a stepwise regression method and an artificial neural network (ANN) trained for NIS forecasting. In our comparative analysis, we use field measurement data from the Pennsylvania, New Jersey, and Maryland (PJM) Regional Transmission Organization (RTO) to train and test each method. Our preliminary results indicate that ensemble-based methods can provide more accurate and consistent NIS forecasts in comparison to non-ensemble alternate methods.

  10. Aviation Forecasting in ICAO

    NASA Technical Reports Server (NTRS)

    Mcmahon, J.

    1972-01-01

    Opinions or plans of qualified experts in the field are used for forecasting future requirements for air navigational facilities and services of international civil aviation. ICAO periodically collects information from Stators and operates on anticipated future operations, consolidates this information, and forecasts the future level of activity at different airports.

  11. The Forecast Interpretation Tool-a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

    USGS Publications Warehouse

    Husak, G.J.; Michaelsen, J.; Kyriakidis, P.; Verdin, J.P.; Funk, C.; Galu, G.

    2011-01-01

    Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique. Copyright ?? 2010 Royal Meteorological Society.

  12. Managing price, gaining profit.

    PubMed

    Marn, M V; Rosiello, R L

    1992-01-01

    The fastest and most effective way for a company to realize maximum profit is to get its pricing right. The right price can boost profit faster than increasing volume will; the wrong price can shrink it just as quickly. Yet many otherwise tough-minded managers miss out on significant profits because they shy away from pricing decisions for fear that they will alienate their customers. Worse, if management isn't controlling its pricing policies, there's a good chance that the company's clients are manipulating them to their own advantage. McKinsey & Company's Michael Marn and Robert Rosiello show managers how to gain control of the pricing puzzle and capture untapped profit potential by using two basic concepts: the pocket price waterfall and the pocket price band. The pocket price waterfall reveals how price erodes between a company's invoice figure and the actual amount paid by the customer--the transaction price. It tracks the volume purchase discounts, early payment bonuses, and frequent customer incentives that squeeze a company's profits. The pocket price band plots the range of pocket prices over which any given unit volume of a single product sells. Wide price bands are commonplace: some manufacturers' transaction prices for a given product range 60%; one fastener supplier's price band ranged up to 500%. Managers who study their pocket price waterfalls and bands can identify unnecessary discounting at the transaction level, low-performance accounts, and misplaced marketing efforts. The problems, once identified, are typically easy and inexpensive to remedy. PMID:10121318

  13. Managing price, gaining profit.

    PubMed

    Marn, M V; Rosiello, R L

    1992-01-01

    The fastest and most effective way for a company to realize maximum profit is to get its pricing right. The right price can boost profit faster than increasing volume will; the wrong price can shrink it just as quickly. Yet many otherwise tough-minded managers miss out on significant profits because they shy away from pricing decisions for fear that they will alienate their customers. Worse, if management isn't controlling its pricing policies, there's a good chance that the company's clients are manipulating them to their own advantage. McKinsey & Company's Michael Marn and Robert Rosiello show managers how to gain control of the pricing puzzle and capture untapped profit potential by using two basic concepts: the pocket price waterfall and the pocket price band. The pocket price waterfall reveals how price erodes between a company's invoice figure and the actual amount paid by the customer--the transaction price. It tracks the volume purchase discounts, early payment bonuses, and frequent customer incentives that squeeze a company's profits. The pocket price band plots the range of pocket prices over which any given unit volume of a single product sells. Wide price bands are commonplace: some manufacturers' transaction prices for a given product range 60%; one fastener supplier's price band ranged up to 500%. Managers who study their pocket price waterfalls and bands can identify unnecessary discounting at the transaction level, low-performance accounts, and misplaced marketing efforts. The problems, once identified, are typically easy and inexpensive to remedy.

  14. A quality assessment of the MARS crop yield forecasting system for the European Union

    NASA Astrophysics Data System (ADS)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  15. Probabilities of Possible Future Prices (Released in the STEO April 2010)

    EIA Publications

    2010-01-01

    The Energy Information Administration introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts.

  16. [The sea-chests of the Dutch East India Company according to the price list of 1739 (a comparison with the French list)].

    PubMed

    Romieux, Y

    1993-01-01

    The medical chests on the vessel "The Amsterdam" of the Dutch East India Company, lost at sea on January 9, 1749, were controlled by a price list of 1739. They were made up by the apothecary of the arsenal of the Company in Amsterdam, and comprised 156 medications divided into 17 classes according to a mixed classification system, that is, galenical, botanical, chemical and even, occasionally, pharmacological. At the same period, for a number of crew members of clearly lesser status, the chests of the French East India Company contained 233 medical products divided into 13 galenical classes.

  17. Characterizing limit order prices

    NASA Astrophysics Data System (ADS)

    Withanawasam, R. M.; Whigham, P. A.; Crack, Timothy Falcon

    2013-11-01

    A computational model of a limit order book is used to study the effect of different limit order distribution offsets. Reference prices such as same side/contra side best market prices and last traded price are considered in combination with different price offset distributions. We show that when characterizing limit order prices, varying the offset distribution only produces different behavior when the reference price is the contra side best price. Irrespective of the underlying mechanisms used in computing the limit order prices, the shape of the price graph and the behavior of the average order book profile distribution are strikingly similar in all the considered reference prices/offset distributions. This implies that existing averaging methods can cancel variabilities in limit order book shape/attributes and may be misleading.

  18. Time series ARIMA models for daily price of palm oil

    NASA Astrophysics Data System (ADS)

    Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu

    2015-02-01

    Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.

  19. Statistical evaluation of forecasts

    NASA Astrophysics Data System (ADS)

    Mader, Malenka; Mader, Wolfgang; Gluckman, Bruce J.; Timmer, Jens; Schelter, Björn

    2014-08-01

    Reliable forecasts of extreme but rare events, such as earthquakes, financial crashes, and epileptic seizures, would render interventions and precautions possible. Therefore, forecasting methods have been developed which intend to raise an alarm if an extreme event is about to occur. In order to statistically validate the performance of a prediction system, it must be compared to the performance of a random predictor, which raises alarms independent of the events. Such a random predictor can be obtained by bootstrapping or analytically. We propose an analytic statistical framework which, in contrast to conventional methods, allows for validating independently the sensitivity and specificity of a forecasting method. Moreover, our method accounts for the periods during which an event has to remain absent or occur after a respective forecast.

  20. A model for Long-term Industrial Energy Forecasting (LIEF)

    SciTech Connect

    Ross, M. Michigan Univ., Ann Arbor, MI . Dept. of Physics Argonne National Lab., IL . Environmental Assessment and Information Sciences Div.); Hwang, R. )

    1992-02-01

    The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

  1. A model for Long-term Industrial Energy Forecasting (LIEF)

    SciTech Connect

    Ross, M. ||; Hwang, R.

    1992-02-01

    The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

  2. Probabilistic river forecast methodology

    NASA Astrophysics Data System (ADS)

    Kelly, Karen Suzanne

    1997-09-01

    The National Weather Service (NWS) operates deterministic conceptual models to predict the hydrologic response of a river basin to precipitation. The output from these models are forecasted hydrographs (time series of the future river stage) at certain locations along a river. In order for the forecasts to be useful for optimal decision making, the uncertainty associated with them must be quantified. A methodology is developed for this purpose that (i) can be implemented with any deterministic hydrologic model, (ii) receives a probabilistic forecast of precipitation as input, (iii) quantifies all sources of uncertainty, (iv) operates in real-time and within computing constraints, and (v) produces probability distributions of future river stages. The Bayesian theory which supports the methodology involves transformation of a distribution of future precipitation into one of future river stage, and statistical characterization of the uncertainty in the hydrologic model. This is accomplished by decomposing total uncertainty into that associated with future precipitation and that associated with the hydrologic transformations. These are processed independently and then integrated into a predictive distribution which constitutes a probabilistic river stage forecast. A variety of models are presented for implementation of the methodology. In the most general model, a probability of exceedance associated with a given future hydrograph specified. In the simplest model, a probability of exceedance associated with a given future river stage is specified. In conjunction with the Ohio River Forecast Center of the NWS, the simplest model is used to demonstrate the feasibility of producing probabilistic river stage forecasts for a river basin located in headwaters. Previous efforts to quantify uncertainty in river forecasting have only considered selected sources of uncertainty, been specific to a particular hydrologic model, or have not obtained an entire probability

  3. Stable prices to fuel gas demand growth - GRI

    SciTech Connect

    O`Driscoll, M.

    1994-08-18

    The Gas Research Institute projects a significant rise in demand for natural gas over the next 16 years, but without new technology, consumption growth cannot be sustained. The record projected increase in gas consumption is due to low prices. In the overall energy market, fewer incentives for energy conservation exist. This article briefly review energy supplies, energy consumption and energy forecasts for the future.

  4. Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000

    EIA Publications

    1999-01-01

    Phase 2 of the U.S. reformulated gasoline program begins at the end of this year. This article, published in the Petroleum Supply Monthly, April 1999, provides a forecast and analysis of the demand and price for Phase 2 reformulated gasoline for the year 2000.

  5. Modelling world gold prices and USD foreign exchange relationship using multivariate GARCH model

    NASA Astrophysics Data System (ADS)

    Ping, Pung Yean; Ahmad, Maizah Hura Binti

    2014-12-01

    World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.

  6. A stochastic delay model for pricing debt and equity: Numerical techniques and applications

    NASA Astrophysics Data System (ADS)

    Tambue, Antoine; Kemajou Brown, Elisabeth; Mohammed, Salah

    2015-01-01

    Delayed nonlinear models for pricing corporate liabilities and European options were recently developed. Using self-financed strategy and duplication we were able to derive a Random Partial Differential Equation (RPDE) whose solutions describe the evolution of debt and equity values of a corporate in the last delay period interval in the accompanied paper (Kemajou et al., 2012) [14]. In this paper, we provide robust numerical techniques to solve the delayed nonlinear model for the corporate value, along with the corresponding RPDEs modeling the debt and equity values of the corporate. Using financial data from some firms, we forecast and compare numerical solutions from both the nonlinear delayed model and classical Merton model with the real corporate data. From this comparison, it comes up that in corporate finance the past dependence of the firm value process may be an important feature and therefore should not be ignored.

  7. An overview of health forecasting.

    PubMed

    Soyiri, Ireneous N; Reidpath, Daniel D

    2013-01-01

    Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.

  8. State prescription drug price Web sites: how useful to consumers?

    PubMed

    Tu, Ha T; Corey, Catherine G

    2008-02-01

    To aid consumers in comparing prescription drug costs, many states have launched Web sites to publish drug prices offered by local retail pharmacies. The current push to make retail pharmacy prices accessible to consumers is part of a much broader movement to increase price transparency throughout the health-care sector. Efforts to encourage price-based shopping for hospital and physician services have encountered widespread concerns, both on grounds that prices for complex services are difficult to measure and compare accurately and that quality varies substantially across providers. Experts agree, however, that prescription drugs are much easier to shop for than other, more complex health services. However, extensive gaps in available price information--the result of relying on Medicaid data--seriously hamper the effectiveness of state drug price-comparison Web sites, according to a new study by the Center for Studying Health System Change (HSC). An alternative approach--requiring pharmacies to submit price lists to the states--would improve the usefulness of price information, but pharmacies typically oppose such a mandate. Another limitation of most state Web sites is that price information is restricted to local pharmacies, when online pharmacies, both U.S. and foreign, often sell prescription drugs at substantially lower prices. To further enhance consumer shopping tools, states might consider expanding the types of information provided, including online pharmacy comparison tools, lists of deeply discounted generic drugs offered by discount retailers, and lists of local pharmacies offering price matches. PMID:18494180

  9. A channel dynamics model for real-time flood forecasting

    USGS Publications Warehouse

    Hoos, A.B.; Koussis, A.D.; Beale, G.O.

    1989-01-01

    A new channel dynamics scheme ASPIRE (alternative system predictor in real time), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio. -Authors

  10. Essays on oil price volatility and irreversible investment

    NASA Astrophysics Data System (ADS)

    Pastor, Daniel J.

    In chapter 1, we provide an extensive and systematic evaluation of the relative forecasting performance of several models for the volatility of daily spot crude oil prices. Empirical research over the past decades has uncovered significant gains in forecasting performance of Markov Switching GARCH models over GARCH models for the volatility of financial assets and crude oil futures. We find that, for spot oil price returns, non-switching models perform better in the short run, whereas switching models tend to do better at longer horizons. In chapter 2, I investigate the impact of volatility on firms' irreversible investment decisions using real options theory. Cost incurred in oil drilling is considered sunk cost, thus irreversible. I collect detailed data on onshore, development oil well drilling on the North Slope of Alaska from 2003 to 2014. Volatility is modeled by constructing GARCH, EGARCH, and GJR-GARCH forecasts based on monthly real oil prices, and realized volatility from 5-minute intraday returns of oil futures prices. Using a duration model, I show that oil price volatility generally has a negative relationship with the hazard rate of drilling an oil well both when aggregating all the fields, and in individual fields.

  11. Field observations of vertical temperature/humidity structure in the Cerdanya Basin -Spanish Pyrenees: Preliminary results and comparison with model forecasts

    NASA Astrophysics Data System (ADS)

    Miró, Josep Ramon; Pepin, Nick

    2016-04-01

    The Cerdanya basin is located in the north-eastern Pyrenees and measures 15 km wide and 40 km long. It is unique in that its north-east to south-west orientation contrasts with most other Pyrenean valleys which run north-south. The upper portion has its valley bottom averaging around 1000 m asl, with the surrounding mountain ranges rising to well over 2000 m asl. To the west (downstream) the Segre flows into a narrow gorge which provides a constriction for any down-valley flow. This topography encourages intense temperature inversions through cold air ponding, decoupling the valley atmosphere from the regional circulation, especially in winter. Prediction of minimum temperatures is a challenge. A network of 40 temperature sensors was installed in 2012 to collect hourly temperatures throughout the cold pool. A transect was also installed in Conflent to the north-east as a comparison, since previous research has shown that the vertical temperature and humidity profiles are less influenced by cold air drainage in this valley system. The sensor data is validated against AWS observations at two contrasting locations. Using two years of data (2012-2014), through calculation of hourly lapse rates in various elevation bands we show frequent inversions developing up to 1450 m, and sometimes extending much higher than this, concentrating in winter. Accumulated potential temperature deficit is shown to be much higher in Cerdanya than in Conflent, and increases in the lower atmospheric layers. Case studies of two intense episodes in December 2012 and January 2013 show that model simulations, despite being able to simulate broad mechanisms of the CAP formation and thermal winds, underestimate the amount of cooling, particularly in incised valley locations.

  12. Voluntary Green Power Market Forecast through 2015

    SciTech Connect

    Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

    2010-05-01

    Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

  13. 18 CFR Appendix A 1 to Part 281 - Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976...

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 423.5 182.8 210.4 202.7 297.0 417.7 Coal: All Grades 84.8 94.7 111.6 122.4 128.7 (3) (3) (3) (3) (3) Natural Gas 103.4 130.0 143.8 175.4 194.8 97.2 131.9 154.1 201.8 237.3 Actual price difference (fuel oil....1 42.9 89.3 166.6 68.7 66.3 32.0 59.7 112.3 All No. 6 92.5 90.4 68.5 124.3 228.7 85.6 78.5 48.6...

  14. Why are product prices in online markets not converging?

    PubMed

    Mizuno, Takayuki; Watanabe, Tsutomu

    2013-01-01

    Why are product prices in online markets dispersed in spite of very small search costs? To address this question, we construct a unique dataset from a Japanese price comparison site, which records price quotes offered by e-retailers as well as customers' clicks on products, which occur when they proceed to purchase the product. The novelty of our approach is that we seek to extract useful information on the source of price dispersion from the shape of price distributions rather than focusing merely on the standard deviation or the coefficient of variation of prices, as previous studies have done. We find that the distribution of prices retailers quote for a particular product at a particular point in time (divided by the lowest price) follows an exponential distribution, showing the presence of substantial price dispersion. For example, 20 percent of all retailers quote prices that are more than 50 percent higher than the lowest price. Next, comparing the probability that customers click on a retailer with a particular rank and the probability that retailers post prices at a particular rank, we show that both decline exponentially with price rank and that the exponents associated with the probabilities are quite close. This suggests that the reason why some retailers set prices at a level substantially higher than the lowest price is that they know that some customers will choose them even at that high price. Based on these findings, we hypothesize that price dispersion in online markets stems from heterogeneity in customers' preferences over retailers; that is, customers choose a set of candidate retailers based on their preferences, which are heterogeneous across customers, and then pick a particular retailer among the candidates based on the price ranking.

  15. Why Are Product Prices in Online Markets Not Converging?

    PubMed Central

    Mizuno, Takayuki; Watanabe, Tsutomu

    2013-01-01

    Why are product prices in online markets dispersed in spite of very small search costs? To address this question, we construct a unique dataset from a Japanese price comparison site, which records price quotes offered by e-retailers as well as customers’ clicks on products, which occur when they proceed to purchase the product. The novelty of our approach is that we seek to extract useful information on the source of price dispersion from the shape of price distributions rather than focusing merely on the standard deviation or the coefficient of variation of prices, as previous studies have done. We find that the distribution of prices retailers quote for a particular product at a particular point in time (divided by the lowest price) follows an exponential distribution, showing the presence of substantial price dispersion. For example, 20 percent of all retailers quote prices that are more than 50 percent higher than the lowest price. Next, comparing the probability that customers click on a retailer with a particular rank and the probability that retailers post prices at a particular rank, we show that both decline exponentially with price rank and that the exponents associated with the probabilities are quite close. This suggests that the reason why some retailers set prices at a level substantially higher than the lowest price is that they know that some customers will choose them even at that high price. Based on these findings, we hypothesize that price dispersion in online markets stems from heterogeneity in customers’ preferences over retailers; that is, customers choose a set of candidate retailers based on their preferences, which are heterogeneous across customers, and then pick a particular retailer among the candidates based on the price ranking. PMID:24015219

  16. Integrating Hydrometeorological Information for Precipitation and Streamflow Forecasting Using Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Chiang, Y.; Chang, F.

    2008-12-01

    The major purpose of this study is to effectively construct artificial neural networks-based multistep ahead flood forecasting using hydrometeorological and numerical weather prediction (NWP) information. To achieve this goal, we first compare three mean areal precipitation forecasts: radar/NWP multisource-derived forecasts (Pr), NWP precipitation forecasts (Pn), and improved precipitation forecasts (Pm) by merging Pr and Pn. The analysis shows that the accuracy of Pm is higher than that of Pr and Pn. The analysis also indicates that the NWP precipitation forecasts do provide relative effectiveness to the merging procedure, particularly for forecast lead time of 4-6 h. In sum, the merged products performed well and captured the main tendency of rainfall pattern. Subsequently, a recurrent neural network (RNN)-based multistep ahead flood forecasting techniques is produced by feeding with the merged precipitation. The evaluation of 1-6 h flood forecasting schemes strongly shows that the proposed hydrological model provides accurate and stable flood forecasts in comparison with conventional case and significantly improves the peak flow forecasts and the time-lag problem. An important finding is the hydrologic model responses seem not sensitive to precipitation predictions in lead times of 1-3 h, whereas the runoff forecasts are highly dependent on predicted precipitation information for longer lead times (4-6 h). Overall, the results demonstrate that accurate and consistent multistep ahead flood forecasting can be obtained by integrating predicted precipitation information into ANNs modeling.

  17. Higher Education Prices and Price Indexes.

    ERIC Educational Resources Information Center

    Halstead, D. Kent

    The purpose of this study and its succeeding editions is to report higher education price information on a continuing basis until a more formal effort in this direction is initiated by the federal government or by interested private organizations. Consideration is given to the uses and limitations of price indexes, expenditure grouping for pricing…

  18. Future Economics of Liver Transplantation: A 20-Year Cost Modeling Forecast and the Prospect of Bioengineering Autologous Liver Grafts.

    PubMed

    Habka, Dany; Mann, David; Landes, Ronald; Soto-Gutierrez, Alejandro

    2015-01-01

    During the past 20 years liver transplantation has become the definitive treatment for most severe types of liver failure and hepatocellular carcinoma, in both children and adults. In the U.S., roughly 16,000 individuals are on the liver transplant waiting list. Only 38% of them will receive a transplant due to the organ shortage. This paper explores another option: bioengineering an autologous liver graft. We developed a 20-year model projecting future demand for liver transplants, along with costs based on current technology. We compared these cost projections against projected costs to bioengineer autologous liver grafts. The model was divided into: 1) the epidemiology model forecasting the number of wait-listed patients, operated patients and postoperative patients; and 2) the treatment model forecasting costs (pre-transplant-related costs; transplant (admission)-related costs; and 10-year post-transplant-related costs) during the simulation period. The patient population was categorized using the Model for End-Stage Liver Disease score. The number of patients on the waiting list was projected to increase 23% over 20 years while the weighted average treatment costs in the pre-liver transplantation phase were forecast to increase 83% in Year 20. Projected demand for livers will increase 10% in 10 years and 23% in 20 years. Total costs of liver transplantation are forecast to increase 33% in 10 years and 81% in 20 years. By comparison, the projected cost to bioengineer autologous liver grafts is $9.7M based on current catalog prices for iPS-derived liver cells. The model projects a persistent increase in need and cost of donor livers over the next 20 years that's constrained by a limited supply of donor livers. The number of patients who die while on the waiting list will reflect this ever-growing disparity. Currently, bioengineering autologous liver grafts is cost prohibitive. However, costs will decline rapidly with the introduction of new manufacturing

  19. Forecasters of earthquakes

    NASA Astrophysics Data System (ADS)

    Maximova, Lyudmila

    1987-07-01

    For the first time Soviet scientists have set up a bioseismological proving ground which will stage a systematic extensive experiment of using birds, ants, mountain rodents including marmots, which can dig holes in the Earth's interior to a depth of 50 meters, for the purpose of earthquake forecasting. Biologists have accumulated extensive experimental data on the impact of various electromagnetic fields, including fields of weak intensity, on living organisms. As far as mammals are concerned, electromagnetic waves with frequencies close to the brain's biorhythms have the strongest effect. How these observations can be used to forecast earthquakes is discussed.

  20. US industrial battery forecast

    SciTech Connect

    Hollingsworth, V. III

    1996-09-01

    Last year was strong year for the US industrial battery market with growth in all segments. Sales of industrial batteries in North America grew 19.2% in 1995, exceeding last year`s forecasted growth rate of 11.6%. The results of the recently completed BCI Membership Survey forecast 1996 sales to be up 10.5%, and to continue to increase at a 10.4% compound annual rate through the year 2000. This year`s survey includes further detail on the stationary battery market with the inclusion of less than 25 Ampere-Hour batteries for the first time.

  1. Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)

    SciTech Connect

    Not Available

    1985-07-01

    The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.

  2. Simulating Price-Taking

    ERIC Educational Resources Information Center

    Engelhardt, Lucas M.

    2015-01-01

    In this article, the author presents a price-takers' market simulation geared toward principles-level students. This simulation demonstrates that price-taking behavior is a natural result of the conditions that create perfect competition. In trials, there is a significant degree of price convergence in just three or four rounds. Students find this…

  3. Price Estimation Guidelines

    NASA Technical Reports Server (NTRS)

    Chamberlain, R. G.; Aster, R. W.; Firnett, P. J.; Miller, M. A.

    1985-01-01

    Improved Price Estimation Guidelines, IPEG4, program provides comparatively simple, yet relatively accurate estimate of price of manufactured product. IPEG4 processes user supplied input data to determine estimate of price per unit of production. Input data include equipment cost, space required, labor cost, materials and supplies cost, utility expenses, and production volume on industry wide or process wide basis.

  4. An emergency response and local weather forecasting software system

    SciTech Connect

    Tremback, C.J.; Lyons, W.A.; Thorson, W.P.; Walko, R.L.

    1994-12-31

    Recent advances in computer technology have now placed supercomputer power on the desktop for a small fraction of the price. Many traditional supercomputer applications have benefited greatly in the move from the realm of the supercomputer center to more direct local control of the end user. Two of the atmospheric applications that have and will continue to benefit greatly from these advances in computer technology is in the arenas of local weather forecasting and emergency response systems.

  5. 18 CFR Appendix A 1 to Part 281 - Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976...

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Comparison of Selected... Part 281 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF... 1978 1979 January 1980 Cents per MMBtu Fuel Oil: No. 2 235.1 264.3 271.9 402.1 564.4 226.4 257.3...

  6. Forecasts covering one month using a cut cell model

    NASA Astrophysics Data System (ADS)

    Steppeler, J.; Park, S.-H.; Dobler, A.

    2013-01-01

    This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by 6 forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell

  7. Forecasts covering one month using a cut-cell model

    NASA Astrophysics Data System (ADS)

    Steppeler, J.; Park, S.-H.; Dobler, A.

    2013-07-01

    This paper investigates the impact and potential use of the cut-cell vertical discretisation for forecasts covering five days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 with six forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut-cell model LMZ (Lokal Modell with z-coordinates) provides a much more accurate representation of mountains on model forecasts than the terrain-following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalayas, over southeastern China, Korea and Japan. The LMZ has previously been tested extensively for one-day forecasts on a European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut-cell discretisation on forecast quality. The cut-cell model is available only for an older (2003) version of the model LM (Lokal Modell). It was compared using a control model differing by the use of the terrain-following coordinate only. The cut-cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved, more transferable version of the terrain-following model LM has been developed since then under the name CLM (Climate version of the Lokal Modell). The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of the cut-cell model were compared also to the CLM. As the cut-cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalayas, the cut-cell model considerably

  8. Forecasting Credit Hours.

    ERIC Educational Resources Information Center

    Bivin, David; Rooney, Patrick Michael

    1999-01-01

    This study used Tobit analysis to estimate retention probabilities and credit hours at two universities. Tobit was judged as appropriate for this problem because it recognizes the lower bound of zero on credit hours and incorporates this bound into parameter estimates and forecasts. Models are estimated for credit hours in a single year and…

  9. Education Planning: Pupil Forecasting.

    ERIC Educational Resources Information Center

    Royal Inst. of Public Administration, Reading (England). Local Government Operational Research Unit.

    This computer-based system of enrollment projection predicts up to seven years ahead the number of school children of each age and sex who will be in school. The main distinguishing feature of the system is the ability to detect well in advance small changes in the geographical distribution of children. Forecasts are made for zones that will yield…

  10. Federal Forecasters Directory, 1995.

    ERIC Educational Resources Information Center

    National Center for Education Statistics (ED), Washington, DC.

    This directory lists employees of the federal government who are involved in forecasting for policy formation and trend prediction purposes. Job title, agency, business address, phone or e-mail number, and specialty areas are listed for each employee. Employees are listed for the following agencies: (1) Bureau of the Census; (2) Bureau of Economic…

  11. External Environmental Forecast.

    ERIC Educational Resources Information Center

    Lapin, Joel D.

    Representing current viewpoints of academics, futures experts, and social observers, this external environmental forecast presents projections and information of particular relevance to the future of Catonsville Community College. The following topics are examined: (1) population changes and implications for higher education; (2) state and local…

  12. Not as bad as you think: a comparison of the nutrient content of best price and brand name food products in Switzerland.

    PubMed

    Khalatbari-Soltani, Saman; Marques-Vidal, Pedro

    2016-06-01

    Several studies have shown that low-cost foods have an equivalent nutrient composition compared to high-cost foods, but such information is lacking in Switzerland. Thus, we compared the caloric and nutrient content of "best price" (BPF) and brand name foods (BNF) in Switzerland using the version 5.0 (April 2015) of the Swiss Food and Nutrient composition database. Over 4000 processed food items were included and 26 food categories were compared regarding total energy, protein, fat and carbohydrates, saturated fatty acids, sugar, fiber and sodium. BPF, namely core food categories like Bread, Red meat, White meat and Fish products, were 42%, 39%, 42% and 46% less expensive than their BNF equivalents, respectively. No differences were found between BPF and BNF regarding total energy and protein, fat and carbohydrates for most food categories. In the Cheese category, BPF had a lower caloric content than BNF [Median (interquartile range, IQR): 307 (249-355) vs. 365 (308-395) kcal/100 g, respectively, p < 0.001]; BPF also had lower fat and saturated fatty acid content but higher carbohydrate content than BNF (both p < 0.01). In the Creams and puddings group, BPF had lower fat 1.3 (0.9-1.7) vs. 6.0 (3.5-11.0) g/100 g and saturated fatty acid 0.6 (0.6-0.8) vs. 2.9 (2.3-6.0) g/100 g content than BNF (both p < 0.005). In the Tinned fruits and vegetables group, BPF had lower sodium content than BNF: 175 (0-330) vs. 370 (150-600) mg/100 g, p = 0.006. BPF might be a reasonable and eventually healthier alternative of BNF for economically deprived people in Switzerland.

  13. Not as bad as you think: a comparison of the nutrient content of best price and brand name food products in Switzerland.

    PubMed

    Khalatbari-Soltani, Saman; Marques-Vidal, Pedro

    2016-06-01

    Several studies have shown that low-cost foods have an equivalent nutrient composition compared to high-cost foods, but such information is lacking in Switzerland. Thus, we compared the caloric and nutrient content of "best price" (BPF) and brand name foods (BNF) in Switzerland using the version 5.0 (April 2015) of the Swiss Food and Nutrient composition database. Over 4000 processed food items were included and 26 food categories were compared regarding total energy, protein, fat and carbohydrates, saturated fatty acids, sugar, fiber and sodium. BPF, namely core food categories like Bread, Red meat, White meat and Fish products, were 42%, 39%, 42% and 46% less expensive than their BNF equivalents, respectively. No differences were found between BPF and BNF regarding total energy and protein, fat and carbohydrates for most food categories. In the Cheese category, BPF had a lower caloric content than BNF [Median (interquartile range, IQR): 307 (249-355) vs. 365 (308-395) kcal/100 g, respectively, p < 0.001]; BPF also had lower fat and saturated fatty acid content but higher carbohydrate content than BNF (both p < 0.01). In the Creams and puddings group, BPF had lower fat 1.3 (0.9-1.7) vs. 6.0 (3.5-11.0) g/100 g and saturated fatty acid 0.6 (0.6-0.8) vs. 2.9 (2.3-6.0) g/100 g content than BNF (both p < 0.005). In the Tinned fruits and vegetables group, BPF had lower sodium content than BNF: 175 (0-330) vs. 370 (150-600) mg/100 g, p = 0.006. BPF might be a reasonable and eventually healthier alternative of BNF for economically deprived people in Switzerland. PMID:27419018

  14. Evolving forecasting classifications and applications in health forecasting

    PubMed Central

    Soyiri, Ireneous N; Reidpath, Daniel D

    2012-01-01

    Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation. PMID:22615533

  15. Price differentiation and transparency in the global pharmaceutical marketplace.

    PubMed

    Ridley, David B

    2005-01-01

    Pharmaceutical manufacturers have increased the availability of their products and sometimes increased their own financial returns by charging lower prices outside of the US and by discounting to lower-income patients in the US. Examples include discounted HIV-AIDS drugs in developing countries and pharmaceutical manufacturers' discount cards in the US. Representatives of some international organisations argue that the price reductions are insufficient to make the medications widely available to lower-income patients. The WHO advocates both differential pricing and price transparency. While its efforts are well meaning, this paper identifies six concerns about its methods of comparing the price of a given molecule across manufacturers and across countries. More significantly, the WHO efforts to increase transparency are likely to lead to less price differentiation and less access to innovative pharmaceuticals. An important reason why manufacturers are reluctant to charge lower prices in lower-income countries is that they fear that such low prices will undermine the prices they charge to higher-income consumers. International organisations should not facilitate transparency but should dissuade governments from making price comparisons and basing their prices on those of lower-income countries. Furthermore, they should endeavour to keep low-priced and free drugs in the hands of the low-income consumers for which they were intended.

  16. Calculating proper transfer prices

    SciTech Connect

    Dorkey, F.C. ); Jarrell, G.A. )

    1991-01-01

    This article deals with developing a proper transfer pricing method. Decentralization is as American as baseball. While managers laud the widespread benefits of both decentralization and baseball, they often greet the term transfer price policy with a yawn. Since transfer prices are as critical to the success of decentralized firms as good pitchers are to baseball teams, this is quite a mistake on the part of our managers. A transfer price is the price charged to one division for a product or service that another division produced or provided. In many, perhaps most, decentralized organizations, the transfer pricing policies actually used are grossly inefficient and sacrifice the potential advantages of decentralization. Experience shows that far too many companies have transfer pricing policies that cost them significantly in foregone growth and profits.

  17. Metric optimisation for analogue forecasting by simulated annealing

    NASA Astrophysics Data System (ADS)

    Bliefernicht, J.; Bárdossy, A.

    2009-04-01

    It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

  18. Understanding Farmers’ Forecast Use from Their Beliefs, Values, Social Norms, and Perceived Obstacles

    NASA Astrophysics Data System (ADS)

    Hu, Qi; Pytlik Zillig, Lisa M.; Lynne, Gary D.; Tomkins, Alan J.; Waltman, William J.; Hayes, Michael J.; Hubbard, Kenneth G.; Artikov, Ikrom; Hoffman, Stacey J.; Wilhite, Donald A.

    2006-09-01

    Although the accuracy of weather and climate forecasts is continuously improving and new information retrieved from climate data is adding to the understanding of climate variation, use of the forecasts and climate information by farmers in farming decisions has changed little. This lack of change may result from knowledge barriers and psychological, social, and economic factors that undermine farmer motivation to use forecasts and climate information. According to the theory of planned behavior (TPB), the motivation to use forecasts may arise from personal attitudes, social norms, and perceived control or ability to use forecasts in specific decisions. These attributes are examined using data from a survey designed around the TPB and conducted among farming communities in the region of eastern Nebraska and the western U.S. Corn Belt. There were three major findings: 1) the utility and value of the forecasts for farming decisions as perceived by farmers are, on average, around 3.0 on a 0 7 scale, indicating much room to improve attitudes toward the forecast value. 2) The use of forecasts by farmers to influence decisions is likely affected by several social groups that can provide “expert viewpoints” on forecast use. 3) A major obstacle, next to forecast accuracy, is the perceived identity and reliability of the forecast makers. Given the rapidly increasing number of forecasts in this growing service business, the ambiguous identity of forecast providers may have left farmers confused and may have prevented them from developing both trust in forecasts and skills to use them. These findings shed light on productive avenues for increasing the influence of forecasts, which may lead to greater farming productivity. In addition, this study establishes a set of reference points that can be used for comparisons with future studies to quantify changes in forecast use and influence.

  19. Price dynamics in political prediction markets

    PubMed Central

    Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes

    2009-01-01

    Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442

  20. Comparison of discrete Fourier transform (DFT) and principal component analysis/DFT as forecasting tools for absorbance time series received by UV-visible probes installed in urban sewer systems.

    PubMed

    Plazas-Nossa, Leonardo; Torres, Andrés

    2014-01-01

    The objective of this work is to introduce a forecasting method for UV-Vis spectrometry time series that combines principal component analysis (PCA) and discrete Fourier transform (DFT), and to compare the results obtained with those obtained by using DFT. Three time series for three different study sites were used: (i) Salitre wastewater treatment plant (WWTP) in Bogotá; (ii) Gibraltar pumping station in Bogotá; and (iii) San Fernando WWTP in Itagüí (in the south part of Medellín). Each of these time series had an equal number of samples (1051). In general terms, the results obtained are hardly generalizable, as they seem to be highly dependent on specific water system dynamics; however, some trends can be outlined: (i) for UV range, DFT and PCA/DFT forecasting accuracy were almost the same; (ii) for visible range, the PCA/DFT forecasting procedure proposed gives systematically lower forecasting errors and variability than those obtained with the DFT procedure; and (iii) for short forecasting times the PCA/DFT procedure proposed is more suitable than the DFT procedure, according to processing times obtained.

  1. Comparison of discrete Fourier transform (DFT) and principal component analysis/DFT as forecasting tools for absorbance time series received by UV-visible probes installed in urban sewer systems.

    PubMed

    Plazas-Nossa, Leonardo; Torres, Andrés

    2014-01-01

    The objective of this work is to introduce a forecasting method for UV-Vis spectrometry time series that combines principal component analysis (PCA) and discrete Fourier transform (DFT), and to compare the results obtained with those obtained by using DFT. Three time series for three different study sites were used: (i) Salitre wastewater treatment plant (WWTP) in Bogotá; (ii) Gibraltar pumping station in Bogotá; and (iii) San Fernando WWTP in Itagüí (in the south part of Medellín). Each of these time series had an equal number of samples (1051). In general terms, the results obtained are hardly generalizable, as they seem to be highly dependent on specific water system dynamics; however, some trends can be outlined: (i) for UV range, DFT and PCA/DFT forecasting accuracy were almost the same; (ii) for visible range, the PCA/DFT forecasting procedure proposed gives systematically lower forecasting errors and variability than those obtained with the DFT procedure; and (iii) for short forecasting times the PCA/DFT procedure proposed is more suitable than the DFT procedure, according to processing times obtained. PMID:24622562

  2. MSSM forecast for the LHC

    NASA Astrophysics Data System (ADS)

    Cabrera, Maria Eugenia; Casas, J. Alberto; de Austri, Roberto Ruiz

    2010-05-01

    We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of M Z is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on e + e - data) is considered, the preferred region (for μ > 0) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative- μ possibilities.

  3. A probabilistic approach to forecast the uncertainty with ensemble spread

    NASA Astrophysics Data System (ADS)

    Van Schaeybroeck, Bert; Vannitsem, Stéphane

    2015-04-01

    For most purposes the information gathered from an ensemble forecast is the ensemble mean and its uncertainty. The ensemble spread is commonly used as a measure of the uncertainty. We propose a method to assess whether the ensemble spread is a good measure of uncertainty and to bring forward an underlying spread-skill relationship. Forecasting the uncertainty should be probabilistic of nature. This implies that, if only the ensemble spread is available, a probability density function (PDF) for the uncertainty forecast must be reconstructed based on one parameter. Different models are introduced for the composition of such PDFs and evaluated for different spread-error metrics. The uncertainty forecast can then be verified based on probabilistic skill scores. For a perfectly reliable forecast the spread-error relationship is strongly heteroscedastic since the error can take a wide range of values, proportional to the ensemble spread. This makes a proper statistical assessment of the spread-skill relation intricate. However, it is shown that a logarithmic transformation of both spread and error allows for alleviating the heteroscedasticity. A linear regression analysis can then be performed to check whether the flow-dependent spread is a realistic indicator of the uncertainty and to what extent ensemble underdispersion or overdispersion depends on the ensemble spread. The methods are tested on the ensemble forecast of wind and geopotential height of the European Centre of Medium-range forecasts (ECMWF) over Europe and Africa. A comparison is also made with spread-skill analysis based on binning methods.

  4. Valuing year-to-go hydrologic forecast improvements for a peaking hydropower system in the Sierra Nevada

    NASA Astrophysics Data System (ADS)

    Rheinheimer, David E.; Bales, Roger C.; Oroza, Carlos A.; Lund, Jay R.; Viers, Joshua H.

    2016-05-01

    We assessed the potential value of hydrologic forecasting improvements for a snow-dominated high-elevation hydropower system in the Sierra Nevada of California, using a hydropower optimization model. To mimic different forecasting skill levels for inflow time series, rest-of-year inflows from regression-based forecasts were blended in different proportions with representative inflows from a spatially distributed hydrologic model. The statistical approach mimics the simpler, historical forecasting approach that is still widely used. Revenue was calculated using historical electricity prices, with perfect price foresight assumed. With current infrastructure and operations, perfect hydrologic forecasts increased annual hydropower revenue by 0.14 to 1.6 million, with lower values in dry years and higher values in wet years, or about $0.8 million (1.2%) on average, representing overall willingness-to-pay for perfect information. A second sensitivity analysis found a wider range of annual revenue gain or loss using different skill levels in snow measurement in the regression-based forecast, mimicking expected declines in skill as the climate warms and historical snow measurements no longer represent current conditions. The value of perfect forecasts was insensitive to storage capacity for small and large reservoirs, relative to average inflow, and modestly sensitive to storage capacity with medium (current) reservoir storage. The value of forecasts was highly sensitive to powerhouse capacity, particularly for the range of capacities in the northern Sierra Nevada. The approach can be extended to multireservoir, multipurpose systems to help guide investments in forecasting.

  5. [Explanation and forecast: relapse of juvenile offenders].

    PubMed

    Giebel, S M

    2006-01-01

    On the basis of n=82 juvenile offenders from a prison for juvenile offenders in Rheinland Pfalz the model of the logistic regression is compared with a procedure from the family of the neural nets in its efficiency to explain and predict "relapse" in form of a renewed imprisonment or prosecution /police search after dismissal. The group which can be examined is limited by the population of the prison for juvenile offenders and the explaining variables for "relapse" as "addicted to drugs" present non-metric scaling. For the explanation only probabilities for "relapse" can be indicated in this connection. By means of this probability it is possible to classify the individual case. The forecast is simulated by coincidental dividing of the data: the first part of the data is used for the explanation, the second for the forecast. With the comparison of the logistic regression with the neural nets, the superiority of neural nets in the explanation of "relapse" can be shown, since the neural nets are able to consider dependence between the explaining variables and according to that they offer a differentiated explanation. Their efficiency to predict "relapse" depends on the comparability of the distribution in the two coincidentally provided samples, the training data record for determining the explanation and the test case for the use of the explanation regarding the forecast. For optimal explanation and forecast neural nets are to be preferred to the logistic regression, since in the model with the better explanation also includes the potential for a usable better forecast. Moreover the model of the logistic regression is in fact a special case of the neural net, with a reduced complexity of the net.

  6. Evolutionary Forecast Engines for Solar Meteorology

    NASA Astrophysics Data System (ADS)

    Coimbra, C. F.

    2012-12-01

    A detailed comparison of non-stationary regression and stochastic learning methods based on k-Nearest Neighbor (kNN), Artificial Neural Networks (ANN) and Genetic Algorithm (GA) approaches is carried out in order to develop high-fidelity solar forecast engines for several time horizons of interest. A hybrid GA/ANN method emerges as the most robust stochastic learning candidate. The GA/ANN approach In general the following decisions need to be made when creating an ANN-based solar forecast model: the ANN architecture: number of layers, numbers of neurons per layer; the preprocessing scheme; the fraction and distribution between training and testing data, and the meteorological and radiometric inputs. ANNs are very well suited to handle multivariate forecasting models due to their overall flexibility and nonlinear pattern recognition abilities. However, the forecasting skill of ANNs depends on a new set of parameters to be optimized within the context of the forecast model, which is the selection of input variables that most directly impact the fidelity of the forecasts. In a data rich scenario where irradiation, meteorological, and cloud cover data are available, it is not always evident which variables to include in the model a priori. New variables can also arise from data preprocessing such as smoothing or spectral decomposition. One way to avoid time-consuming trial-and-error approaches that have limited chance to result in optimal ANN topology and input selection is to couple the ANN with some optimization algorithm that scans the solution space and "evolves" the ANN structure. Genetic Algorithms (GAs) are well suited for this task. Results and Discussion The models built upon the historical data of 2009 and 2010 are applied to the 2011 data without modifications or retraining. We consider 3 solar variability seasons or periods, which are subsets of the total error evaluation data set. The 3 periods are defined based on the solar variability study as: - a high

  7. Annual energy outlook 1999, with projections to 2020

    SciTech Connect

    1998-12-01

    The Annual Energy Outlook 1999 (AEO99) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA`s National Energy Modeling System (NEMS). The report begins with an Overview summarizing the AEO99 reference case. The next section, Legislation and Regulations, describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. Issues in Focus discusses current energy issues--the economic decline in East Asia, growth in demand for natural gas, vehicle emissions standards, competitive electricity pricing, renewable portfolio standards, and carbon emissions. It is followed by the analysis of energy market trends. The analysis in AEO99 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present a summary of the reference case forecasts in units of oil equivalence and household energy expenditures. The AEO99 projections are based on Federal, State, and local laws and regulations in effect on July 1, 1998. Pending legislation and sections of existing legislation for which funds have not been appropriated are not reflected in the forecasts. Historical data used for the AEOI99 projections were the most current available as of July 31, 1998, when most 1997 data but only partial 1998 data were available.

  8. Forecasting carbon dioxide emissions.

    PubMed

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy.

  9. The forecaster's added value

    NASA Astrophysics Data System (ADS)

    Turco, M.; Milelli, M.

    2009-09-01

    To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the

  10. Forecasting Infectious Disease Outbreaks

    NASA Astrophysics Data System (ADS)

    Shaman, J. L.

    2015-12-01

    Dynamic models of infectious disease systems abound and are used to study the epidemiological characteristics of disease outbreaks, the ecological mechanisms affecting transmission, and the suitability of various control and intervention strategies. The dynamics of disease transmission are non-linear and consequently difficult to forecast. Here, we describe combined model-inference frameworks developed for the prediction of infectious diseases. We show that accurate and reliable predictions of seasonal influenza outbreaks can be made using a mathematical model representing population-level influenza transmission dynamics that has been recursively optimized using ensemble data assimilation techniques and real-time estimates of influenza incidence. Operational real-time forecasts of influenza and other infectious diseases have been and are currently being generated.

  11. Forecasting carbon dioxide emissions.

    PubMed

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy. PMID:26081307

  12. InnoPOL: an EMCCD imaging polarimeter and 85-element curvature AO system on the 3.6-m AEOS telescope for cost effective polarimetric speckle suppression

    NASA Astrophysics Data System (ADS)

    Harrington, David; Berdyugina, Svetlana; Chun, Mark; Ftaclas, Christ; Gisler, Daniel; Kuhn, Jeff

    2014-08-01

    The Hokupa'a-85 curvature adaptive optics system components have been adapted to create a new AO-corrected coudé instrument at the 3.67m Advanced Electro-Optical System (AEOS) telescope. This new AO-corrected optical path is designed to deliver an f/40 diffraction-limited focus at wavelengths longer than 800nm. A new EMCCD-based dual-beam imaging polarimeter called InnoPOL has been designed and is presently being installed behind this corrected f/40 beam. The InnoPOL system is a flexible platform for optimizing polarimetric performance using commercial solutions and for testing modulation strategies. The system is designed as a technology test and demonstration platform as the coudé path is built using off-the-shelf components wherever possible. Models of the polarimetric performance after AO correction show that polarization modulation at rates as slow as 200Hz can cause speckle correlations in brightness and focal plane location sufficient enough to change the speckle suppression behavior of the modulators. These models are also verified by initial EMCCD scoring camera data at AEOS. Substantial instrument trades and development efforts are explored between instrument performance parameters and various polarimetric noise sources.

  13. STS pricing policy

    NASA Technical Reports Server (NTRS)

    Lee, C. M.; Stone, B.

    1982-01-01

    In 1977 NASA published Shuttle Reimbursement Policies for Civil U.S. Government, DOD and Commercial and Foreign Users. These policies were based on the principle of total cost recovery over a period of time with a fixed flat price for initial period to time to enhance transition. This fixed period was to be followed with annual adjustments thereafter, NASA is establishing a new price for 1986 and beyond. In order to recover costs, that price must be higher than the initial fixed price through FY 1985. NASA intends to remain competitive. Competitive posture includes not only price, but other factors such as assured launch, reliability, and unique services. NASA's pricing policy considers all these factors.

  14. Technology 2005 : Reviews & Forecasts

    NASA Astrophysics Data System (ADS)

    Kimura, Ken

    Nine Technical Committees (TC's) of the Fundamentals and Materials Society of IEE Japan have contributed their Review & Forecast articles to the present. Special Issue of the IEEJ Transaction on Fundamentals and Materials. So you can survey the state-of-the-art of the 9 different technical fields with these articles. The series of reviews were submitted in reply to the request by experts in the respective fields.

  15. Satellite freeze forecast system

    NASA Technical Reports Server (NTRS)

    Martsolf, J. D. (Principal Investigator)

    1983-01-01

    Provisions for back-up operations for the satellite freeze forecast system are discussed including software and hardware maintenance and DS/1000-1V linkage; troubleshooting; and digitized radar usage. The documentation developed; dissemination of data products via television and the IFAS computer network; data base management; predictive models; the installation of and progress towards the operational status of key stations; and digital data acquisition are also considered. The d addition of dew point temperature into the P-model is outlined.

  16. Frost Forecasting for Fruitgrowers

    NASA Technical Reports Server (NTRS)

    Martsolf, J. D.; Chen, E.

    1983-01-01

    Progress in forecasting from satellite data reviewed. University study found data from satellites displayed in color and used to predict frost are valuable aid to agriculture. Study evaluated scheme to use Earth-temperature data from Geostationary Operational Environmental Satellite in computer model that determines when and where freezing temperatures endanger developing fruit crops, such as apples, peaches and cherries in spring and citrus crops in winter.

  17. Land-Breeze Forecasting

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Wheeler, Mark M.; Merceret, Francis J. (Technical Monitor)

    2002-01-01

    The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability, low temperatures, and fog development. Accurate predictions of the land breeze are critical for toxic material dispersion forecasts associated with space launch missions, since wind direction and low-level stability can change noticeably with the onset of a land breeze. This report presents a seven-year observational study of land breezes over east-central Florida from 1995 to 2001. This comprehensive analysis was enabled by the high-resolution tower observations over KSC/CCAFS. Five-minute observations of winds, temperature, and moisture along with 9 15-MHz Doppler Radar Wind Profiler data were used to analyze specific land-breeze cases, while the tower data were used to construct a composite climatology. Utilities derived from this climatology were developed to assist forecasters in determining the land-breeze occurrence, timing, and movement based on predicted meteorological conditions.

  18. Global crop forecasting

    NASA Technical Reports Server (NTRS)

    Macdonald, R. B.; Hall, F. G.

    1980-01-01

    The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.

  19. Essays in financial transmission rights pricing

    NASA Astrophysics Data System (ADS)

    Posner, Barry

    This work examines issues in the pricing of financial transmission rights in the PJM market region. The US federal government is advocating the creation of large-scale, not-for-profit regional transmission organizations to increase the efficiency of the transmission of electricity. As a non-profit entity, PJM needs to allocate excess revenues collected as congestion rents, and the participants in the transmission markets need to be able to hedge their exposure to congestion rents. For these purposes, PJM has developed an instrument known as the financial transmission right (FTR). This research, utilizing a new data set assembled by the author, looks at two aspects of the FTR market. The first chapter examines the problem of forecasting congestion in a transmission grid. In the PJM FTR system firms bid in a competitive auction for FTRs that cover a period of one month. The auctions take place in the middle of the previous month; therefore firms have to forecast congestion rents for the period two to six weeks after the auction. The common methods of forecasting congestion are either time-series models or full-information engineering studies. In this research, the author develops a forecasting system that is more economically grounded than a simple time-series model, but requires less information than an engineering model. This method is based upon the arbitrage-cost methodology, whereby congesting is calculated as the difference of two non-observable variables: the transmission price difference that would exist in the total absence of transmission capacity between two nodes, and the ability of the existing transmission to reduced that price difference. If the ability to reduce the price difference is greater than the price difference, then the cost of electricity at each node will be the same, and congestion rent will be zero. If transmission capacity limits are binding on the flow of power, then a price difference persists and congestion rents exist. Three

  20. Essays in financial transmission rights pricing

    NASA Astrophysics Data System (ADS)

    Posner, Barry

    This work examines issues in the pricing of financial transmission rights in the PJM market region. The US federal government is advocating the creation of large-scale, not-for-profit regional transmission organizations to increase the efficiency of the transmission of electricity. As a non-profit entity, PJM needs to allocate excess revenues collected as congestion rents, and the participants in the transmission markets need to be able to hedge their exposure to congestion rents. For these purposes, PJM has developed an instrument known as the financial transmission right (FTR). This research, utilizing a new data set assembled by the author, looks at two aspects of the FTR market. The first chapter examines the problem of forecasting congestion in a transmission grid. In the PJM FTR system firms bid in a competitive auction for FTRs that cover a period of one month. The auctions take place in the middle of the previous month; therefore firms have to forecast congestion rents for the period two to six weeks after the auction. The common methods of forecasting congestion are either time-series models or full-information engineering studies. In this research, the author develops a forecasting system that is more economically grounded than a simple time-series model, but requires less information than an engineering model. This method is based upon the arbitrage-cost methodology, whereby congesting is calculated as the difference of two non-observable variables: the transmission price difference that would exist in the total absence of transmission capacity between two nodes, and the ability of the existing transmission to reduced that price difference. If the ability to reduce the price difference is greater than the price difference, then the cost of electricity at each node will be the same, and congestion rent will be zero. If transmission capacity limits are binding on the flow of power, then a price difference persists and congestion rents exist. Three

  1. Estimating Prices of Products

    NASA Technical Reports Server (NTRS)

    Aster, R. W.; Chamberlain, R. G.; Zendejas, S. C.; Lee, T. S.; Malhotra, S.

    1986-01-01

    Company-wide or process-wide production simulated. Price Estimation Guidelines (IPEG) program provides simple, accurate estimates of prices of manufactured products. Simplification of SAMIS allows analyst with limited time and computing resources to perform greater number of sensitivity studies. Although developed for photovoltaic industry, readily adaptable to standard assembly-line type of manufacturing industry. IPEG program estimates annual production price per unit. IPEG/PC program written in TURBO PASCAL.

  2. Food price volatility

    PubMed Central

    Gilbert, C. L.; Morgan, C. W.

    2010-01-01

    The high food prices experienced over recent years have led to the widespread view that food price volatility has increased. However, volatility has generally been lower over the two most recent decades than previously. Variability over the most recent period has been high but, with the important exception of rice, not out of line with historical experience. There is weak evidence that grains price volatility more generally may be increasing but it is too early to say. PMID:20713400

  3. Influenza forecasting in human populations: a scoping review.

    PubMed

    Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey; Chitale, Rohit A; McKenzie, F Ellis

    2014-01-01

    Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms "influenza AND (forecast* OR predict*)", excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials.

  4. Science of Tsunami Forecasting: 2010 Chilean Tsunami Challenge

    NASA Astrophysics Data System (ADS)

    Titov, Vasily; Bernard, Eddie; Tang, Rachel; Wei, Yong; Uslu, Burak; Eble, Marie

    2010-05-01

    Tsunami forecasting with real-time models and real-time data has always been one of the main goals of tsunami research. The February 27th, 2010 Chile tsunami provided the challenge and the opportunity to test the modern state of the science in tsunami forecasting. By contrast with the previous basin-wide tsunami generated by the third largest 2004 Sumatra earthquake, the fifth largest Chilean earthquake occurred at the time and in the area where a variety of real-time measurements and model forecast models have been available to assess the generated tsunami in real-time. The Chile tsunami was generated by a Mw 8.8 earthquake (35.846S, 72.719W ), at 06:34 UTC, 115 km (60 miles) NNE of Concepcion, Chile (according to the USGS). It has been recorded at coastal sea level gages around the Pacific Ocean, staring from the near-field record that caught the wave half an hour after generation at Valparaiso, to the coastal recordings of the wave arrived at Japan and Russian Far East almost a day later. In approximately 3 hours after the earthquake, the tsunami was first recorded at DART buoy 32412, providing real-time deep ocean signature of the propagating tsunami. All that measurements provided ample data for the real-time forecast analysis and for the model performance and forecast skills assessment throughout the Pacific basin. We present results of the performance of the NOAA forecast. The forecast method uses MOST model with the data assimilated from the earthquake and deep-ocean tsunami DART measurement. The comparison with tide gages and coastal impacts provide opportunity to assess the accuracy and efficiency of the forecast. The successes, lessons learned and future challengers for the tsunami forecast science are discussed.

  5. Do quantitative decadal forecasts from GCMs provide decision relevant skill?

    NASA Astrophysics Data System (ADS)

    Suckling, E. B.; Smith, L. A.

    2012-04-01

    forecasts up to ten years ahead (decadal forecasts) are considered, both on global and regional spatial scales for surface air temperature. Such decadal forecasts are not only important in terms of providing information on the impacts of near-term climate change, but also from the perspective of climate model validation, as hindcast experiments and a sufficient database of historical observations allow standard forecast verification methods to be used. Simulation models from the ENSEMBLES hindcast experiment [3] are evaluated and contrasted with static forecasts of the observed climatology, persistence forecasts and against simple statistical models, called dynamic climatology (DC). It is argued that DC is a more apropriate benchmark in the case of a non-stationary climate. It is found that the ENSEMBLES models do not demonstrate a significant increase in skill relative to the empirical models even at global scales over any lead time up to a decade ahead. It is suggested that the contsruction and co-evaluation with the data-based models become a regular component of the reporting of large simulation model forecasts. The methodology presented may easily be adapted to other forecasting experiments and is expected to influence the design of future experiments. The inclusion of comparisons with dynamic climatology and other data-based approaches provide important information to both scientists and decision makers on which aspects of state-of-the-art simulation forecasts are likely to be fit for purpose. [1] J. Bröcker and L. A. Smith. From ensemble forecasts to predictive distributions, Tellus A, 60(4), 663-678 (2007). [2] J. Bröcker and L. A. Smith. Scoring probabilistic forecasts: The importance of being proper, Weather and Forecasting, 22, 382-388 (2006). [3] F. J. Doblas-Reyes, A. Weisheimer, T. N. Palmer, J. M. Murphy and D. Smith. Forecast quality asessment of the ENSEMBLES seasonal-to-decadal stream 2 hindcasts, ECMWF Technical Memorandum, 621 (2010).

  6. Seasonal forecasting of discharge for the Raccoon River, Iowa

    NASA Astrophysics Data System (ADS)

    Slater, Louise; Villarini, Gabriele; Bradley, Allen; Vecchi, Gabriel

    2016-04-01

    The state of Iowa (central United States) is regularly afflicted by severe natural hazards such as the 2008/2013 floods and the 2012 drought. To improve preparedness for these catastrophic events and allow Iowans to make more informed decisions about the most suitable water management strategies, we have developed a framework for medium to long range probabilistic seasonal streamflow forecasting for the Raccoon River at Van Meter, a 8900-km2 catchment located in central-western Iowa. Our flow forecasts use statistical models to predict seasonal discharge for low to high flows, with lead forecasting times ranging from one to ten months. Historical measurements of daily discharge are obtained from the U.S. Geological Survey (USGS) at the Van Meter stream gage, and used to compute quantile time series from minimum to maximum seasonal flow. The model is forced with basin-averaged total seasonal precipitation records from the PRISM Climate Group and annual row crop production acreage from the U.S. Department of Agriculture's National Agricultural Statistics Services database. For the forecasts, we use corn and soybean production from the previous year (persistence forecast) as a proxy for the impacts of agricultural practices on streamflow. The monthly precipitation forecasts are provided by eight Global Climate Models (GCMs) from the North American Multi-Model Ensemble (NMME), with lead times ranging from 0.5 to 11.5 months, and a resolution of 1 decimal degree. Additionally, precipitation from the month preceding each season is used to characterize antecedent soil moisture conditions. The accuracy of our modelled (1927-2015) and forecasted (2001-2015) discharge values is assessed by comparison with the observed USGS data. We explore the sensitivity of forecast skill over the full range of lead times, flow quantiles, forecast seasons, and with each GCM. Forecast skill is also examined using different formulations of the statistical models, as well as NMME forecast

  7. Stochastic Energy Deployment System (SEDS) World Oil Model (WOM)

    2009-08-07

    The function of the World Oil Market Model (WOMM) is to calculate a world oil price. SEDS will set start and end dates for the forecast period, and a time increment (assumed to be 1 year in the initial version). The WOMM will then randomly select an Annual Energy Outlook (AEO) oil price case and calibrate itself to that case. As it steps through each year, the WOMM will generate a stochastic supply shock tomore » OPEC output and accept a new estimate of U.S. petroleum demand from SEDS. The WOMM will then calculate a new oil market equilibrium for the current year. The world oil price at the new equilibrium will be sent back to SEDS. When the end year is reached, the process will begin again with the selection of a new AEO forecast. Iterations over forecasts will continue until SEDS has completed all its simulation runs.« less

  8. Generalized networking engineering: optimal pricing and routing in multiservice networks

    NASA Astrophysics Data System (ADS)

    Mitra, Debasis; Wang, Qiong

    2002-07-01

    One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.

  9. Hydrological Forecasting Practices in Brazil

    NASA Astrophysics Data System (ADS)

    Fan, Fernando; Paiva, Rodrigo; Collischonn, Walter; Ramos, Maria-Helena

    2016-04-01

    This work brings a review on current hydrological and flood forecasting practices in Brazil, including the main forecasts applications, the different kinds of techniques that are currently being employed and the institutions involved on forecasts generation. A brief overview of Brazil is provided, including aspects related to its geography, climate, hydrology and flood hazards. A general discussion about the Brazilian practices on hydrological short and medium range forecasting is presented. Detailed examples of some hydrological forecasting systems that are operational or in a research/pre-operational phase using the large scale hydrological model MGB-IPH are also presented. Finally, some suggestions are given about how the forecasting practices in Brazil can be understood nowadays, and what are the perspectives for the future.

  10. A 30-day forecast experiment with the GISS model and updated sea surface temperatures

    NASA Technical Reports Server (NTRS)

    Spar, J.; Atlas, R.; Kuo, E.

    1975-01-01

    The GISS model was used to compute two parallel global 30-day forecasts for the month January 1974. In one forecast, climatological January sea surface temperatures were used, while in the other observed sea temperatures were inserted and updated daily. A comparison of the two forecasts indicated no clear-cut beneficial effect of daily updating of sea surface temperatures. Despite the rapid decay of daily predictability, the model produced a 30-day mean forecast for January 1974 that was generally superior to persistence and climatology when evaluated over either the globe or the Northern Hemisphere, but not over smaller regions.

  11. Competitive electricity markets, prices and generator entry and exit

    NASA Astrophysics Data System (ADS)

    Ethier, Robert George

    The electric power industry in the United States is quickly being deregulated and restructured. In the past, new electric generation capacity was added by regulated utilities to meet forecasted demand levels and maintain reserve margins. With competitive wholesale generation, investment will be the responsibility of independent private investors. Electricity prices will assume the coordinating function which has until recently been the responsibility of regulatory agencies. Competitive prices will provide the entry and exit signals for generators in the future. Competitive electricity markets have a distinctive price formation process, and thus require a specialized price model. A mean-reverting price process with stochastic jumps is proposed as an appropriate long-run price process for annual electricity prices. This price process is used to develop an analytic real options model for private investment decisions. The required recursive infinite series solutions have not been widely used for real option models. Entry thresholds and asset values for competitive wholesale electricity markets, and exit decisions for plants with significant retirement costs (i.e. nuclear power plants), are examined. The proposed model results in significantly lower trigger prices for both entry and exit decisions, and higher asset values, when compared with other standard models. The model is used to show that the incentives for retiring a nuclear plant are very sensitive to the treatment of decommissioning costs (e.g. if plant owners do not face full decommissioning costs, retirement decisions may be economically premature.) An econometric model of short-run price behavior is estimated by the method of maximum likelihood using daily electricity prices from markets in the USA and Australia. The model specifies two mean reverting price processes with stochastic Markov switching between the regimes, which allows discontinuous jumps in electricity prices. Econometric tests show that a two

  12. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, E.; Wetterhall, F.; Dutra, E.; Di Giuseppe, F.; Pappenberger, F.

    2014-02-01

    The humanitarian crises caused by the recent droughts (2008-2009 and 2010-2011) in East Africa have illustrated that the ability to make accurate drought forecasts with sufficient lead time is essential. The use of dynamical model precipitation forecasts in combination with drought indices, such as the Standardized Precipitation Index (SPI), can potentially lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for March-May and October-December rain seasons when evaluated against measurements from the available in situ stations from East Africa. The forecast for October-December rain season has higher skill than for the March-May season. ECMWF forecasts add value to the consensus forecasts produced during the Greater Horn of Africa Climate Outlook Forum (GHACOF), which is the present operational product for precipitation forecast over East Africa. Complementing the original ECMWF precipitation forecasts with SPI provides additional information on the spatial extent and intensity of the drought event.

  13. Hydrologic Forecasting and Hydropower Production

    NASA Astrophysics Data System (ADS)

    Wigmosta, M. S.; Voisin, N.; Lettenmaier, D. P.; Coleman, A.; Mishra, V.; Schaner, N. A.

    2011-12-01

    Hydroelectric power production is one of many competing demands for available water along with other priority uses such as irrigation, thermoelectric cooling, municipal, recreation, and environmental performance. Increasingly, hydroelectric generation is being used to offset the intermittent nature of some renewable energy sources such as wind-generated power. An accurate forecast of the magnitude and timing of water supply assists managers in integrated planning and operations to balance competing water uses against current and future supply while protecting against the possibility of water or energy shortages and excesses with real-time actions. We present a medium-range to seasonal ensemble streamflow forecasting system where uncertainty in forecasts is addressed explicitly. The integrated forecast system makes use of remotely-sensed data and automated spatial and temporal data assimilation. Remotely-sensed snow cover, observed snow water equivalent, and observed streamflow data are used to update the hydrologic model state prior to the forecast. In forecast mode, the hydrology model is forced by calibrated ensemble weather/climate forecasts. This system will be fully integrated into a water optimization toolset to inform reservoir and power operations, and guide environmental performance decision making. This flow forecast system development is carried out in agreement with the National Weather Service so that the system can later be incorporated into the NOAA eXperimental Ensemble Forecast Service (XEFS).

  14. Solar Indices Forecasting Tool

    NASA Astrophysics Data System (ADS)

    Henney, Carl John; Shurkin, Kathleen; Arge, Charles; Hill, Frank

    2016-05-01

    Progress to forecast key space weather parameters using SIFT (Solar Indices Forecasting Tool) with the ADAPT (Air Force Data Assimilative Photospheric flux Transport) model is highlighted in this presentation. Using a magnetic flux transport model, ADAPT, we estimate the solar near-side field distribution that is used as input into empirical models for predicting F10.7(solar 10.7 cm, 2.8 GHz, radio flux), the Mg II core-to-wing ratio, and selected bands of solar far ultraviolet (FUV) and extreme ultraviolet (EUV) irradiance. Input to the ADAPT model includes the inferred photospheric magnetic field from the NISP ground-based instruments, GONG & VSM. Besides a status update regarding ADAPT and SIFT models, we will summarize the findings that: 1) the sum of the absolute value of strong magnetic fields, associated with sunspots, is shown to correlate well with the observed daily F10.7 variability (Henney et al. 2012); and 2) the sum of the absolute value of weak magnetic fields, associated with plage regions, is shown to correlate well with EUV and FUV irradiance variability (Henney et al. 2015). This work utilizes data produced collaboratively between Air Force Research Laboratory (AFRL) and the National Solar Observatory (NSO). The ADAPT model development is supported by AFRL. The input data utilized by ADAPT is obtained by NISP (NSO Integrated Synoptic Program). NSO is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under a cooperative agreement with the National Science Foundation (NSF). The 10.7 cm solar radio flux data service, utilized by the ADAPT/SIFT F10.7 forecasting model, is operated by the National Research Council of Canada and National Resources Canada, with the support of the Canadian Space Agency.

  15. Comparing Prices for Food and Diet Research: The Metric Matters

    PubMed Central

    Jones, N. R. V.; Monsivais, P.

    2016-01-01

    ABSTRACT An important issue in research into access to healthy food is how best to compare the price of foods. The appropriate metric for comparison has been debated at length, with proponents variously stating that food prices should be compared in terms of their energy content, their edible mass, or their typical portion size. In this article we assessed the impact of using different food price metrics on the observed difference in price between food groups and categories of healthiness, using United Kingdom consumer price index data for 148 foods and beverages in 2012. We found that the choice of metric had a marked effect on the findings and conclude that this must be decided in advance to suit the reason for comparing food prices.

  16. Comparing Prices for Food and Diet Research: The Metric Matters

    PubMed Central

    Jones, N. R. V.; Monsivais, P.

    2016-01-01

    ABSTRACT An important issue in research into access to healthy food is how best to compare the price of foods. The appropriate metric for comparison has been debated at length, with proponents variously stating that food prices should be compared in terms of their energy content, their edible mass, or their typical portion size. In this article we assessed the impact of using different food price metrics on the observed difference in price between food groups and categories of healthiness, using United Kingdom consumer price index data for 148 foods and beverages in 2012. We found that the choice of metric had a marked effect on the findings and conclude that this must be decided in advance to suit the reason for comparing food prices. PMID:27630754

  17. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ..., rounded to the nearest cent, shall be the protein price per pound times 3.1 plus the other solids price... cents and multiplying the result by 0.99. (n) Protein price. The protein price per pound, rounded to the... one-hundredth cent, shall be the U.S. average NASS dry whey survey price reported by the...

  18. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ..., rounded to the nearest cent, shall be the protein price per pound times 3.1 plus the other solids price... cents and multiplying the result by 0.99. (n) Protein price. The protein price per pound, rounded to the... one-hundredth cent, shall be the U.S. average NASS dry whey survey price reported by the...

  19. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ..., rounded to the nearest cent, shall be the protein price per pound times 3.1 plus the other solids price... cents and multiplying the result by 0.99. (n) Protein price. The protein price per pound, rounded to the... one-hundredth cent, shall be the U.S. average NASS dry whey survey price reported by the...

  20. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ..., rounded to the nearest cent, shall be the protein price per pound times 3.1 plus the other solids price... cents and multiplying the result by 0.99. (n) Protein price. The protein price per pound, rounded to the... one-hundredth cent, shall be the U.S. average NASS dry whey survey price reported by the...

  1. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ..., rounded to the nearest cent, shall be the protein price per pound times 3.1 plus the other solids price... cents and multiplying the result by 0.99. (n) Protein price. The protein price per pound, rounded to the... one-hundredth cent, shall be the U.S. average NASS dry whey survey price reported by the...

  2. Weather Forecasting Aid

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Weather forecasters are usually very precise in reporting such conditions as temperature, wind velocity and humidity. They also provide exact information on barometric pressure at a given moment, and whether the barometer is "rising" or "falling"- but not how rapidly or how slowly it is rising or falling. Until now, there has not been available an instrument which measures precisely the current rate of change of barometric pressure. A meteorological instrument called a barograph traces the historical ups and downs of barometric pressure and plots a rising or falling curve, but, updated every three hours, it is only momentarily accurate at each updating.

  3. Forecast Mekong: 2011 update

    USGS Publications Warehouse

    Turnipseed, D. Phil

    2011-01-01

    In 2009, U.S. Secretary of State Hillary R. Clinton joined with the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam in launching the Lower Mekong Initiative to enhance U.S. engagement with the Lower Mekong countries in the areas of environment, health, education, and infrastructure. Part of the Lower Mekong Initiative, the U.S. Geological Survey's Forecast Mekong project is engaging the United States in scientific research relevant to environmental issues in the Lower Mekong River countries and is staying the course in support of the Mekong Nations with a suite of new projects for 2011.

  4. Forecasting in Complex Systems

    NASA Astrophysics Data System (ADS)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  5. Mind your pricing cues.

    PubMed

    Anderson, Eric; Simester, Duncan

    2003-09-01

    For most of the items they buy, consumers don't have an accurate sense of what the price should be. Ask them to guess how much a four-pack of 35-mm film costs, and you'll get a variety of wrong answers: Most people will underestimate; many will only shrug. Research shows that consumers' knowledge of the market is so far from perfect that it hardly deserves to be called knowledge at all. Yet people happily buy film and other products every day. Is this because they don't care what kind of deal they're getting? No. Remarkably, it's because they rely on retailers to tell them whether they're getting a good price. In subtle and not-so-subtle ways, retailers send signals to customers, telling them whether a given price is relatively high or low. In this article, the authors review several common pricing cues retailers use--"sale" signs, prices that end in 9, signpost items, and price-matching guarantees. They also offer some surprising facts about how--and how well--those cues work. For instance, the authors' tests with several mail-order catalogs reveal that including the word "sale" beside a price can increase demand by more than 50%. The practice of using a 9 at the end of a price to denote a bargain is so common, you'd think customers would be numb to it. Yet in a study the authors did involving a women's clothing catalog, they increased demand by a third just by changing the price of a dress from $34 to $39. Pricing cues are powerful tools for guiding customers' purchasing decisions, but they must be applied judiciously. Used inappropriately, the cues may breach customers' trust, reduce brand equity, and give rise to lawsuits. PMID:12964397

  6. Simple fuzzy logic estimation of flow forecast uncertainty

    NASA Astrophysics Data System (ADS)

    Danhelka, Jan

    2010-05-01

    Fuzzy logic is recognized as useful tool to support for decision making under uncertainty. As such some methods for reservoir operation or real time flood management were developed. Maskey (2004) describes method of model uncertainty assessment based on qualitative expert judgement and its representation in fuzzy space. It is based on categorical judging of the quality and importance of selected model parameters (processes). The method was modified in order to reflect varying uncertainty of single model realization (forecast) with respect to inputting precipitation forecast (QPF). Two model uncertainty parameters were distinguish: 1) QPF, 2) model uncertainty due to concept and parameters. The approach was tested and applied for Černá river basin (127 km2) in southern Bohemia for the period from January 2008. Aqualog forecasting system (SAC-SMA implemented) is used for real time forecasting within the basin. It provides deterministic QPF based (NWP ALADIN) forecast with 48 h lead time. The aim of the study was to estimate the uncertainty of the forecast using simple fuzzy procedure. QPF uncertainty dominates the total uncertainty of hydrological forecast in condition of the Czech Republic. Therefore an evaluation of QPF performance was done for the basin. Based on detected quantiles of relative difference the fuzzy expression of QPF exceedance probability was done to represent the quality of QPF parameter. We further assumed that the importance of QPF parameter is proportional to its quality. Model uncertainty was qualitatively estimated to be moderate both in quality and importance. Than the fuzzy sum of both parameters was computed. The output is than fitted to deterministic flow forecast using the highest forecasted flow and its known reference in fuzzy space (determined according to QPF performance evaluation). The case study provided promising results in the meaning of Brier skill score (0.24) as well as in comparison of forecasted to expected distribution

  7. Forecast Skill Visualization in Climate Research

    NASA Astrophysics Data System (ADS)

    Boettinger, Michael; Roeber, Niklas; Spickermann, Dela; Polkova, Iuliia

    2015-04-01

    With ensemble simulation techniques, the uncertainty in climate simulations can be assessed, and the statistical robustness of the results is improved in comparison to single model realizations. Different ensemble generation schemes exist to represent sources of uncertainty relevant at certain timescales. In this project, we analyze near-term climate predictions, for which the initial condition uncertainty dominates the total uncertainty, and can be sampled by repeating forecasts several times with the same boundary condition, but with slightly varying initial conditions. Such experiments allow estimating the model specific ensemble spread. Ensemble simulations have added a new dimension to the data: for climate variables with a given spatial and temporal resolution, associated uncertainty (or certainty) measures can be derived. To make use of this new information, the data has to be visualized concurrently with its respective uncertainty information. For near-term climate predictions, the uncertainty is usually represented in terms of spread scores or the forecast skill. This information might have completely different spatial and temporal characteristics than the forecast variable. In this work, we show how geospatial uncertainty information is visualized today within the climate community. Furthermore, we present own approaches using state-of-the-art visualization systems like Avizo Green or Paraview. As example data set, we have used decadal climate predictions.

  8. Calls Forecast for the Moscow Ambulance Service. The Impact of Weather Forecast

    NASA Astrophysics Data System (ADS)

    Gordin, Vladimir; Bykov, Philipp

    2015-04-01

    We use the known statistics of the calls for the current and previous days to predict them for tomorrow and for the following days. We assume that this algorithm will work operatively, will cyclically update the available information and will move the horizon of the forecast. Sure, the accuracy of such forecasts depends on their lead time, and from a choice of some group of diagnoses. For comparison we used the error of the inertial forecast (tomorrow there will be the same number of calls as today). Our technology has demonstrated accuracy that is approximately two times better compared to the inertial forecast. We obtained the following result: the number of calls depends on the actual weather in the city as well as on its rate of change. We were interested in the accuracy of the forecast for 12-hour sum of the calls in real situations. We evaluate the impact of the meteorological errors [1] on the forecast errors of the number of Ambulance calls. The weather and the Ambulance calls number both have seasonal tendencies. Therefore, if we have medical information from one city only, we should separate the impacts of such predictors as "annual variations in the number of calls" and "weather". We need to consider the seasonal tendencies (associated, e. g. with the seasonal migration of the population) and the impact of the air temperature simultaneously, rather than sequentially. We forecasted separately the number of calls with diagnoses of cardiovascular group, where it was demonstrated the advantage of the forecasting method, when we use the maximum daily air temperature as a predictor. We have a chance to evaluate statistically the influence of meteorological factors on the dynamics of medical problems. In some cases it may be useful for understanding of the physiology of disease and possible treatment options. We can assimilate some personal archives of medical parameters for the individuals with concrete diseases and the relative meteorological archive. As a

  9. Interactive Forecasting with the National Weather Service River Forecast System

    NASA Technical Reports Server (NTRS)

    Smith, George F.; Page, Donna

    1993-01-01

    The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

  10. [Study on early-warning of Chinese materia medica price base on ARMA model].

    PubMed

    Chang, Feng; Mao, Yang-Dui

    2014-05-01

    This study sets up an early-warning system framework of Chinese materia medica price, using price index as early warning indicator to establish black early-warning model, with indicator of price index volatility and limit line of "price principal". The research divides warning degree into 5 parts named negative heavy warning, negative light warning, no warning, positive light warning and positive heavy warning, with 5 corresponding lights to describe the change level of the medicine price. Then make an early-warning empirical research based on Chengdu Chinese materia medica price index from December in 2010 to October in 2013. ARMA model is applied to forecast index and the result of early-warning is analyzed, and finally farmer households, companies, customers and the government are recommended respectively.

  11. Hydro-economic assessment of hydrological forecasting systems

    NASA Astrophysics Data System (ADS)

    Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

    2012-01-01

    SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

  12. Pricing of new vaccines

    PubMed Central

    McGlone, Sarah M

    2010-01-01

    New vaccine pricing is a complicated process that could have substantial long-standing scientific, medical and public health ramifications. Pricing can have a considerable impact on new vaccine adoption and, thereby, either culminate or thwart years of research and development and public health efforts. Typically, pricing strategy consists of the following eleven components: (1) Conduct a target population analysis; (2) Map potential competitors and alternatives; (3) Construct a vaccine target product profile (TPP) and compare it to projected or actual TPPs of competing vaccines; (4) Quantify the incremental value of the new vaccine's characteristics; (5) Determine vaccine positioning in the marketplace; (6) Estimate the vaccine price-demand curve; (7) Calculate vaccine costs (including those of manufacturing, distribution, and research and development); (8) Account for various legal, regulatory, third party payer and competitor factors; (9) Consider the overall product portfolio; (10) Set pricing objectives; (11) Select pricing and pricing structure. While the biomedical literature contains some studies that have addressed these components, there is still considerable room for more extensive evaluation of this important area. PMID:20861678

  13. New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Tondel, Fabien; Thorne, Jennifer A.; Essam, Timothy; Mann, Bristol F.; Stabler, Blake; Eilerts, Gary

    2011-01-01

    Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.

  14. Long-Term Drought Forecasting based on Climate Signals using Multi-Channel

    NASA Astrophysics Data System (ADS)

    Cui, H.; Singh, V. P.; Tang, Q.; Ge, Q.

    2015-12-01

    Drought is an insidious natural hazard, which may cause severe damage both in natural environment and human society. Timely drought forecasting enables civil protection authorities and public to take actions to reduce the risk of droughts. Thus drought forecasting plays an important role in setting out drought mitigation strategy. Analysis of the dominant oscillations of droughts and large-scale climate indices has shown that climate indices, such as the El Niño Southern Oscillation (ENSO), are significant indicators of drought occurrences in southern United States. It suggests that the climate indices may be used in drought forecasting at a long lead time. In this study, the multi-channel entropy spectral analysis (MCESA) was developed to incorporate the ENSO climate signals to entropy approach for long-term drought forecasting. To focus on the lack of surface water, drought was quantified by standardized streamflow index (SSI) in this study. SSI time series turned out to be stationary and highly autocorrelated, which showed significant 12-month periodicity. As a result, SSI was successfully forecasted using MCESA with ENSO as an indicator for lead times of 4-6 years. The drought forecasting was more reliable for the stations in humid areas than arid areas. Comparison from the retrospective drought forecasts with or without ENSO showed that inclusion of ENSO climate signals reduced the forecasting errors. The forecasts under El Nino (La Nina) condition reduced (increased) drought severity, making the forecasts more accurate.

  15. Six Sigma pricing.

    PubMed

    Sodhi, ManMohan S; Sodhi, Navdeep S

    2005-05-01

    Many companies are now good at managing costs and wringing out manufacturing efficiencies. The TQM movement and the disciplines of Six Sigma have seen to that. But the discipline so often brought to the cost side of the business equation is found far less commonly on the revenue side. The authors describe how a global manufacturer of industrial equipment, which they call Acme Incorporated, recently applied Six Sigma to one major revenue related activity--the price-setting process. It seemed to Acme's executives that pricing closely resembled many manufacturing processes. So, with the help of a Six Sigma black belt from manufacturing, a manager from Acme's pricing division recruited a team to carry out the five Six Sigma steps: Define what constitutes a defect. At Acme, a defect was an item sold at an unauthorized price. Gather data and prepare it for analysis. That involved mapping out the existing pricing-agreement process. Analyze the data. The team identified the ways in which people failed to carry out or assert effective control at each stage. Recommend modifications to the existing process. The team sought to decrease the number of unapproved prices without creating an onerous approval apparatus. Create controls. This step enabled Acme to sustain and extend the improvements in its pricing procedures. As a result of the changes, Acme earned dollar 6 million in additional revenue on one product line alone in the six months following implementation--money that went straight to the bottom line. At the same time, the company removed much of the organizational friction that had long bedeviled its pricing process. Other companies can benefit from Acme's experience as they look for ways to exercise price control without alienating customers. PMID:15929409

  16. Approximate option pricing

    SciTech Connect

    Chalasani, P.; Saias, I.; Jha, S.

    1996-04-08

    As increasingly large volumes of sophisticated options (called derivative securities) are traded in world financial markets, determining a fair price for these options has become an important and difficult computational problem. Many valuation codes use the binomial pricing model, in which the stock price is driven by a random walk. In this model, the value of an n-period option on a stock is the expected time-discounted value of the future cash flow on an n-period stock price path. Path-dependent options are particularly difficult to value since the future cash flow depends on the entire stock price path rather than on just the final stock price. Currently such options are approximately priced by Monte carlo methods with error bounds that hold only with high probability and which are reduced by increasing the number of simulation runs. In this paper the authors show that pricing an arbitrary path-dependent option is {number_sign}-P hard. They show that certain types f path-dependent options can be valued exactly in polynomial time. Asian options are path-dependent options that are particularly hard to price, and for these they design deterministic polynomial-time approximate algorithms. They show that the value of a perpetual American put option (which can be computed in constant time) is in many cases a good approximation to the value of an otherwise identical n-period American put option. In contrast to Monte Carlo methods, the algorithms have guaranteed error bounds that are polynormally small (and in some cases exponentially small) in the maturity n. For the error analysis they derive large-deviation results for random walks that may be of independent interest.

  17. Six Sigma pricing.

    PubMed

    Sodhi, ManMohan S; Sodhi, Navdeep S

    2005-05-01

    Many companies are now good at managing costs and wringing out manufacturing efficiencies. The TQM movement and the disciplines of Six Sigma have seen to that. But the discipline so often brought to the cost side of the business equation is found far less commonly on the revenue side. The authors describe how a global manufacturer of industrial equipment, which they call Acme Incorporated, recently applied Six Sigma to one major revenue related activity--the price-setting process. It seemed to Acme's executives that pricing closely resembled many manufacturing processes. So, with the help of a Six Sigma black belt from manufacturing, a manager from Acme's pricing division recruited a team to carry out the five Six Sigma steps: Define what constitutes a defect. At Acme, a defect was an item sold at an unauthorized price. Gather data and prepare it for analysis. That involved mapping out the existing pricing-agreement process. Analyze the data. The team identified the ways in which people failed to carry out or assert effective control at each stage. Recommend modifications to the existing process. The team sought to decrease the number of unapproved prices without creating an onerous approval apparatus. Create controls. This step enabled Acme to sustain and extend the improvements in its pricing procedures. As a result of the changes, Acme earned dollar 6 million in additional revenue on one product line alone in the six months following implementation--money that went straight to the bottom line. At the same time, the company removed much of the organizational friction that had long bedeviled its pricing process. Other companies can benefit from Acme's experience as they look for ways to exercise price control without alienating customers.

  18. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  19. Regional-seasonal weather forecasting

    SciTech Connect

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  20. The pioneers of weather forecasting

    NASA Astrophysics Data System (ADS)

    Ballard, Susan

    2016-01-01

    In The Weather Experiment author Peter Moore takes us on a compelling journey through the early history of weather forecasting, bringing to life the personalities, lives and achievements of the men who put in place the building blocks required for forecasts to be possible.

  1. Weather Forecasting Systems and Methods

    NASA Technical Reports Server (NTRS)

    Mecikalski, John (Inventor); MacKenzie, Wayne M., Jr. (Inventor); Walker, John Robert (Inventor)

    2014-01-01

    A weather forecasting system has weather forecasting logic that receives raw image data from a satellite. The raw image data has values indicative of light and radiance data from the Earth as measured by the satellite, and the weather forecasting logic processes such data to identify cumulus clouds within the satellite images. For each identified cumulus cloud, the weather forecasting logic applies interest field tests to determine a score indicating the likelihood of the cumulus cloud forming precipitation and/or lightning in the future within a certain time period. Based on such scores, the weather forecasting logic predicts in which geographic regions the identified cumulus clouds will produce precipitation and/or lighting within during the time period. Such predictions may then be used to provide a weather map thereby providing users with a graphical illustration of the areas predicted to be affected by precipitation within the time period.

  2. Forecasting Smoothed Non-Stationary Time Series Using Genetic Algorithms

    NASA Astrophysics Data System (ADS)

    Norouzzadeh, P.; Rahmani, B.; Norouzzadeh, M. S.

    We introduce kernel smoothing method to extract the global trend of a time series and remove short time scales variations and fluctuations from it. A multifractal detrended fluctuation analysis (MF-DFA) shows that the multifractality nature of TEPIX returns time series is due to both fatness of the probability density function of returns and long range correlations between them. MF-DFA results help us to understand how genetic algorithm and kernel smoothing methods act. Then we utilize a recently developed genetic algorithm for carrying out successful forecasts of the trend in financial time series and deriving a functional form of Tehran price index (TEPIX) that best approximates the time variability of it. The final model is mainly dominated by a linear relationship with the most recent past value, while contributions from nonlinear terms to the total forecasting performance are rather small.

  3. Models for forecasting energy use in the US farm sector

    NASA Astrophysics Data System (ADS)

    Christensen, L. R.

    1981-07-01

    Econometric models were developed and estimated for the purpose of forecasting electricity and petroleum demand in US agriculture. A structural approach is pursued which takes account of the fact that the quantity demanded of any one input is a decision made in conjunction with other input decisions. Three different functional forms of varying degrees of complexity are specified for the structural cost function, which describes the cost of production as a function of the level of output and factor prices. Demand for materials (all purchased inputs) is derived from these models. A separate model which break this demand up into demand for the four components of materials is used to produce forecasts of electricity and petroleum is a stepwise manner.

  4. Price and cost estimation

    NASA Technical Reports Server (NTRS)

    Stewart, R. D.

    1979-01-01

    Price and Cost Estimating Program (PACE II) was developed to prepare man-hour and material cost estimates. Versatile and flexible tool significantly reduces computation time and errors and reduces typing and reproduction time involved in preparation of cost estimates.

  5. Pricing and Fee Management.

    ERIC Educational Resources Information Center

    Fischer, Richard B.

    1986-01-01

    Defines key terms and discusses things to consider when setting fees for a continuing education program. These include (1) the organization's philosophy and mission, (2) certain key variables, (3) pricing strategy options, and (4) the test of reasonableness. (CH)

  6. Price percolation model

    NASA Astrophysics Data System (ADS)

    Kanai, Yasuhiro; Abe, Keiji; Seki, Yoichi

    2015-06-01

    We propose a price percolation model to reproduce the price distribution of components used in industrial finished goods. The intent is to show, using the price percolation model and a component category as an example, that percolation behaviors, which exist in the matter system, the ecosystem, and human society, also exist in abstract, random phenomena satisfying the power law. First, we discretize the total potential demand for a component category, considering it a random field. Second, we assume that the discretized potential demand corresponding to a function of a finished good turns into actual demand if the difficulty of function realization is less than the maximum difficulty of the realization. The simulations using this model suggest that changes in a component category's price distribution are due to changes in the total potential demand corresponding to the lattice size and the maximum difficulty of realization, which is an occupation probability. The results are verified using electronic components' sales data.

  7. Reliable probabilistic forecasts from an ensemble reservoir inflow forecasting system

    NASA Astrophysics Data System (ADS)

    Bourdin, Dominique R.; Nipen, Thomas N.; Stull, Roland B.

    2014-04-01

    This paper describes a probabilistic reservoir inflow forecasting system that explicitly attempts to sample from major sources of uncertainty in the modeling chain. Uncertainty in hydrologic forecasts arises due to errors in the hydrologic models themselves, their parameterizations, and in the initial and boundary conditions (e.g., meteorological observations or forecasts) used to drive the forecasts. The Member-to-Member (M2M) ensemble presented herein uses individual members of a numerical weather model ensemble to drive two different distributed hydrologic models, each of which is calibrated using three different objective functions. An ensemble of deterministic hydrologic states is generated by spinning up the daily simulated state using each model and parameterization. To produce probabilistic forecasts, uncertainty models are used to fit probability distribution functions (PDF) to the bias-corrected ensemble. The parameters of the distribution are estimated based on statistical properties of the ensemble and past verifying observations. The uncertainty model is able to produce reliable probability forecasts by matching the shape of the PDF to the shape of the empirical distribution of forecast errors. This shape is found to vary seasonally in the case-study watershed. We present an "intelligent" adaptation to a Probability Integral Transform (PIT)-based probability calibration scheme that relabels raw cumulative probabilities into calibrated cumulative probabilities based on recent past forecast performance. As expected, the intelligent scheme, which applies calibration corrections only when probability forecasts are deemed sufficiently unreliable, improves reliability without the inflation of ignorance exhibited in certain cases by the original PIT-based scheme.

  8. Dynamic pricing of network goods with boundedly rational consumers

    PubMed Central

    Radner, Roy; Radunskaya, Ami; Sundararajan, Arun

    2014-01-01

    We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller’s optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product’s user base evolving over time and consumers basing their choices on a mixture of a myopic and a “stubborn” expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice. PMID:24367101

  9. Electricity Prices in a Competitive Environment: Marginal Cost Pricing

    EIA Publications

    1997-01-01

    Presents the results of an analysis that focuses on two questions: (1) How are prices for competitive generation services likely to differ from regulated prices if competitive prices are based on marginal costs rather than regulated cost-of-service pricing? (2) What impacts will the competitive pricing of generation services (based on marginal costs) have on electricity consumption patterns, production costs, and the financial integrity of electricity suppliers?

  10. The ethics of dynamic pricing

    SciTech Connect

    Faruqui, Ahmad

    2010-07-15

    Dynamic pricing has garnered much interest among regulators and utilities, since it has the potential for lowering energy costs for society. But the deployment of dynamic pricing has been remarkably tepid. The underlying premise is that dynamic pricing is unfair. But the presumption of unfairness in dynamic pricing rests on an assumption of fairness in today's tariffs. (author)

  11. Competitive Electricity Prices: An Update

    EIA Publications

    1998-01-01

    Illustrates a third impact of the move to competitive generation pricing -- the narrowing of the range of prices across regions of the country. This feature article updates information in Electricity Prices in a Competitive Environment: Marginal Cost Pricing of Generation Services and Financial Status of Electric Utilities.

  12. Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systems

    SciTech Connect

    Kim, K.H.; Park, J.K.; Hwang, K.J.; Kim, S.H.

    1995-08-01

    In this paper, a hybrid model for short-term load forecast that integrates artificial neural networks and fuzzy expert systems is presented. The forecasted load is obtained by passing through two steps. In the first procedure, the artificial neural networks are trained with the load patterns corresponding to the forecasting hour, and the provisional forecasted load is obtained by the trained artificial neural networks. In the second procedure, the fuzzy expert systems modify the provisional forecasted load considering the possibility of load variation due to changes in temperature and the load behavior of holiday. In the test case of 1994 for implementation in short term load forecasting expert system of Korea Electric Power Corporation (KEPCO), the proposed hybrid model provided good forecasting accuracy of the mean absolute percentage errors below 1.3%. The comparison results with exponential smoothing method showed the efficiency and accuracy of the hybrid model.

  13. A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression

    PubMed Central

    2014-01-01

    Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting. PMID:25045738

  14. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, Emmah; Wetterhall, Fredrik; Dutra, Emanuel; Di Giuseppe, Francesca; Pappenberger, Florian

    2014-05-01

    The humanitarian crisis caused by the recent droughts (2008-2009 and 2010-2011) in East Africa have illustrated that the ability to make accurate drought predictions with sufficient lead time is essential. The use of dynamical model forecasts in combination with drought indices, such as the Standardized Precipitation Index (SPI), can potentially to lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for both rain seasons when evaluated against measurements from the available in-situ stations from East Africa. The forecast for October-December rain season has higher skill than for the March-May season. ECMWF forecasts add value to the statistical forecasts produced during the Greater Horn of Africa Climate Outlook Forums (GHACOF), which is the present operational product. Complementing the raw precipitation forecasts with SPI provides additional information on the spatial extent and intensity of the drought event.

  15. Atmospheric composition forecasting in Europe

    NASA Astrophysics Data System (ADS)

    Menut, L.; Bessagnet, B.

    2010-01-01

    The atmospheric composition is a societal issue and, following new European directives, its forecast is now recommended to quantify the air quality. It concerns both gaseous and particles species, identified as potential problems for health. In Europe, numerical systems providing daily air quality forecasts are numerous and, mostly, operated by universities. Following recent European research projects (GEMS, PROMOTE), an organization of the air quality forecast is currently under development. But for the moment, many platforms exist, each of them with strengths and weaknesses. This overview paper presents all existing systems in Europe and try to identify the main remaining gaps in the air quality forecast knowledge. As modeling systems are now able to reasonably forecast gaseous species, and in a lesser extent aerosols, the future directions would concern the use of these systems with ensemble approaches and satellite data assimilation. If numerous improvements were recently done on emissions and chemistry knowledge, improvements are still needed especially concerning meteorology, which remains a weak point of forecast systems. Future directions will also concern the use of these forecast tools to better understand and quantify the air pollution impact on health.

  16. Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences.

    PubMed

    Sabatelli, Lorenzo

    2016-01-01

    Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand. PMID:26999511

  17. Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences

    PubMed Central

    Sabatelli, Lorenzo

    2016-01-01

    Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand. PMID:26999511

  18. Electricity generation modeling and photovoltaic forecasts in China

    NASA Astrophysics Data System (ADS)

    Li, Shengnan

    With the economic development of China, the demand for electricity generation is rapidly increasing. To explain electricity generation, we use gross GDP, the ratio of urban population to rural population, the average per capita income of urban residents, the electricity price for industry in Beijing, and the policy shift that took place in China. Ordinary least squares (OLS) is used to develop a model for the 1979--2009 period. During the process of designing the model, econometric methods are used to test and develop the model. The final model is used to forecast total electricity generation and assess the possible role of photovoltaic generation. Due to the high demand for resources and serious environmental problems, China is pushing to develop the photovoltaic industry. The system price of PV is falling; therefore, photovoltaics may be competitive in the future.

  19. Improving Groundwater Predictions using Seasonal Precipitation Forecasts

    NASA Astrophysics Data System (ADS)

    Almanaseer, N.; Arumugam, S.; Bales, J. D.

    2011-12-01

    This research aims to evaluate the utility of precipitation forecasts in improving groundwater and streamflow predictions at seasonal and monthly time scales using statistical modeling techniques. For this purpose, we select ten groundwater wells from the Groundwater Climate Response Network (GCRN) and nine streamgauges from the Hydro-Climatic Data Network (HCDN) to represent groundwater and surface water variability with minimal anthropogenic influences over Flint River Basin (FRB) in Georgia, U.S. Preliminary analysis shows significant correlation between precipitation forecasts over FRB with observed precipitation (P), streamflow discharges (Q) and depth to groundwater (G). Three statistical models are developed using principle component regression (PCR) and canonical correlation analysis (CCA) with leave-5-out cross-validation to predict winter (JFM) and spring (AMJ) as well as monthly (Jan through Jun) groundwater and streamflow for the selected sites. The three models starts at the end of Dec and uses Oct, Nov and Dec (OND) observed records to predict 2-seasons and 6-months ahead. Model-1 is the "null model" that does not include precipitation forecasts as predictors. It is developed using PCR to predict seasonal and monthly Q and G independently based on previous (Oct. Nov. and Dec; OND) observations of Q or G at a given site without using climate information. Model predictands are JFM, AMJ for seasonal and Jan. through Jun for monthly. Model-2 is also developed using PCR, but it uses the issued at January precipitation forecasts from nine ECHAM 4.5 grid points as additional predictors. Model-3 is developed using CCA and it aims to integrate additional information on the predictands (i.e., groundwater) from adjacent basins to improve the prediction. Model-3 is designed to evaluate the role of climate versus the role groundwater and surface water flows in the selected basins. Finally, comparisons between the three models for each site and across the sites

  20. Forecasting Geomagnetic Conditions in near-Earth space

    NASA Astrophysics Data System (ADS)

    Abunina, M.; Papaioannou, A.; Gerontidou, M.; Paschalis, P.; Abunin, A.; Gaidash, S.; Tsepakina, I.; Malimbayev, A.; Belov, A.; Mavromichalaki, H.; Kryakunova, O.; Velinov, P.

    2013-02-01

    Geomagnetic conditions in near-Earth space have been a constantly evolving scientific field, especially during the latest years when the dependence of our everyday life on space environment has significantly increased. The scientific community managed to implement centers for the continuous monitoring of the geomagnetic conditions which resulted into short and long term forecasting of the planetary geomagnetic index Ap. In this work, the centers that have been established and are in operational mode in Russia (IZMIRAN), Greece (Athens), Kazakhstan (Almaty) and Bulgaria (Sofia) are presented. The methods that have been used for the forecasting of Ap index are demonstrated and the forecasted results in comparison to the actual Ap measurements are also discussed.

  1. Inflow forecasting using Artificial Neural Networks for reservoir operation

    NASA Astrophysics Data System (ADS)

    Chiamsathit, Chuthamat; Adeloye, Adebayo J.; Bankaru-Swamy, Soundharajan

    2016-05-01

    In this study, multi-layer perceptron (MLP) artificial neural networks have been applied to forecast one-month-ahead inflow for the Ubonratana reservoir, Thailand. To assess how well the forecast inflows have performed in the operation of the reservoir, simulations were carried out guided by the systems rule curves. As basis of comparison, four inflow situations were considered: (1) inflow known and assumed to be the historic (Type A); (2) inflow known and assumed to be the forecast (Type F); (3) inflow known and assumed to be the historic mean for month (Type M); and (4) inflow is unknown with release decision only conditioned on the starting reservoir storage (Type N). Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. It was found that Type F inflow situation produced the best performance while Type N was the worst performing. This clearly demonstrates the importance of good inflow information for effective reservoir operation.

  2. Determining the Effects on Residential Electricity Prices and Carbon Emissions of Electricity Market Restructuring in Alberta

    NASA Astrophysics Data System (ADS)

    Jahangir, Junaid Bin

    When electricity restructuring initiatives were introduced in Alberta, and finalized with the institution of retail electricity market competition in 2001, it was argued that the changes would deliver lower electricity prices to residential consumers. However, residential electricity prices in Alberta increased dramatically in 2001, and have never returned to their pre-restructuring levels. Proponents of restructuring argue that electricity prices would have been even higher under continued regulation, citing the effect of considerably higher natural gas prices and the roles of other variables. However, many Alberta residential electricity consumers tend to attribute their higher electricity prices to factors such as market power and manipulation associated with restructuring. Since the effects of restructuring on electricity prices cannot be evaluated by simply comparing prices before and after it occurred, the main objective of this thesis is to determine what electricity prices would have been under continued regulation, and to compare them with what was actually observed. To determine these counterfactual electricity prices, a structural model of the determinants of Alberta residential electricity prices is developed, estimated for the prerestructuring period, and used to forecast (counterfactual) prices in the postrestructuring period. However, in forming these forecasts it is necessary to separately account for changes in explanatory variables that could be viewed as occurring due to the restructuring (endogenous) from those changes that would Since the effects of restructuring on electricity prices cannot be evaluated by simply comparing prices before and after it occurred, the main objective of this thesis is to determine what electricity prices would have been under continued regulation, and to compare them with what was actually observed. To determine these counterfactual electricity prices, a structural model of the determinants of Alberta residential

  3. Economic indicators selection for crime rates forecasting using cooperative feature selection

    NASA Astrophysics Data System (ADS)

    Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Salleh Sallehuddin, Roselina

    2013-04-01

    Features selection in multivariate forecasting model is very important to ensure that the model is accurate. The purpose of this study is to apply the Cooperative Feature Selection method for features selection. The features are economic indicators that will be used in crime rate forecasting model. The Cooperative Feature Selection combines grey relational analysis and artificial neural network to establish a cooperative model that can rank and select the significant economic indicators. Grey relational analysis is used to select the best data series to represent each economic indicator and is also used to rank the economic indicators according to its importance to the crime rate. After that, the artificial neural network is used to select the significant economic indicators for forecasting the crime rates. In this study, we used economic indicators of unemployment rate, consumer price index, gross domestic product and consumer sentiment index, as well as data rates of property crime and violent crime for the United States. Levenberg-Marquardt neural network is used in this study. From our experiments, we found that consumer price index is an important economic indicator that has a significant influence on the violent crime rate. While for property crime rate, the gross domestic product, unemployment rate and consumer price index are the influential economic indicators. The Cooperative Feature Selection is also found to produce smaller errors as compared to Multiple Linear Regression in forecasting property and violent crime rates.

  4. Price smarter on the Net.

    PubMed

    Baker, W; Marn, M; Zawada, C

    2001-02-01

    Companies generally have set prices on the Internet in two ways. Many start-ups have offered untenably low prices in a rush to capture first-mover advantage. Many incumbents have simply charged the same prices on-line as they do off-line. Either way, companies are missing a big opportunity. The fundamental value of the Internet lies not in lowering prices or making them consistent but in optimizing them. After all, if it's easy for customers to compare prices on the Internet, it's also easy for companies to track customers' behavior and adjust prices accordingly. The Net lets companies optimize prices in three ways. First, it lets them set and announce prices with greater precision. Different prices can be tested easily, and customers' responses can be collected instantly. Companies can set the most profitable prices, and they can tap into previously hidden customer demand. Second, because it's so easy to change prices on the Internet, companies can adjust prices in response to even small fluctuations in market conditions, customer demand, or competitors' behavior. Third, companies can use the clickstream data and purchase histories that it collects through the Internet to segment customers quickly. Then it can offer segment-specific prices or promotions immediately. By taking full advantage of the unique possibilities afforded by the Internet to set prices with precision, adapt to changing circumstances quickly, and segment customers accurately, companies can get their pricing right. It's one of the ultimate drivers of e-business success.

  5. Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Mohamed Ismael, Hawa; Vandyck, George Kobina

    The Doraleh Container Terminal (DCT) located in Djibouti has been noted as the most technologically advanced container terminal on the African continent. DCT's strategic location at the crossroads of the main shipping lanes connecting Asia, Africa and Europe put it in a unique position to provide important shipping services to vessels plying that route. This paper aims to forecast container throughput through the Doraleh Container Port in Djibouti by Time Series Analysis. A selection of univariate forecasting models has been used, namely Triple Exponential Smoothing Model, Grey Model and Linear Regression Model. By utilizing the above three models and their combination, the forecast of container throughput through the Doraleh port was realized. A comparison of the different forecasting results of the three models, in addition to the combination forecast is then undertaken, based on commonly used evaluation criteria Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The study found that the Linear Regression forecasting Model was the best prediction method for forecasting the container throughput, since its forecast error was the least. Based on the regression model, a ten (10) year forecast for container throughput at DCT has been made.

  6. Characterizing the uncertainty in river stage forecasts conditional on point forecast values

    NASA Astrophysics Data System (ADS)

    Yan, Jun; Liao, Gong-Yi; Gebremichael, Mekonnen; Shedd, Robert; Vallee, David R.

    2012-12-01

    Uncertainty information about river level forecast is as important as the forecast itself for forecast users. This paper presents a flexible, statistical approach that processes deterministic forecasts into probabilistic forecasts. The model is a smoothly changing conditional distribution of river stage given point forecast and other information available, such as lagged river level at the time of forecasting. The parametric distribution is a four-parameter skewt distribution, with each parameter modeled as a smooth function of the point forecast and the 1 day ago observed river level. The model was applied to 9 years of daily 6 h lead forecasts and 24 h lead forecasts in the warm season and their matching observations at the Plymouth station on the Pemigewasset River in New Hampshire. For each point forecast, the conditional distribution and resulting prediction intervals provide uncertainty information that are potentially very important to forecast users and algorithm developers in decision making and improvement of forecast quality.

  7. Expanding the performance curve of different weather data sources for hydrologic modeling in central Texas: a comparison of ground observations and the Climate Forecast System Reanalysis as watershed model inputs

    NASA Astrophysics Data System (ADS)

    Fuka, D. R.; Collick, A.; Auerbach, D.; Kleinman, P. J. A.; Wagena, M. B.; Sommerlot, A.; Harmel, D.; Easton, Z. M.

    2015-12-01

    Obtaining location specific representative meteorological data can be difficult and time consuming, even though correctly representing the weather is critical to hydrological modeling and watershed management planning. The Climate Forecast System Reanalysis (CFSR) dataset provides continuous, globally-available records that offer a consistent baseline for assessments of candidate weather data, have produced satisfactory hydrological model performance in some temperate and monsoonal locations, as well as have been demonstrated as a solution for ungaged tropical and semi-tropical montane basins. Taking advantage of exceptionally high rainfall data density in USDA-ARS's Reisel experimental watershed. We compared model performance under alternative weather inputs: Climate Forecast System Reanalysis (CFSR) records, a standard public weather station dataset available from the Global Historical Climate Network (GHCN), and a the high density research quality dataset available from the USDA-ARS. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations available from GHCN, especially when stations are more than 10-km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling ungauged watersheds and advancing real-time hydrological modelling.

  8. Oil Prices, Exhaustible Resources, and Economic Growth

    NASA Astrophysics Data System (ADS)

    Hamilton, J. D.

    2012-12-01

    This talk explores details behind the phenomenal increase in global crude oil production over the last century and a half and the implications if that trend should be reversed. I document that a key feature of the growth in production has been exploitation of new geographic areas rather than application of better technology to existing sources, and suggest that the end of that era could come soon. The economic dislocations that historically followed temporary oil supply disruptions are reviewed, and the possible implications of that experience for what the transition era could look like are explored.nnual crude oil production (in thousands of barrels per year) from the states of Pennsylvania and New York combined, 1860-2010. ashed line: actual value for real GDP, 2007-2009. Red line: dynamic conditional forecast as of 2007:Q3 (1- to 5-quarters ahead) based on oil prices using equation (3.8) in Hamilton (2003)

  9. An overview of alternative fossil fuel price and carbon regulation scenarios

    SciTech Connect

    Wiser, Ryan; Bolinger, Mark

    2004-10-01

    The benefits of the Department of Energy's research and development (R&D) efforts have historically been estimated under business-as-usual market and policy conditions. In recognition of the insurance value of R&D, however, the Office of Energy Efficiency and Renewable Energy (EERE) and the Office of Fossil Energy (FE) have been exploring options for evaluating the benefits of their R&D programs under an array of alternative futures. More specifically, an FE-EERE Scenarios Working Group (the Working Group) has proposed to EERE and FE staff the application of an initial set of three scenarios for use in the Working Group's upcoming analyses: (1) a Reference Case Scenario, (2) a High Fuel Price Scenario, which includes heightened natural gas and oil prices, and (3) a Carbon Cap-and-Trade Scenario. The immediate goal is to use these scenarios to conduct a pilot analysis of the benefits of EERE and FE R&D efforts. In this report, the two alternative scenarios being considered by EERE and FE staff--carbon cap-and-trade and high fuel prices--are compared to other scenarios used by energy analysts and utility planners. The report also briefly evaluates the past accuracy of fossil fuel price forecasts. We find that the natural gas prices through 2025 proposed in the FE-EERE Scenarios Working Group's High Fuel Price Scenario appear to be reasonable based on current natural gas prices and other externally generated gas price forecasts and scenarios. If anything, an even more extreme gas price scenario might be considered. The price escalation from 2025 to 2050 within the proposed High Fuel Price Scenario is harder to evaluate, primarily because few existing forecasts or scenarios extend beyond 2025, but, at first blush, it also appears reasonable. Similarly, we find that the oil prices originally proposed by the Working Group in the High Fuel Price Scenario appear to be reasonable, if not conservative, based on: (1) the current forward market for oil, (2) current oil prices

  10. Value of Wind Power Forecasting

    SciTech Connect

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  11. Method Forecasts Global Energy Substitution

    ERIC Educational Resources Information Center

    Chemical and Engineering News, 1975

    1975-01-01

    Describes a model developed to forecast energy demands and determine trends in demand for primary fuels. The energy model essentially considers primary energy sources as competing commodities in a market. (MLH)

  12. Latin American Battery Forecast Report

    SciTech Connect

    Malacon, S.

    1995-12-31

    A forecast of battery production in Latin America is described. The economic influence and political difficulties which have influenced the market are discussed. Data is presented for original equipment shipments and replacement batteries.

  13. Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling.

    PubMed

    Ye, Hao; Beamish, Richard J; Glaser, Sarah M; Grant, Sue C H; Hsieh, Chih-Hao; Richards, Laura J; Schnute, Jon T; Sugihara, George

    2015-03-31

    It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.

  14. A Bayesian Assessment of Seismic Semi-Periodicity Forecasts

    NASA Astrophysics Data System (ADS)

    Nava, F.; Quinteros, C.; Glowacka, E.; Frez, J.

    2016-01-01

    Among the schemes for earthquake forecasting, the search for semi-periodicity during large earthquakes in a given seismogenic region plays an important role. When considering earthquake forecasts based on semi-periodic sequence identification, the Bayesian formalism is a useful tool for: (1) assessing how well a given earthquake satisfies a previously made forecast; (2) re-evaluating the semi-periodic sequence probability; and (3) testing other prior estimations of the sequence probability. A comparison of Bayesian estimates with updated estimates of semi-periodic sequences that incorporate new data not used in the original estimates shows extremely good agreement, indicating that: (1) the probability that a semi-periodic sequence is not due to chance is an appropriate estimate for the prior sequence probability estimate; and (2) the Bayesian formalism does a very good job of estimating corrected semi-periodicity probabilities, using slightly less data than that used for updated estimates. The Bayesian approach is exemplified explicitly by its application to the Parkfield semi-periodic forecast, and results are given for its application to other forecasts in Japan and Venezuela.

  15. Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling.

    PubMed

    Ye, Hao; Beamish, Richard J; Glaser, Sarah M; Grant, Sue C H; Hsieh, Chih-Hao; Richards, Laura J; Schnute, Jon T; Sugihara, George

    2015-03-31

    It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts. PMID:25733874

  16. Three models intercomparison for Quantitative Precipitation Forecast over Calabria

    NASA Astrophysics Data System (ADS)

    Federico, S.; Avolio, E.; Bellecci, C.; Colacino, M.; Lavagnini, A.; Accadia, C.; Mariani, S.; Casaioli, M.

    2004-11-01

    In the framework of the National Project “Sviluppo di distretti industriali per le Osservazioni della Terra” (Development of Industrial Districts for Earth Observations) funded by MIUR (Ministero dell'Università e della Ricerca Scientifica --Italian Ministry of the University and Scientific Research) two operational mesoscale models were set-up for Calabria, the southernmost tip of the Italian peninsula. Models are RAMS (Regional Atmospheric Modeling System) and MM5 (Mesoscale Modeling 5) that are run every day at Crati scrl to produce weather forecast over Calabria (http://www.crati.it). This paper reports model intercomparison for Quantitative Precipitation Forecast evaluated for a 20 month period from 1th October 2000 to 31th May 2002. In addition to RAMS and MM5 outputs, QBOLAM rainfall fields are available for the period selected and included in the comparison. This model runs operationally at “Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici”. Forecasts are verified comparing models outputs with raingauge data recorded by the regional meteorological network, which has 75 raingauges. Large-scale forcing is the same for all models considered and differences are due to physical/numerical parameterizations and horizontal resolutions. QPFs show differences between models. Largest differences are for BIA compared to the other considered scores. Performances decrease with increasing forecast time for RAMS and MM5, whilst QBOLAM scores better for second day forecast.

  17. Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling

    PubMed Central

    Ye, Hao; Beamish, Richard J.; Glaser, Sarah M.; Grant, Sue C. H.; Hsieh, Chih-hao; Richards, Laura J.; Schnute, Jon T.; Sugihara, George

    2015-01-01

    It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner–recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts. PMID:25733874

  18. An application of ensemble/multi model approach for wind power production forecast.

    NASA Astrophysics Data System (ADS)

    Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

    2010-09-01

    The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic

  19. Practical Meteor Stream Forecasting

    NASA Technical Reports Server (NTRS)

    Cooke, William J.; Suggs, Robert M.

    2003-01-01

    Inspired by the recent Leonid meteor storms, researchers have made great strides in our ability to predict enhanced meteor activity. However, the necessary calibration of the meteor stream models with Earth-based ZHRs (Zenith Hourly Rates) has placed emphasis on the terran observer and meteor activity predictions are published in such a manner to reflect this emphasis. As a consequence, many predictions are often unusable by the satellite community, which has the most at stake and the greatest interest in meteor forecasting. This paper suggests that stream modelers need to pay more attention to the needs of this community and publish not just durations and times of maxima for Earth, but everything needed to characterize the meteor stream in and out of the plane of the ecliptic, which, at a minimum, consists of the location of maximum stream density (ZHR) and the functional form of the density decay with distance from this point. It is also suggested that some of the terminology associated with meteor showers may need to be more strictly defined in order to eliminate the perception of crying wolf by meteor scientists. An outburst is especially problematic, as it usually denotes an enhancement by a factor of 2 or more to researchers, but conveys the notion of a sky filled with meteors to satellite operators and the public. Experience has also taught that predicted ZHRs often lead to public disappointment, as these values vastly overestimate what is seen.

  20. Preparing for an Uncertain Forecast

    ERIC Educational Resources Information Center

    Karolak, Eric

    2011-01-01

    Navigating the world of government relations and public policy can be a little like predicting the weather. One can't always be sure what's in store or how it will affect him/her down the road. But there are common patterns and a few basic steps that can help one best prepare for a change in the forecast. Though the forecast is uncertain, early…

  1. Verification of a high-resolution forecasting system of surface minimum, mean and maximum temperature in Calabria for summer 2008

    NASA Astrophysics Data System (ADS)

    Federico, S.; Avolio, E.; Fusto, F.; Niccoli, R.; Bellecci, C.

    2010-09-01

    Gridded high horizontal resolution (2.5 km) forecasts of minimum, mean and maximum temperature are evaluated against gridded analyses at the same horizontal resolution for Calabria, southern Italy. Temperature forecasts are issued at CRATI/ISAC-CNR (meteo.crati.it/previsioni.html) since 2005 by the RAMS (Regional Atmospheric Modeling System) model and, starting from June 2008, the horizontal resolution was enhanced to 2.5 km. Forecast skill and accuracy are determined out to four days for the 2008 summer season (from 6 June to 30 September). Gridded analysis is based on Optimal Interpolation (OI) and uses RAMS first day forecast for minimum, mean and maximum temperatures as background field. Observations from 87 thermometers of the Centro Funzionale - ARPACAL network are used in the analysis system. Cumulative measure oriented statistics are used to quantify forecast errors out to four days. Results show that maximum temperature has the largest root men square error (RMSE), while minimum and mean temperature errors are similar. The RMSE of minimum, mean, and maximum temperature vary from 1.9, 1.7, and 2.2 ° C, respectively, for the first-day forecast, to 2.0, 2.0, and 2.6 ° C for the fourth-day forecast. The forecast skill is analyzed by comparison with persistence forecast. Anomaly correlation (AC) analysis shows that the model is able to catch the day-to-day variations of synoptic and mesoscale features and that the model performance for the fourth-day forecast is still better than one-day persistence forecast. Distributions oriented statistics of forecast and analysis and distributions of forecast conditioned to specific values of analyses are also studied to show common forecast tendencies. Results show that forecast underestimates the analysis for the warmest temperatures and overestimates analysis for the lowest temperatures.

  2. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, E.; Wetterhall, F.; Dutra, E.; Di Giuseppe, F.; Pappenberger, F.

    2013-08-01

    The humanitarian crisis caused by the recent droughts (2008-2009 and 2010-2011) in the East African region have illustrated that the ability to make accurate drought predictions with adequate lead time is essential. The use of dynamical model forecasts and drought indices, such as Standardized Precipitation Index (SPI), promises to lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for both rain seasons when evaluated against measurements from the available in-situ stations from East Africa. The October-December rain season has higher skill that the March-May season. ECMWF forecasts add value to the statistical forecasts produced during the Greater Horn of Africa Climate Outlook Forums (GHACOF) which is the present operational product. Complementing the raw precipitation forecasts with SPI provides additional information on the spatial extend and intensity of the drought event.

  3. Municipal water consumption forecast accuracy

    NASA Astrophysics Data System (ADS)

    Fullerton, Thomas M.; Molina, Angel L.

    2010-06-01

    Municipal water consumption planning is an active area of research because of infrastructure construction and maintenance costs, supply constraints, and water quality assurance. In spite of that, relatively few water forecast accuracy assessments have been completed to date, although some internal documentation may exist as part of the proprietary "grey literature." This study utilizes a data set of previously published municipal consumption forecasts to partially fill that gap in the empirical water economics literature. Previously published municipal water econometric forecasts for three public utilities are examined for predictive accuracy against two random walk benchmarks commonly used in regional analyses. Descriptive metrics used to quantify forecast accuracy include root-mean-square error and Theil inequality statistics. Formal statistical assessments are completed using four-pronged error differential regression F tests. Similar to studies for other metropolitan econometric forecasts in areas with similar demographic and labor market characteristics, model predictive performances for the municipal water aggregates in this effort are mixed for each of the municipalities included in the sample. Given the competitiveness of the benchmarks, analysts should employ care when utilizing econometric forecasts of municipal water consumption for planning purposes, comparing them to recent historical observations and trends to insure reliability. Comparative results using data from other markets, including regions facing differing labor and demographic conditions, would also be helpful.

  4. The Barcelona Dust Forecast Center: The first WMO regional meteorological center specialized on atmospheric sand and dust forecast

    NASA Astrophysics Data System (ADS)

    Basart, Sara; Terradellas, Enric; Cuevas, Emilio; Jorba, Oriol; Benincasa, Francesco; Baldasano, Jose M.

    2015-04-01

    The World Meteorological Organization's Sand and Dust Storm Warning Advisory and Assessment System (WMO SDS-WAS, http://sds-was.aemet.es/) project has the mission to enhance the ability of countries to deliver timely and quality sand and dust storm forecasts, observations, information and knowledge to users through an international partnership of research and operational communities. The good results obtained by the SDS-WAS Northern Africa, Middle East and Europe (NAMEE) Regional Center and the demand of many national meteorological services led to the deployment of operational dust forecast services. On June 2014, the first WMO Regional Meteorological Center Specialized on Atmospheric Sand and Dust Forecast, the Barcelona Dust Forecast Center (BDFC; http://dust.aemet.es/), was publicly presented. The Center operationally generates and distributes predictions for the NAMEE region. The dust forecasts are based on the NMMB/BSC-Dust model developed at the Barcelona Supercomputing Center (BSC-CNS). The present contribution will describe the main objectives and capabilities of BDFC. One of the activities performed by the BDFC is to establish a protocol to routinely exchange products from dust forecast models as dust load, dust optical depth (AOD), surface concentration, surface extinction and deposition. An important step in dust forecasting is the evaluation of the results that have been generated. This process consists of the comparison of the model results with multiple kinds of observations (i.e. AERONET and MODIS) and is aimed to facilitate the understanding of the model capabilities, limitations, and appropriateness for the purpose for which it was designed. The aim of this work is to present different evaluation approaches and to test the use of different observational products in the evaluation system.

  5. Survey of air cargo forecasting techniques

    NASA Technical Reports Server (NTRS)

    Kuhlthan, A. R.; Vermuri, R. S.

    1978-01-01

    Forecasting techniques currently in use in estimating or predicting the demand for air cargo in various markets are discussed with emphasis on the fundamentals of the different forecasting approaches. References to specific studies are cited when appropriate. The effectiveness of current methods is evaluated and several prospects for future activities or approaches are suggested. Appendices contain summary type analyses of about 50 specific publications on forecasting, and selected bibliographies on air cargo forecasting, air passenger demand forecasting, and general demand and modalsplit modeling.

  6. 7 CFR 1000.54 - Equivalent price.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Equivalent price. 1000.54 Section 1000.54 Agriculture... Prices § 1000.54 Equivalent price. If for any reason a price or pricing constituent required for computing the prices described in § 1000.50 is not available, the market administrator shall use a price...

  7. HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts"

    NASA Astrophysics Data System (ADS)

    Wetterhall, F.; Pappenberger, F.; Alfieri, L.; Cloke, H. L.; Thielen-del Pozo, J.; Balabanova, S.; Daňhelka, J.; Vogelbacher, A.; Salamon, P.; Carrasco, I.; Cabrera-Tordera, A. J.; Corzo-Toscano, M.; Garcia-Padilla, M.; Garcia-Sanchez, R. J.; Ardilouze, C.; Jurela, S.; Terek, B.; Csik, A.; Casey, J.; Stankūnavičius, G.; Ceres, V.; Sprokkereef, E.; Stam, J.; Anghel, E.; Vladikovic, D.; Alionte Eklund, C.; Hjerdt, N.; Djerv, H.; Holmberg, F.; Nilsson, J.; Nyström, K.; Sušnik, M.; Hazlinger, M.; Holubecka, M.

    2013-11-01

    Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

  8. Fairness and dynamic pricing: comments

    SciTech Connect

    Hogan, William W.

    2010-07-15

    In ''The Ethics of Dynamic Pricing,'' Ahmad Faruqui lays out a case for improved efficiency in using dynamic prices for retail electricity tariffs and addresses various issues about the distributional effects of alternative pricing mechanisms. The principal contrast is between flat or nearly constant energy prices and time-varying prices that reflect more closely the marginal costs of energy and capacity. The related issues of fairness criteria, contracts, risk allocation, cost allocation, means testing, real-time pricing, and ethical policies of electricity market design also must be considered. (author)

  9. OPEC pricing decisions through 1985

    SciTech Connect

    Krupp, H.W.

    1982-05-01

    Recent developments brought the future of OPEC price decisions under intense scrutiny. Since OPEC's decision in March to support the Saudi marker price and curb crude oil production, oil prices firmed somewhat in the spot markets. Nevertheless, as of the end of April, petroleum markets remained sloppy and the final outcome still remains uncertain. Bankers Trust felt that OPEC would succeed in holding the marker price at $34 a barrel in 1982; through 1985, they predict nominal increases in the price of oil but at a rate lower than inflation. The real price, therefore, will decline modestly for the next few years. 1 table.

  10. A simplified real time method to forecast semi-enclosed basins storm surge

    NASA Astrophysics Data System (ADS)

    Pasquali, D.; Di Risio, M.; De Girolamo, P.

    2015-11-01

    Semi-enclosed basins are often prone to storm surge events. Indeed, their meteorological exposition, the presence of large continental shelf and their shape can lead to strong sea level set-up. A real time system aimed at forecasting storm surge may be of great help to protect human activities (i.e. to forecast flooding due to storm surge events), to manage ports and to safeguard coasts safety. This paper aims at illustrating a simple method able to forecast storm surge events in semi-enclosed basins in real time. The method is based on a mixed approach in which the results obtained by means of a simplified physics based model with low computational costs are corrected by means of statistical techniques. The proposed method is applied to a point of interest located in the Northern part of the Adriatic Sea. The comparison of forecasted levels against observed values shows the satisfactory reliability of the forecasts.

  11. Future Economics of Liver Transplantation: A 20-Year Cost Modeling Forecast and the Prospect of Bioengineering Autologous Liver Grafts

    PubMed Central

    Habka, Dany; Mann, David; Landes, Ronald; Soto-Gutierrez, Alejandro

    2015-01-01

    During the past 20 years liver transplantation has become the definitive treatment for most severe types of liver failure and hepatocellular carcinoma, in both children and adults. In the U.S., roughly 16,000 individuals are on the liver transplant waiting list. Only 38% of them will receive a transplant due to the organ shortage. This paper explores another option: bioengineering an autologous liver graft. We developed a 20-year model projecting future demand for liver transplants, along with costs based on current technology. We compared these cost projections against projected costs to bioengineer autologous liver grafts. The model was divided into: 1) the epidemiology model forecasting the number of wait-listed patients, operated patients and postoperative patients; and 2) the treatment model forecasting costs (pre-transplant-related costs; transplant (admission)-related costs; and 10-year post-transplant-related costs) during the simulation period. The patient population was categorized using the Model for End-Stage Liver Disease score. The number of patients on the waiting list was projected to increase 23% over 20 years while the weighted average treatment costs in the pre-liver transplantation phase were forecast to increase 83% in Year 20. Projected demand for livers will increase 10% in 10 years and 23% in 20 years. Total costs of liver transplantation are forecast to increase 33% in 10 years and 81% in 20 years. By comparison, the projected cost to bioengineer autologous liver grafts is $9.7M based on current catalog prices for iPS-derived liver cells. The model projects a persistent increase in need and cost of donor livers over the next 20 years that’s constrained by a limited supply of donor livers. The number of patients who die while on the waiting list will reflect this ever-growing disparity. Currently, bioengineering autologous liver grafts is cost prohibitive. However, costs will decline rapidly with the introduction of new manufacturing

  12. Fields, Flares, And Forecasts

    NASA Astrophysics Data System (ADS)

    Boucheron, L.; Al-Ghraibah, Amani; McAteer, J.; Cao, H.; Jackiewicz, J.; McNamara, B.; Voelz, D.; Calabro, B.; DeGrave, K.; Kirk, M.; Madadi, A.; Petsov, A.; Taylor, G.

    2011-05-01

    Solar active regions are the source of many energetic and geo-effective events such as solar flares and coronal mass ejections (CMEs). Understanding how these complex source regions evolve and produce these events is of fundamental importance, not only to solar physics, but also to the demands of space weather forecasting. We propose to investigate the physical properties of active region magnetic fields using fractal-, gradient-, neutral line-, emerging flux-, wavelet- and general image-based techniques, and to correlate them to solar activity. The combination of these projects with solarmonitor.org and the international Max Millenium Campaign presents an opportunity for accurate and timely flare predictions for the first time. Many studies have attempted to relate solar flares to their concomitant magnetic field distributions. However, a consistent, causal relationship between the magnetic field on the photosphere and the production of solar flares is unknown. Often the local properties of the active region magnetic field - critical in many theories of activity - are lost in the global definition of their diagnostics, in effect smoothing out variations that occur on small spatial scales. Mindful of this, our overall goal is to create measures that are sensitive to both the global and the small-scale nature of energy storage and release in the solar atmosphere in order to study solar flare prediction. This set of active region characteristics will be automatically explored for discriminating features through the use of feature selection methods. Such methods search a feature space while optimizing a criterion - the prediction of a flare in this case. The large size of the datasets used in this project make it well suited for an exploration of a large feature space. This work is funded through a New Mexico State University Interdisciplinary Research Grant.

  13. Lead and the London Metal Exchange — a happy marriage? The outlook for prices and pricing issues confronting the lead industry

    NASA Astrophysics Data System (ADS)

    Keen, A.

    The outlook for the supply-demand balance for refined lead is addressed and takes into account the growing non-fundamental forces on price determination. The market for refined lead is presently experiencing its first year of surplus since the major crisis of the early 1990s. Earlier in the decade, the dissolution of the Soviet Union and recession in developed economies led to a significant rise in London Metal Exchange (LME) stocks. An acceleration absorbed these stocks in an 18-month period in the mid-1990s, and LME lead prices reacted to the market deficit by peaking above US900. Since then the market has balanced, yet prices have declined steadily to less that 50% of their peak levels. It is argued that, on fundamental grounds, prices have fallen below justified levels. As much of the reason for this depression between 1997 and 1999 has been the generally depressive effect of the Asian economic crisis on financial markets, the level of lead prices may now be due for a correction. Other metals have begun to increase during the first half of 1999 and lead, given its neutral fundamental outlook, is now poised to participate in the generally more buoyant moods across LME metals. An increase of approximately 10% in average LME 3-month settlement prices is forecast and will result in annual average prices of US 570/tonne over the course of 1999. Monthly averages and spot prices are predicted to exceed this level, particularly during peak third-quarter demand.

  14. Price transparency: building community trust.

    PubMed

    Clarke, Richard L

    2007-01-01

    With the push from policymakers, payers, and consumers for hospitals to make their prices public, healthcare executives need to recognize two central issues related to price transparency: 1) meaningful price transparency involves helping patients and consumers understand their financial obligation for an episode of care, and 2) price transparency is key to the most critical success strategy for healthcare providers: building trust. This article reviews the history of pricing and billing practices and explores why price transparency is not easily achieved in today's environment. Pricing is a mystery even to those of us who work in the field, yet despite its complexity, the call for price transparency is not going to go away. For transparency, the goal should be to establish a rational pricing system that is easily explainable and justified to all stakeholders. Healthcare executives must make pricing a priority, understand cost, develop a pricing philosophy, understand the overall revenue requirements, examine market conditions and prices, and set up systems for review. A rational process of price setting should enhance community trust. In this matter there is nothing less at stake than the hearts of our community members. PMID:17405387

  15. An application of ensemble/multi model approach for wind power production forecasting

    NASA Astrophysics Data System (ADS)

    Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S.

    2011-02-01

    The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.

  16. A feature fusion based forecasting model for financial time series.

    PubMed

    Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

    2014-01-01

    Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

  17. A Feature Fusion Based Forecasting Model for Financial Time Series

    PubMed Central

    Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

    2014-01-01

    Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

  18. Modular learning models in forecasting natural phenomena.

    PubMed

    Solomatine, D P; Siek, M B

    2006-03-01

    Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input space, and may be trained on a subset of training set. Many algorithms for allocating such regions to local models typically do this in automatic fashion. In forecasting natural processes, however, domain experts want to bring in more knowledge into such allocation, and to have certain control over the choice of models. This paper presents a number of approaches to building modular models based on various types of splits of training set and combining the models' outputs (hard splits, statistically and deterministically driven soft combinations of models, 'fuzzy committees', etc.). An issue of including a domain expert into the modeling process is also discussed, and new algorithms in the class of model trees (piece-wise linear modular regression models) are presented. Comparison of the algorithms based on modular local modeling to the more traditional 'global' learning models on a number of benchmark tests and river flow forecasting problems shows their higher accuracy and transparency of the resulting models. PMID:16531005

  19. Statistical earthquake focal mechanism forecasts

    NASA Astrophysics Data System (ADS)

    Kagan, Yan Y.; Jackson, David D.

    2014-04-01

    Forecasts of the focal mechanisms of future shallow (depth 0-70 km) earthquakes are important for seismic hazard estimates and Coulomb stress, and other models of earthquake occurrence. Here we report on a high-resolution global forecast of earthquake rate density as a function of location, magnitude and focal mechanism. In previous publications we reported forecasts of 0.5° spatial resolution, covering the latitude range from -75° to +75°, based on the Global Central Moment Tensor earthquake catalogue. In the new forecasts we have improved the spatial resolution to 0.1° and the latitude range from pole to pole. Our focal mechanism estimates require distance-weighted combinations of observed focal mechanisms within 1000 km of each gridpoint. Simultaneously, we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms, using the method of Kagan & Jackson proposed in 1994. This average angle reveals the level of tectonic complexity of a region and indicates the accuracy of the prediction. The procedure becomes problematical where longitude lines are not approximately parallel, and where shallow earthquakes are so sparse that an adequate sample spans very large distances. North or south of 75°, the azimuths of points 1000 km away may vary by about 35°. We solved this problem by calculating focal mechanisms on a plane tangent to the Earth's surface at each forecast point, correcting for the rotation of the longitude lines at the locations of earthquakes included in the averaging. The corrections are negligible between -30° and +30° latitude, but outside that band uncorrected rotations can be significantly off. Improved forecasts at 0.5° and 0.1° resolution are posted at http://eq.ess.ucla.edu/kagan/glob_gcmt_index.html.

  20. Use of wind power forecasting in operational decisions.

    SciTech Connect

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help

  1. 2050: A Pricing Odyssey

    SciTech Connect

    Faruqui, Ahmad

    2006-10-15

    The author uses the Rip Van Winkle approach favored by marketers to gaze, clear-eyed, into the future - say, the year 2050 - to visualize alternative demand-response possibilities. Dare we go California Dreamin' of a distant utopia - or is it inevitable that pricing myopia will keep us from attaining the fulfillment of many of our career goals? (author)

  2. Pricing Decisions: A Game.

    ERIC Educational Resources Information Center

    Read, Simon

    1989-01-01

    Describes a game that illustrates the effects of pricing on profit. Students compete against each other in an imaginary industry and become familiar with decision-making processes. Depicts the gameboard, how to make it, and how to use it. (GG)

  3. The Price Is Right?

    ERIC Educational Resources Information Center

    Schaffhauser, Dian

    2012-01-01

    There's something about textbook prices that generates outrage in ways that other college expenses, such as housing and technology fees, don't. Maybe it's the shock felt by new students when faced with a $900 bill after getting their textbooks for free in K-12. Maybe it's the awful realization that $40,000 in tuition and board doesn't even cover…

  4. Price bundling packs pitfalls.

    PubMed

    Jaklevic, M C

    1995-02-27

    Hospitals thought bundling of healthcare services under one all-inclusive price would have great appeal to payers, bringing in more business. But instead, the concept has brought disappointment as the expected boost in patient volume has failed to materialize. PMID:10140286

  5. Sixth special price report: world petroleum-product prices

    SciTech Connect

    Not Available

    1984-01-11

    Twice annually, Energy Detente accesses its own twice-monthly supplement, the Fuel Price/Tax Series, for an overview of how prices and taxes for refined petroleum products from natural gas to asphalt for end-users are changing. In this issue, it also updates its review of individual nations' pricing as to controls or free-market practices. The front cover chart reveals that, in terms of US dollars, the world average price of regular leaded (RL) gasoline is US $1.63, and high-octane leaded is US $1.78 - a difference of about 9%. A table details RL retail prices, the taxes pertaining to them, the percentages that those taxes are of prices, plus the January 1983 prices and the price change in US dollars over the period. In terms of US dollars, most price changes since January 1983 appear negative - particularly in the cases of Bolivia, El Salvador, and Nicaragua. A view of actual market price changes in terms of national currencies is depicted in another table. The fuel price/tax series and the principal industrial fuel prices are presented for January 1984 for countries of the Eastern Hemisphere.

  6. Option pricing: Stock price, stock velocity and the acceleration Lagrangian

    NASA Astrophysics Data System (ADS)

    Baaquie, Belal E.; Du, Xin; Bhanap, Jitendra

    2014-12-01

    The industry standard Black-Scholes option pricing formula is based on the current value of the underlying security and other fixed parameters of the model. The Black-Scholes formula, with a fixed volatility, cannot match the market's option price; instead, it has come to be used as a formula for generating the option price, once the so called implied volatility of the option is provided as additional input. The implied volatility not only is an entire surface, depending on the strike price and maturity of the option, but also depends on calendar time, changing from day to day. The point of view adopted in this paper is that the instantaneous rate of return of the security carries part of the information that is provided by implied volatility, and with a few (time-independent) parameters required for a complete pricing formula. An option pricing formula is developed that is based on knowing the value of both the current price and rate of return of the underlying security which in physics is called velocity. Using an acceleration Lagrangian model based on the formalism of quantum mathematics, we derive the pricing formula for European call options. The implied volatility of the market can be generated by our pricing formula. Our option price is applied to foreign exchange rates and equities and the accuracy is compared with Black-Scholes pricing formula and with the market price.

  7. Higher Education Prices and Price Indexes. 1975 Supplement.

    ERIC Educational Resources Information Center

    Halstead, D. Kent

    Higher Education price in index data for fiscal years 1971 through 1975 are presented. The supplement is published yearly shortly after the fiscal year to which the latest data refer, and the index values refer to the entire year, not any specific month of the year. The basic study, "Higher Education Prices and Price Indexes," presents complete…

  8. The Mediterranean Forecasting System: recent developments

    NASA Astrophysics Data System (ADS)

    Tonani, Marina; Oddo, Paolo; Korres, Gerasimos; Clementi, Emanuela; Dobricic, Srdjan; Drudi, Massimiliano; Pistoia, Jenny; Guarnieri, Antonio; Romaniello, Vito; Girardi, Giacomo; Grandi, Alessandro; Bonaduce, Antonio; Pinardi, Nadia

    2014-05-01

    ) forcing provided by the COSMO-MED system (provided by the Italian Meteorological Office), have been performed and a pre-operational 3-day forecast production system has been developed. The comparison between this system and the official one forced by the ECMWF NWP data will be discussed.

  9. Communicating Storm Surge Forecast Uncertainty

    NASA Astrophysics Data System (ADS)

    Troutman, J. A.; Rhome, J.

    2015-12-01

    When it comes to tropical cyclones, storm surge is often the greatest threat to life and property along the coastal United States. The coastal population density has dramatically increased over the past 20 years, putting more people at risk. Informing emergency managers, decision-makers and the public about the potential for wind driven storm surge, however, has been extremely difficult. Recently, the Storm Surge Unit at the National Hurricane Center in Miami, Florida has developed a prototype experimental storm surge watch/warning graphic to help communicate this threat more effectively by identifying areas most at risk for life-threatening storm surge. This prototype is the initial step in the transition toward a NWS storm surge watch/warning system and highlights the inundation levels that have a 10% chance of being exceeded. The guidance for this product is the Probabilistic Hurricane Storm Surge (P-Surge) model, which predicts the probability of various storm surge heights by statistically evaluating numerous SLOSH model simulations. Questions remain, however, if exceedance values in addition to the 10% may be of equal importance to forecasters. P-Surge data from 2014 Hurricane Arthur is used to ascertain the practicality of incorporating other exceedance data into storm surge forecasts. Extracting forecast uncertainty information through analyzing P-surge exceedances overlaid with track and wind intensity forecasts proves to be beneficial for forecasters and decision support.

  10. CME Ensemble Forecasting - A Primer

    NASA Astrophysics Data System (ADS)

    Pizzo, V. J.; de Koning, C. A.; Cash, M. D.; Millward, G. H.; Biesecker, D. A.; Codrescu, M.; Puga, L.; Odstrcil, D.

    2014-12-01

    SWPC has been evaluating various approaches for ensemble forecasting of Earth-directed CMEs. We have developed the software infrastructure needed to support broad-ranging CME ensemble modeling, including composing, interpreting, and making intelligent use of ensemble simulations. The first step is to determine whether the physics of the interplanetary propagation of CMEs is better described as chaotic (like terrestrial weather) or deterministic (as in tsunami propagation). This is important, since different ensemble strategies are to be pursued under the two scenarios. We present the findings of a comprehensive study of CME ensembles in uniform and structured backgrounds that reveals systematic relationships between input cone parameters and ambient flow states and resulting transit times and velocity/density amplitudes at Earth. These results clearly indicate that the propagation of single CMEs to 1 AU is a deterministic process. Thus, the accuracy with which one can forecast the gross properties (such as arrival time) of CMEs at 1 AU is determined primarily by the accuracy of the inputs. This is no tautology - it means specifically that efforts to improve forecast accuracy should focus upon obtaining better inputs, as opposed to developing better propagation models. In a companion paper (deKoning et al., this conference), we compare in situ solar wind data with forecast events in the SWPC operational archive to show how the qualitative and quantitative findings presented here are entirely consistent with the observations and may lead to improved forecasts of arrival time at Earth.

  11. Forecasting seasonal outbreaks of influenza.

    PubMed

    Shaman, Jeffrey; Karspeck, Alicia

    2012-12-11

    Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.

  12. Advances in Solar Power Forecasting

    NASA Astrophysics Data System (ADS)

    Haupt, S. E.; Kosovic, B.; Drobot, S.

    2014-12-01

    The National Center for Atmospheric Research and partners are building a blended SunCast Solar Power Forecasting system. This system includes several short-range nowcasting models and improves upon longer range numerical weather prediction (NWP) models as part of the "Public-Private-Academic Partnership to Advance Solar Power Forecasting." The nowcasting models being built include statistical learning models that include cloud regime prediction, multiple sky imager-based advection models, satellite image-based advection models, and rapid update NWP models with cloud assimilation. The team has also integrated new modules into the Weather Research and Forecasting Model (WRF) to better predict clouds, aerosols, and irradiance. The modules include a new shallow convection scheme; upgraded physics parameterizations of clouds; new radiative transfer modules that specify GHI, DNI, and DIF prediction; better satellite assimilation methods; and new aerosol estimation methods. These new physical models are incorporated into WRF-Solar, which is then integrated with publically available NWP models via the Dynamic Integrated Forecast (DICast) system as well as the Nowcast Blender to provide seamless forecasts at partner utility and balancing authority commercial solar farms. The improvements will be described and results to date discussed.

  13. Personal Computer Price and Performance.

    ERIC Educational Resources Information Center

    Crawford, Walt

    1993-01-01

    Discusses personal computer price trends since 1986; describes offerings and prices for four direct-market suppliers, i.e., Dell CompuAdd, PC Brand, and Gateway 2000; and discusses overall value and price/performance ratios. Tables and graphs chart value over time. (EA)

  14. Pricing of GPO Sales Publications.

    ERIC Educational Resources Information Center

    Schwarzkopf, LeRoy C.

    This report analyzes the pricing policy of the Government Printing Office (GPO) for publications sold to the public. It discusses the sharp rise in prices for GPO sales publications from November 1972 through 1975. This is a detailed report which expands on the summary report prepared by the author as chairman of the Pricing Subcommittee, GPO…

  15. Price Discrimination: A Classroom Experiment

    ERIC Educational Resources Information Center

    Aguiló, Paula; Sard, Maria; Tugores, Maria

    2016-01-01

    In this article, the authors describe a classroom experiment aimed at familiarizing students with different types of price discrimination (first-, second-, and third-degree price discrimination). During the experiment, the students were asked to decide what tariffs to set as monopolists for each of the price discrimination scenarios under…

  16. Forecasting Model for IPTV Service in Korea Using Bootstrap Ridge Regression Analysis

    NASA Astrophysics Data System (ADS)

    Lee, Byoung Chul; Kee, Seho; Kim, Jae Bum; Kim, Yun Bae

    The telecom firms in Korea are taking new step to prepare for the next generation of convergence services, IPTV. In this paper we described our analysis on the effective method for demand forecasting about IPTV broadcasting. We have tried according to 3 types of scenarios based on some aspects of IPTV potential market and made a comparison among the results. The forecasting method used in this paper is the multi generation substitution model with bootstrap ridge regression analysis.

  17. Statistical Short-Range Forecast Guidance for Cloud Ceilings Over the Shuttle Landing Facility

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred C.

    2001-01-01

    This report describes the results of the AMU's Short-Range Statistical Forecasting task. The cloud ceiling forecast over the Shuttle Landing Facility (SLF) is a critical element in determining whether a Shuttle should land. Spaceflight Meteorology Group (SMG) forecasters find that ceilings at the SLF are challenging to forecast. The AMU was tasked to develop ceiling forecast equations to minimize the challenge. Studies in the literature that showed success in improving short-term forecasts of ceiling provided the basis for the AMU task. A 20-year record of cool-season hourly surface observations from stations in east-central Florida was used for the equation development. Two methods were used: an observations-based (OBS) method that incorporated data from all stations, and a persistence climatology (PCL) method used as the benchmark. Equations were developed for 1-, 2-, and 3-hour lead times at each hour of the day. A comparison between the two methods indicated that the OBS equations performed well and produced an improvement over the PCL equations. Therefore, the conclusion of the AMU study is that OBS equations produced more accurate forecasts than the PCL equations, and can be used in operations. They provide another tool with which to make the ceiling forecasts that are critical to safe Shuttle landings at KSC.

  18. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    NASA Astrophysics Data System (ADS)

    Mittermaier, M. P.

    2008-05-01

    A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP) verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used. The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  19. Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

    PubMed

    Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  20. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    PubMed Central

    Dai, Wensheng

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740

  1. Impact of High Resolution SST Data on Regional Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Case, Jonathon; LaFontaine, Frank; Vazquez, Jorge; Mattocks, Craig

    2010-01-01

    Past studies have shown that the use of coarse resolution SST products such as from the real-time global (RTG) SST analysis[1] or other coarse resolution once-a-day products do not properly portray the diurnal variability of fluxes of heat and moisture from the ocean that drive the formation of low level clouds and precipitation over the ocean. For example, the use of high resolution MODIS SST composite [2] to initialize the Advanced Research Weather Research and Forecast (WRF) (ARW) [3] has been shown to improve the prediction of sensible weather parameters in coastal regions [4][5}. In an extend study, [6] compared the MODIS SST composite product to the RTG SST analysis and evaluated forecast differences for a 6 month period from March through August 2007 over the Florida coastal regions. In a comparison to buoy data, they found that that the MODIS SST composites reduced the bias and standard deviation over that of the RTG data. These improvements led to significant changes in the initial and forecasted heat fluxes and the resulting surface temperature fields, wind patterns, and cloud distributions. They also showed that the MODIS composite SST product, produced for the Terra and Aqua satellite overpass times, captured a component of the diurnal cycle in SSTs not represented in the RTG or other one-a-day SST analyses. Failure to properly incorporate these effects in the WRF initialization cycle led to temperature biases in the resulting short term forecasts. The forecast impact was limited in some situations however, due to composite product inaccuracies brought about by data latency during periods of long-term cloud cover. This paper focuses on the forecast impact of an enhanced MODIS/AMSR-E composite SST product designed to reduce inaccuracies due data latency in the MODIS only composite product.

  2. Higher prices in Jamaica.

    PubMed

    1982-03-01

    Price increases in the Jamaica CSM program went into effect on August 31, 1981. The program began in 1975. While the need for higher prices has been under discussion for the past 3 years, this is the 1st time the requisite approval from the Jamaica Price Commission has been obtained. The Jamaica National Family Planning Board (JNFPB) reports that the Panther 3-pack (condom) is up US$0.15 to US$0.30. Each Perle package (oral contraceptive) was increased by US$0.20. Single cycle Perle now sells for US$0.50, and 3-pack Perle sells for US$1.10. The 6-year price stagnation experienced by the CSM program resulted in a decreasing operational budget as program costs continued to rise. Marketing costs alone during this period escalated by 100-300%. For example, Panther pop-up display cartons cost the project US 16U each in 1975. By 1979 the same product cost US 49U. Newspaper advertisements have increased from the 1975 cost of US$68.00 to nearly $200.00 per placement. The overall inflation rate in Jamaica during the last 5 years has averaged more than 20% annually. In the face of these rising costs, outlet expansion for Perle has been prevented, wholesaler margins have been unavailable, and new retailer training has been discontinued. It is projected that the new prices will result in an annual increased revenues of US$80,000 which will be used to reinstate these essential marketing activities. The JNFPB is also planning to introduce a Panther 12-pack and Panther strips to the CSM product line. According to Marketing Manager Aston Evans, "We believe the public is now ready for this type of packaging" which is scheduled to be available soon. Panther is presently only available in a 3-pack, but annual sales have been steady. The new 12-pack will be stocked on supermarket shelves to provide higher product visibility and wider distribution. The selling price has been set as US$1.20 and is expected to yield a 25% increase in sales during the 1st year. A complete sales promotion

  3. Verification of Ensemble Forecasts for the New York City Operations Support Tool

    NASA Astrophysics Data System (ADS)

    Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

    2012-12-01

    forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

  4. Smooth Sailing for Weather Forecasting

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Through a cooperative venture with NASA's Stennis Space Center, WorldWinds, Inc., developed a unique weather and wave vector map using space-based radar satellite information and traditional weather observations. Called WorldWinds, the product provides accurate, near real-time, high-resolution weather forecasts. It was developed for commercial and scientific users. In addition to weather forecasting, the product's applications include maritime and terrestrial transportation, aviation operations, precision farming, offshore oil and gas operations, and coastal hazard response support. Target commercial markets include the operational maritime and aviation communities, oil and gas providers, and recreational yachting interests. Science applications include global long-term prediction and climate change, land-cover and land-use change, and natural hazard issues. Commercial airlines have expressed interest in the product, as it can provide forecasts over remote areas. WorldWinds, Inc., is currently providing its product to commercial weather outlets.

  5. Aggregate vehicle travel forecasting model

    SciTech Connect

    Greene, D.L.; Chin, Shih-Miao; Gibson, R.

    1995-05-01

    This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

  6. ALFA: Automated load forecasting assistant

    SciTech Connect

    Jabbour, K.; Riveros, J.F.V.; Landsbergen, D.; Meyer, W.

    1988-08-01

    ALFA, an expert system for forecasting short term demand for electricity is presented. ALFA is in operation at the new Energy Management System center at Niagara Mohawk Power Corporation in Upstate New York, generating the real time hourly load forecasts up to 48 hours in advance. ALFA uses an extensive 10 year historical data base of hourly observations of 12 weather variables and load, and a rule base that takes into account daily, weekly, and seasonal variations of load, as well as holidays, special events, and load growth. A satellite interface for the real-time acquisition of weather data, and the machine-operator interface are also discussed.

  7. Acquisition forecast: Fiscal year 1995

    NASA Technical Reports Server (NTRS)

    1995-01-01

    This volume includes projections of all anticipated FY95, and beyond, NASA contract actions above $25,000 that small and small disadvantaged businesses may be able to perform under direct contract with the government or as subcontractors. The forecast consolidates anticipated procurements at each NASA center into an agencywide report, with the aim of increasing industries' advance knowledge of NASA requirements and enhancing competition in contracting. Each center forecast report is divided into three principal categories of procurement: research and development, services, and supplies and equipment.

  8. GEM: Statistical weather forecasting procedure

    NASA Technical Reports Server (NTRS)

    Miller, R. G.

    1983-01-01

    The objective of the Generalized Exponential Markov (GEM) Program was to develop a weather forecast guidance system that would: predict between 0 to 6 hours all elements in the airways observations; respond instantly to the latest observed conditions of the surface weather; process these observations at local sites on minicomputing equipment; exceed the accuracy of current persistence predictions at the shortest prediction of one hour and beyond; exceed the accuracy of current forecast model output statistics inside eight hours; and be capable of making predictions at one location for all locations where weather information is available.

  9. Alcohol in Greenland 1951–2010: consumption, mortality, prices

    PubMed Central

    Aage, Hans

    2012-01-01

    Background Fluctuations in alcohol consumption in Greenland have been extreme since alcohol became available to the Greenland Inuit in the 1950s, increasing from low levels in the 1950s to very high levels in the 1980s – about twice as high as alcohol consumption in Denmark. Since then, consumption has declined, and current consumption is slightly below alcohol consumption in Denmark, while alcohol prices are far above Danish prices. Objective Description of historical trends and possible causal connections of alcohol prices, alcohol consumption and alcohol-related mortality in Greenland 1951–2010 as a background for the evaluation of the impact of various types of policy. Design Time series for Greenland 1951–2010 for alcohol prices, consumption and mortality are compiled, and variation and correlations are discussed in relation to various policies aimed at limiting alcohol consumption. Corresponding time series for Denmark 1906–2010 are presented for comparison. Results The trends in alcohol prices and consumption followed each other rather closely until the 1990s in Greenland and the 1980s in Denmark. At this time, consumption stabilised while prices decreased further, but the effect of prices upon consumption is strong, also in recent years. A trend in Greenlandic mortality similar to consumption is discernible, but not significant. Among alcohol-related deaths cirrhosis of the liver is less prevalent whilst accidents are more prevalent than in Denmark. Conclusions The effect of alcohol excise taxes and rationing upon consumption is evident. The stabilisation and subsequent decline in consumption since the mid-1990s, while alcohol prices decreased persistently, does not preclude continued effects of prices. On the contrary, price effects have been neutralised by other stronger causes. Whether these are government anti-alcohol campaigns or a cultural change is not clear. PMID:23256091

  10. Cost Validation Using PRICE H

    NASA Technical Reports Server (NTRS)

    Jack, John; Kwan, Eric; Wood, Milana

    2011-01-01

    PRICE H was introduced into the JPL cost estimation tool set circa 2003. It became more available at JPL when IPAO funded the NASA-wide site license for all NASA centers. PRICE H was mainly used as one of the cost tools to validate proposal grassroots cost estimates. Program offices at JPL view PRICE H as an additional crosscheck to Team X (JPL Concurrent Engineering Design Center) estimates. PRICE H became widely accepted ca, 2007 at JPL when the program offices moved away from grassroots cost estimation for Step 1 proposals. PRICE H is now one of the key cost tools used for cost validation, cost trades, and independent cost estimates.

  11. Forecasting Energy Market Contracts by Ambit Processes: Empirical Study and Numerical Results

    PubMed Central

    Di Persio, Luca; Marchesan, Michele

    2014-01-01

    In the present paper we exploit the theory of ambit processes to develop a model which is able to effectively forecast prices of forward contracts written on the Italian energy market. Both short-term and medium-term scenarios are considered and proper calibration procedures as well as related numerical results are provided showing a high grade of accuracy in the obtained approximations when compared with empirical time series of interest. PMID:27437500

  12. Forecasting Energy Market Contracts by Ambit Processes: Empirical Study and Numerical Results.

    PubMed

    Di Persio, Luca; Marchesan, Michele

    2014-01-01

    In the present paper we exploit the theory of ambit processes to develop a model which is able to effectively forecast prices of forward contracts written on the Italian energy market. Both short-term and medium-term scenarios are considered and proper calibration procedures as well as related numerical results are provided showing a high grade of accuracy in the obtained approximations when compared with empirical time series of interest.

  13. Buying stagnates; prices slide

    SciTech Connect

    1994-03-01

    This article is an overview of Uranium transactions during the period January-February 1994. Trading volume and prices are given for conversion trades, SWUs, U3O8, and spot market activities. Due to a wait-and-see attitude pending the modification of the Suspension Agreement, volume during this period was limited to four contracts: two in the spot market and two in the enrichment market.

  14. Forecast communication through the newspaper Part 1: Framing the forecaster

    NASA Astrophysics Data System (ADS)

    Harris, Andrew J. L.

    2015-04-01

    This review is split into two parts both of which address issues of forecast communication of an environmental disaster through the newspaper during a period of crisis. The first part explores the process by which information passes from the scientist or forecaster, through the media filter, to the public. As part of this filter preference, omission, selection of data, source, quote and story, as well as placement of the same information within an individual piece or within the newspaper itself, can serve to distort the message. The result is the introduction of bias and slant—that is, the message becomes distorted so as to favor one side of the argument against another as it passes through the filter. Bias can be used to support spin or agenda setting, so that a particular emphasis becomes placed on the story which exerts an influence on the reader's judgment. The net result of the filter components is either a negative (contrary) or positive (supportive) frame. Tabloidization of the news has also resulted in the use of strong, evocative, exaggerated words, headlines and images to support a frame. I illustrate these various elements of the media filter using coverage of the air space closure due to the April 2010 eruption of Eyjafjallajökull (Iceland). Using the British press coverage of this event it is not difficult to find examples of all media filter elements, application of which resulted in bias against the forecast and forecaster. These actors then became named and blamed. Within this logic, it becomes only too easy for forecasters and scientists to be framed in a negative way through blame culture. The result is that forecast is framed in such a way so as to cause the forecaster to be blamed for all losses associated with the loss-causing event. Within the social amplification of risk framework (SARF), this can amplify a negative impression of the risk, the event and the response. However, actions can be taken to avoid such an outcome. These actions

  15. Increases in consumer cost sharing redirect patient volumes and reduce hospital prices for orthopedic surgery.

    PubMed

    Robinson, James C; Brown, Timothy T

    2013-08-01

    Some employers are implementing reference-pricing benefit designs, which establish limits on the amount they will pay for some procedures covered by employer-sponsored insurance. Employees are required to pay the difference between the employer's contribution limit and the actual price received by the hospital. These initiatives encourage patients to select low-price facilities and indirectly encourage facilities to reduce prices to increase patient volume. We evaluated the impact of reference pricing on the use of and prices paid for knee and hip replacement surgery by members of the California Public Employees' Retirement System (CalPERS) from 2008 to 2012, using enrollees in Anthem Blue Cross as a comparison group. In the first year after implementation, surgical volumes for CalPERS members increased by 21.2 percent at low-price facilities and decreased by 34.3 percent at high-price facilities. Prices charged to CalPERS members declined by 5.6 percent at low-price facilities and by 34.3 percent at high-price facilities. Our analysis indicates that in 2011 reference pricing accounted for $2.8 million in savings for CalPERS and $0.3 million in lower cost sharing for CalPERS members.

  16. Trading Network Predicts Stock Price

    NASA Astrophysics Data System (ADS)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-01

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  17. Trading network predicts stock price.

    PubMed

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  18. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

  19. Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

    NASA Astrophysics Data System (ADS)

    Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

    2010-02-01

    This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

  20. Accuracy of forecasts in strategic intelligence

    PubMed Central

    Mandel, David R.; Barnes, Alan

    2014-01-01

    The accuracy of 1,514 strategic intelligence forecasts abstracted from intelligence reports was assessed. The results show that both discrimination and calibration of forecasts was very good. Discrimination was better for senior (versus junior) analysts and for easier (versus harder) forecasts. Miscalibration was mainly due to underconfidence such that analysts assigned more uncertainty than needed given their high level of discrimination. Underconfidence was more pronounced for harder (versus easier) forecasts and for forecasts deemed more (versus less) important for policy decision making. Despite the observed underconfidence, there was a paucity of forecasts in the least informative 0.4–0.6 probability range. Recalibrating the forecasts substantially reduced underconfidence. The findings offer cause for tempered optimism about the accuracy of strategic intelligence forecasts and indicate that intelligence producers aim to promote informativeness while avoiding overstatement. PMID:25024176

  1. Error growth in operational ECMWF forecasts

    NASA Technical Reports Server (NTRS)

    Kalnay, E.; Dalcher, A.

    1985-01-01

    A parameterization scheme used at the European Centre for Medium Range Forecasting to model the average growth of the difference between forecasts on consecutive days was extended by including the effect of error growth on forecast model deficiencies. Error was defined as the difference between the forecast and analysis fields during the verification time. Systematic and random errors were considered separately in calculating the error variance for a 10 day operational forecast. A good fit was obtained with measured forecast errors and a satisfactory trend was achieved in the difference between forecasts. Fitting six parameters to forecast errors and differences that were performed separately for each wavenumber revealed that the error growth rate grew with wavenumber. The saturation error decreased with the total wavenumber and the limit of predictability, i.e., when error variance reaches 95 percent of saturation, decreased monotonically with the total wavenumber.

  2. The key to better times is Opec pricing discipline

    SciTech Connect

    Crouse, P.C. )

    1989-02-01

    According to the author, 1988 proved again that Opec's ability to control world oil markets in tenuous at best. Oil analysts had trouble determining direction of the cartel, with forecasts showing a wide range of possibilities for oil prices. In the last half of the year, concern about a long-term collapse in oil prices sent many U.S. producers to the sidelines with drilling activity languishing at 911 rigs running at the end of November. Most active rigs were looking for natural gas, further complicating U.S. oil reserve replenishment. Opec gradually lost control of world oil markets in 1988. Opec impotence will continue unless non-Opec producers cooperate to cut output, global oil demand increases significantly, or members finally begin to seriously address the critical issue of adhering strictly to production quotas. The author discusses the status of OPEC and U.S. petroleum in regard to current U.S. and worldwide economic conditions.

  3. Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

    NASA Astrophysics Data System (ADS)

    Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

    2013-04-01

    Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

  4. 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.

  5. Forecasting for energy and chemical decision analysis

    SciTech Connect

    Cazalet, E.G.

    1984-08-01

    This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

  6. Forecasting Consumer Adoption of Information Technology and Services--Lessons from Home Video Forecasting.

    ERIC Educational Resources Information Center

    Klopfenstein, Bruce C.

    1989-01-01

    Describes research that examined the strengths and weaknesses of technological forecasting methods by analyzing forecasting studies made for home video players. The discussion covers assessments and explications of correct and incorrect forecasting assumptions, and their implications for forecasting the adoption of home information technologies…

  7. Improved forecasting of thermospheric densities using multi-model ensembles

    NASA Astrophysics Data System (ADS)

    Elvidge, Sean; Godinez, Humberto C.; Angling, Matthew J.

    2016-07-01

    This paper presents the first known application of multi-model ensembles to the forecasting of the thermosphere. A multi-model ensemble (MME) is a method for combining different, independent models. The main advantage of using an MME is to reduce the effect of model errors and bias, since it is expected that the model errors will, at least partly, cancel. The MME, with its reduced uncertainties, can then be used as the initial conditions in a physics-based thermosphere model for forecasting. This should increase the forecast skill since a reduction in the errors of the initial conditions of a model generally increases model skill. In this paper the Thermosphere-Ionosphere Electrodynamic General Circulation Model (TIE-GCM), the US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar Exosphere 2000 (NRLMSISE-00), and Global Ionosphere-Thermosphere Model (GITM) have been used to construct the MME. As well as comparisons between the MMEs and the "standard" runs of the model, the MME densities have been propagated forward in time using the TIE-GCM. It is shown that thermospheric forecasts of up to 6 h, using the MME, have a reduction in the root mean square error of greater than 60 %. The paper also highlights differences in model performance between times of solar minimum and maximum.

  8. Worldwide satellite market demand forecast

    NASA Technical Reports Server (NTRS)

    Bowyer, J. M.; Frankfort, M.; Steinnagel, K. M.

    1981-01-01

    The forecast is for the years 1981 - 2000 with benchmark years at 1985, 1990 and 2000. Two typs of markets are considered for this study: Hardware (worldwide total) - satellites, earth stations and control facilities (includes replacements and spares); and non-hardware (addressable by U.S. industry) - planning, launch, turnkey systems and operations. These markets were examined for the INTELSAT System (international systems and domestic and regional systems using leased transponders) and domestic and regional systems. Forecasts were determined for six worldwide regions encompassing 185 countries using actual costs for existing equipment and engineering estimates of costs for advanced systems. Most likely (conservative growth rate estimates) and optimistic (mid range growth rate estimates) scenarios were employed for arriving at the forecasts which are presented in constant 1980 U.S. dollars. The worldwide satellite market demand forecast predicts that the market between 181 and 2000 will range from $35 to $50 billion. Approximately one-half of the world market, $16 to $20 billion, will be generated in the United States.

  9. Forecasting phenology under global warming.

    PubMed

    Ibáñez, Inés; Primack, Richard B; Miller-Rushing, Abraham J; Ellwood, Elizabeth; Higuchi, Hiroyoshi; Lee, Sang Don; Kobori, Hiromi; Silander, John A

    2010-10-12

    As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953-2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology. PMID:20819816

  10. Understanding and Forecasting Ethnolinguistic Vitality

    ERIC Educational Resources Information Center

    Karan, Mark E.

    2011-01-01

    Forecasting of ethnolinguistic vitality can only be done within a well-functioning descriptive and explanatory model of the dynamics of language stability and shift. It is proposed that the Perceived Benefit Model of Language Shift, used with a taxonomy of language shift motivations, provides that model. The model, based on individual language…

  11. Premier Forecasting Center Avoids Ax

    NASA Astrophysics Data System (ADS)

    Simpson, Sarah

    2004-03-01

    Last fall, the U.S. Senate proposed eliminating all 2004 funding for NOAA's Space Environment Center (SEC), but fortunately for the world's premier space weather forecasting center and its myriad customers, the Senate did not get its way. When the full Congress passed the final budget on 22 January, the center's budget for the year was at least restored-at least partially.

  12. Wavelet-based Evapotranspiration Forecasts

    NASA Astrophysics Data System (ADS)

    Bachour, R.; Maslova, I.; Ticlavilca, A. M.; McKee, M.; Walker, W.

    2012-12-01

    Providing a reliable short-term forecast of evapotranspiration (ET) could be a valuable element for improving the efficiency of irrigation water delivery systems. In the last decade, wavelet transform has become a useful technique for analyzing the frequency domain of hydrological time series. This study shows how wavelet transform can be used to access statistical properties of evapotranspiration. The objective of the research reported here is to use wavelet-based techniques to forecast ET up to 16 days ahead, which corresponds to the LANDSAT 7 overpass cycle. The properties of the ET time series, both physical and statistical, are examined in the time and frequency domains. We use the information about the energy decomposition in the wavelet domain to extract meaningful components that are used as inputs for ET forecasting models. Seasonal autoregressive integrated moving average (SARIMA) and multivariate relevance vector machine (MVRVM) models are coupled with the wavelet-based multiresolution analysis (MRA) results and used to generate short-term ET forecasts. Accuracy of the models is estimated and model robustness is evaluated using the bootstrap approach.

  13. Military needs and forecast, 2

    NASA Technical Reports Server (NTRS)

    Goldstayn, Alan B.

    1986-01-01

    FORECAST 2 has accomplished its objectives of identifying high leverage technologies for corporate Air Force review. Implementation is underway with emphasis on restructuring existing programs and programming resources in the FY88 BES/FY89 POM. Many joint service/agency opportunities exist.

  14. Volcanic forcing in decadal forecasts

    NASA Astrophysics Data System (ADS)

    Ménégoz, Martin; Doblas-Reyes, Francisco; Guemas, Virginie; Asif, Muhammad; Prodhomme, chloe

    2016-04-01

    Volcanic eruptions can significantly impact the climate system, by injecting large amounts of particles into the stratosphere. By reflecting backward the solar radiation, these particles cool the troposphere, and by absorbing the longwave radiation, they warm the stratosphere. As a consequence of this radiative forcing, the global mean surface temperature can decrease by several tenths of degrees. However, large eruptions are also associated to a complex dynamical response of the climate system that is particularly tricky do understand regarding the low number of available observations. Observations seem to show an increase of the positive phases of the Northern Atlantic Oscillation (NAO) the two winters following large eruptions, associated to positive temperature anomalies over the Eurasian continent. The summers following large eruptions are generally particularly cold, especially over the continents of the Northern Hemisphere. Overall, it is really challenging to forecast the climate response to large eruptions, as it is both modulated by, and superimposed to the climate background conditions, largely driven themselves by internal variability at seasonal to decadal scales. This work describes the additional skill of a forecast system used for seasonal and decadal predictions when it includes observed volcanic forcing over the last decades. An idealized volcanic forcing that could be used for real-time forecasts is also evaluated. This work consists in a base for forecasts that will be performed in the context of the next large volcanic eruption.

  15. In Brief: Forecasting meningitis threats

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2008-12-01

    The University Corporation for Atmospheric Research (UCAR), in conjunction with a team of health and weather organizations, has launched a project to provide weather forecasts to medical officials in Africa to help reduce outbreaks of meningitis. The forecasts will enable local health care providers to target vaccination programs more effectively. In 2009, meteorologists with the National Center for Atmospheric Research, which is managed by UCAR, will begin issuing 14-day forecasts of atmospheric conditions in Ghana. Later, UCAR plans to work closely with health experts from several African countries to design and test a decision support system to provide health officials with useful meteorological information. ``By targeting forecasts in regions where meningitis is a threat, we may be able to help vulnerable populations. Ultimately, we hope to build on this project and provide information to public health programs battling weather-related diseases in other parts of the world,'' said Rajul Pandya, director of UCAR's Community Building Program. Funding for the project comes from a $900,000 grant from Google.org, the philanthropic arm of the Internet search company.

  16. Severe Weather Forecast Decision Aid

    NASA Technical Reports Server (NTRS)

    Bauman, William H., III; Wheeler, Mark

    2005-01-01

    The Applied Meteorology Unit developed a forecast tool that provides an assessment of the likelihood of local convective severe weather for the day in order to enhance protection of personnel and material assets of the 45th Space Wing Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC).

  17. Severe Weather Forecast Decision Aid

    NASA Technical Reports Server (NTRS)

    Bauman, William H., III; Wheeler, Mark M.; Short, David A.

    2005-01-01

    This report presents a 15-year climatological study of severe weather events and related severe weather atmospheric parameters. Data sources included local forecast rules, archived sounding data, Cloud-to-Ground Lightning Surveillance System (CGLSS) data, surface and upper air maps, and two severe weather event databases covering east-central Florida. The local forecast rules were used to set threat assessment thresholds for stability parameters that were derived from the sounding data. The severe weather events databases were used to identify days with reported severe weather and the CGLSS data was used to differentiate between lightning and non-lightning days. These data sets provided the foundation for analyzing the stability parameters and synoptic patterns that were used to develop an objective tool to aid in forecasting severe weather events. The period of record for the analysis was May - September, 1989 - 2003. The results indicate that there are certain synoptic patterns more prevalent on days with severe weather and some of the stability parameters are better predictors of severe weather days based on locally tuned threat values. The results also revealed the stability parameters that did not display any skill related to severe weather days. An interactive web-based Severe Weather Decision Aid was developed to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters, CGLSS data, and synoptic-scale dynamics. The tool will be tested and evaluated during the 2005 warm season.

  18. Seasonal Streamflow Forecasts for African Basins

    NASA Astrophysics Data System (ADS)

    Serrat-Capdevila, A.; Valdes, J. B.; Wi, S.; Roy, T.; Roberts, J. B.; Robertson, F. R.; Demaria, E. M.

    2015-12-01

    Using high resolution downscaled seasonal meteorological forecasts we present the development and evaluation of seasonal hydrologic forecasts with Stakeholder Agencies for selected African basins. The meteorological forecasts are produced using the Bias Correction and Spatial Disaggregation (BCSD) methodology applied to NMME hindcasts (North American Multi-Model Ensemble prediction system) to generate a bootstrap resampling of plausible weather forecasts from historical observational data. This set of downscaled forecasts is then used to drive hydrologic models to produce a range of forecasts with uncertainty estimates suitable for water resources planning in African pilot basins (i.e. Upper Zambezi, Mara Basin). In an effort to characterize the utility of these forecasts, we will present an evaluation of these forecast ensembles over the pilot basins, and discuss insights as to their operational applicability by regional actors. Further, these forecasts will be contrasted with those from a standard Ensemble Streamflow Prediction (ESP) approach to seasonal forecasting. The case studies presented here have been developed in the setting of the NASA SERVIR Applied Sciences Team and within the broader context of operational seasonal forecasting in Africa. These efforts are part of a dialogue with relevant planning and management agencies and institutions in Africa, which are in turn exploring how to best use uncertain forecasts for decision making.

  19. Student Enrollment Forecasting in Georgia: Lessons Learned.

    ERIC Educational Resources Information Center

    Chan, Tak Cheung; Pool, Harbison; Davidson, Ronald

    2002-01-01

    Study of school district enrollment forecasting in Georgia finds, for example, differences in forecasting accuracy between large and small school districts, the widespread use of the Cohort Survival Technique, a lag in small school districts' use of sophisticated, computer-based enrollment forecasting models. (Contains 34 references.) (PKP)

  20. Can Business Students Forecast Their Own Grade?

    ERIC Educational Resources Information Center

    Hossain, Belayet; Tsigaris, Panagiotis

    2013-01-01

    This study examines grade expectations of two groups of business students for their final course mark. We separate students that are on average "better" forecasters on the basis of them not making significant forecast errors during the semester from those students that are poor forecasters of their final grade. We find that the better…

  1. Beat the Instructor: An Introductory Forecasting Game

    ERIC Educational Resources Information Center

    Snider, Brent R.; Eliasson, Janice B.

    2013-01-01

    This teaching brief describes a 30-minute game where student groups compete in-class in an introductory time-series forecasting exercise. The students are challenged to "beat the instructor" who competes using forecasting techniques that will be subsequently taught. All forecasts are graphed prior to revealing the randomly generated…

  2. Comparison of Arctic clouds between European Center for Medium-Range Weather Forecasts simulations and Atmospheric Radiation Measurement Climate Research Facility long-term observations at the North Slope of Alaska Barrow site

    NASA Astrophysics Data System (ADS)

    Zhao, Ming; Wang, Zhien

    2010-12-01

    This study evaluated the European Center for Medium-Range Weather Forecasts (ECMWF) model-simulated clouds and boundary layer (BL) properties based upon Atmospheric Radiation Measurement Climate Research Facility observations at the North Slope of Alaska site during 1999-2007. The ECMWF model-simulated near-surface humidity had seasonal dependent biases as large as 20%, while also experiencing difficulty representing BL temperature inversion height and strength during the transition seasons. Although the ECMWF model captured the seasonal variation of surface heat fluxes, it had sensible heat flux biases over 20 W m-2 in most of the cold months. Furthermore, even though the model captured the general seasonal variations of low-level cloud fraction (LCF) and liquid water path (LWP), it still overestimated the LCF by 20% or more and underestimated the LWP over 50% in the cold season. On average, the ECMWF model underestimated LWP by ˜30 g m-2 but more accurately predicted ice water path for BL clouds. For BL mixed-phase clouds, the model predicted water-ice mass partition was significantly lower than the observations, largely due to the temperature dependence of water-ice mass partition used in the model. The ECMWF model captured the general response of cloud fraction and LWP on large-scale vertical motion changes but overpredicted the magnitude of the difference, especially for LWP. The new cloud and BL schemes of the ECMWF model that were implemented after 2003 only resulted in minor improvements in BL cloud simulations in summer. These results indicate that significant improvements in cold season BL and mixed-phase cloud processes in the model are needed.

  3. A Wind Forecasting System for Energy Application

    NASA Astrophysics Data System (ADS)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated

  4. The COMESEP SEP forecast tool

    NASA Astrophysics Data System (ADS)

    Dierckxsens, Mark; Tziotziou, Kostas; Dalla, Silvia; Patsou, Ioanna; Marsh, Mike; Crosby, Norma; Malandraki, Olga; Lygeros, Nik

    2014-05-01

    The FP7 COMESEP (COronal Mass Ejections and Solar Energetic Particles: forecasting the space weather impact) project developed tools for forecasting geomagnetic storms and solar energetic particle (SEP) radiation storms. Here we present the SEP forecast tool which provides a prediction of the probability for an SEP event to occur near Earth following the real-time observation of an X-ray flare, and estimates the most likely impact if such an event would occur. The tool has been operational on the COMESEP alert system (http://www.comesep.eu/alert) since November 2013. Alerts are provided for proton storms with E>10 MeV and E>60 MeV in the form of a risk level, combining the probability and expected impact. The predictions are based on a statistical analysis of SEP events and their parent solar activity during Solar Cycle 23. The input parameters are the flare intensity and longitude location, as well as the CME speed and width, if an observed CME can be associated with the flare. This information is also received through the COMESEP system. Alerts are based on the available information when triggered and are subsequently updated if more information becomes available. The forecast for the probability, the impact and risk level are evaluated on events from solar cycles 22 and 24. The effect of including flare location and CME parameters is also studied. The performance of the SEP forecast tool within the COMESEP alert system will be described. This work has received funding from the European Commission FP7 Project COMESEP (263252)

  5. Forecasting wind power production from a wind farm using the RAMS model

    NASA Astrophysics Data System (ADS)

    Tiriolo, L.; Torcasio, R. C.; Montesanti, S.; Sempreviva, A. M.; Calidonna, C. R.; Transerici, C.; Federico, S.

    2015-04-01

    The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading. This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography around the site is complex and the horizontal resolution of the wind forecast has an important role. To explore this point we compared the performance of two 48 h wind power forecasts using the winds predicted by the Regional Atmospheric Modeling System (RAMS) for the year 2011. The two forecasts differ only for the horizontal resolution of the RAMS model, which is 3 km (R3) and 12 km (R12), respectively. Both forecasts use the 12 UTC analysis/forecast cycle issued by the European Centre for Medium range Weather Forecast (ECMWF) as initial and boundary conditions. As an additional comparison, the results of R3 and R12 are compared with those of the ECMWF Integrated Forecasting System (IFS), whose horizontal resolution over Central Italy is about 25 km at the time considered in this paper. v Because wind observations were not available for the site, the power curve for the whole wind farm was derived from the ECMWF wind operational analyses available at 00:00, 06:00, 12:00 and 18:00 UTC for the years 2010 and 2011. Also, for R3 and R12, the RAMS model was used to refine the horizontal resolution of the ECMWF analyses by a two-years hindcast at 3 and 12 km horizontal resolution, respectively. The R3 reduces the RMSE of the predicted wind power of the whole 2011 by 5% compared to R12, showing an impact of the meteorological model horizontal resolution in forecasting the wind power for the specific site.

  6. Comparing complementary NWP model performance for hydrologic forecasting for the river Rhine in an operational setting

    NASA Astrophysics Data System (ADS)

    Davids, Femke; den Toom, Matthijs

    2016-04-01

    This paper investigates the performance of complementary NWP models for hydrologic forecasting for the river Rhine, a large river catchment in Central Europe. An operational forecasting system, RWsOS-Rivieren, produces daily forecasts of discharges and water levels at the Water Management Centre Netherlands. A combination of HBV (rainfall-runoff) and SOBEK (hydrodynamic routing) models is used to produce simulations and forecasts for the catchment. Data assimilation is applied both to the model state of SOBEK and to model outputs. The primary function of the operational forecasting system is to provide reliable and accurate forecasts during periods of high water. The secondary main function is producing daily predictions for water management and water transport in The Netherlands. In addition, predicting water levels during drought periods is becoming increasingly important as well. At this moment several complementary deterministic and ensemble NWP models are used to provide the forecasters with predictions with varied initial conditions, such as ICON, ICON-EU Nest, ECMWF-DET, ECMWF-EPS, HiRLAM, COSMO-LEPS and GLAMEPS. ICON and ICON-EU have recently replaced DWD-GME and DWD COSMO-EU. These models provide weather forecasts with different lengths of lead times and also different periods of operational usage. A direct and quantitative comparison is therefore challenging. Nevertheless, it is important to investigate the suitability of the different NWP models for certain lead times and certain weather situations to help support the hydrological forecasters make an informed forecast during an operational crisis. A hindcast study will investigate the performance of these models in the operational system for different lead times and focusing on periods of both high and low water for Lobith, the location of entry of the river Rhine into The Netherlands.

  7. A Course in Economic Forecasting: Rationale and Content.

    ERIC Educational Resources Information Center

    Loomis, David G.; Cox, James E., Jr.

    2000-01-01

    Discusses four reasons why economic forecasting courses are important: (1) forecasting skills are in demand by businesses; (2) forecasters are in demand; (3) forecasting courses have positive externalities; (4) and forecasting provides a real-world context. Describes what should be taught in an economic forecasting course. (CMK)

  8. Pricing equity warrants with a promised lowest price in Merton's jump-diffusion model

    NASA Astrophysics Data System (ADS)

    Xiao, Weilin; Zhang, Xili

    2016-09-01

    Motivated by the empirical evidence of jumps in the dynamics of firm behavior, this paper considers the problem of pricing equity warrants in the presence of a promised lowest price when the price of the underlying asset follows the Merton's jump-diffusion process. Using the Martingale approach, we propose a valuation model of equity warrants based on the firm value, its volatility, and parameters of the jump component, which are not directly observable. To implement our pricing model empirically, this paper also provides a promising estimation method for obtaining these desired variables based on observable data, such as stock prices and the book value of total liability. We conduct an empirical study to ascertain the performance of our proposed model using the data of Changdian warrant collected from 25 May 2006 (the listing date) to 29 January 2007 (the expiration date). Furthermore, the comparison of traditional models (such as the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model) with our model is presented. From the empirical study, we can see that the mean absolute error of our pricing model is 16.75%. By contrast, the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model applied to the same warrant produce mean absolute errors of 92.24%, 45.38%, 87.34%, 76.12%, respectively. Thus both the dilution effect and the jump feature cannot be ignored in determining the valuation of equity warrants.

  9. Advances in Global Flood Forecasting Systems

    NASA Astrophysics Data System (ADS)

    Thielen-del Pozo, J.; Pappenberger, F.; Burek, P.; Alfieri, L.; Kreminski, B.; Muraro, D.

    2012-12-01

    A trend of increasing number of heavy precipitation events over many regions in the world during the past century has been observed (IPCC, 2007), but conclusive results on a changing frequency or intensity of floods have not yet been established. However, the socio-economic impact particularly of floods is increasing at an alarming trend. Thus anticipation of severe events is becoming a key element of society to react timely to effectively reduce socio-economic damage. Anticipation is essential on local as well as on national or trans-national level since management of response and aid for major disasters requires a substantial amount of planning and information on different levels. Continental and trans-national flood forecasting systems already exist. The European Flood Awareness System (EFAS) has been developed in close collaboration with the National services and is going operational in 2012, enhancing the national forecasting centres with medium-range probabilistic added value information while at the same time providing the European Civil Protection with harmonised information on ongoing and upcoming floods for improved aid management. Building on experiences and methodologies from EFAS, a Global Flood Awareness System (GloFAS) has now been developed jointly between researchers from the European Commission Joint Research Centre (JRC) and the European Centre for Medium-Range Weather Forecast (ECWMF). The prototype couples HTESSEL, the land-surface scheme of the ECMWF NWP model with the LISFLOOD hydrodynamic model for the flow routing in the river network. GloFAS is set-up on global scale with horizontal grid spacing of 0.1 degree. The system is driven with 51 ensemble members from VAREPS with a time horizon of 15 days. In order to allow for the routing in the large rivers, the coupled model is run for 45 days assuming zero rainfall after day 15. Comparison with observations have shown that in some rivers the system performs quite well while in others the hydro

  10. The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models

    NASA Astrophysics Data System (ADS)

    Demirel, M. C.; Booij, M. J.; Hoekstra, A. Y.

    2015-01-01

    This paper investigates the skill of 90-day low-flow forecasts using two conceptual hydrological models and one data-driven model based on Artificial Neural Networks (ANNs) for the Moselle River. The three models, i.e. HBV, GR4J and ANN-Ensemble (ANN-E), all use forecasted meteorological inputs (precipitation P and potential evapotranspiration PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low-flow forecasts for five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the models. The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the models are compared based on their skill of low-flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90-day-ahead low flows in the very dry year 2003 without precipitation data. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET

  11. Strategic pricing: hitting the mark with pricing strategies. Part 1.

    PubMed

    Porn, L; Manning, M

    1988-01-01

    Efforts by government and business to reduce healthcare expenditures by fostering competition and reducing utilization have combined to redefine the basic economic structure of the healthcare delivery system. Increased competition among providers has prompted an increased awareness of strategic pricing as a means of achieving institutional goals and objectives. In this article, the first in a three-part series on strategic pricing, the authors examine some of the key theoretical considerations related to pricing strategies for healthcare providers. Future articles will examine practical applications as they relate to package pricing, discounting, per diem systems, and capitation arrangements.

  12. Internet Access and Pricing: Sorting Out the Options.

    ERIC Educational Resources Information Center

    Fowler, Thomas B.

    1997-01-01

    Discusses Internet access and pricing options. Highlights include restructuring of the telecommunications industry; current methods of access; economics of high-speed access; the impact of cheap Internet access; long-term possibilities; and a table that provides a comparison of Internet access methods. (LRW)

  13. Intercomparison of mesoscale meteorological models for precipitation forecasting

    NASA Astrophysics Data System (ADS)

    Richard, E.; Cosma, S.; Benoit, R.; Binder, P.; Buzzi, A.; Kaufmann, P.

    In the framework of the RAPHAEL EU project, a series of past heavy precipitation events has been simulated with different meteorological models. Rainfall hindcasts and forecasts have been produced by four models in use at various meteorological services or research centres of Italy, Canada, France and Switzerland. The paper is focused on the comparison of the computed precipitation fields with the available surface observations. The comparison is carried out for three meteorological situations which lead to severe flashflood over the Toce-Ticino catchment in Italy (6599 km2) or the Ammer catchment (709 km2) in Germany. The results show that all four models reproduced the occurrence of these heavy precipitation events. The accuracy of the computed precipitation appears to be more case-dependent than model-dependent. The sensitivity of the computed rainfall to the boundary conditions (hindcast v. forecast) was found to be rather weak, indicating that a flood forecasting system based upon a numerical meteo-hydrological simulation could be feasible in an operational context.

  14. Spatial competition and price formation

    NASA Astrophysics Data System (ADS)

    Nagel, Kai; Shubik, Martin; Paczuski, Maya; Bak, Per

    2000-12-01

    We look at price formation in a retail setting, that is, companies set prices, and consumers either accept prices or go someplace else. In contrast to most other models in this context, we use a two-dimensional spatial structure for information transmission, that is, consumers can only learn from nearest neighbors. Many aspects of this can be understood in terms of generalized evolutionary dynamics. In consequence, we first look at spatial competition and cluster formation without price. This leads to establishement size distributions, which we compare to reality. After some theoretical considerations, which at least heuristically explain our simulation results, we finally return to price formation, where we demonstrate that our simple model with nearly no organized planning or rationality on the part of any of the agents indeed leads to an economically plausible price.

  15. Critique of the mid-range energy forecasting, system oil and gas supply models

    SciTech Connect

    Patton, W.P.

    1980-10-01

    The Mid-Range Energy Forecasting System (MEFS) is a model used by the Department of Energy to forecast domestic production, consumption and price for conventional energy sources on a regional basis over a period of 5 to 15 years. Among the energy sources included in the model are oil, gas and other petroleum fuels, coal, uranium, and electricity. Final consumption of alternative energy sources is broken into end-use categories, such as residential, commercial and industrial uses. Regional prices for all energy sources are calculated by iteratively equating domestic supply and demand. The purpose of this paper is to assess the ability of the Oil and Gas Supply Submodels of MEFS to reliably and accurately project oil and gas supply curves, which are used in the integrating model, along with fuel demand curves to estimate market price. The reliability and accuracy of the oil and gas model cannot be judged by comparing its predictions against actual observations because those observations have not yet occurred. The reliability and reasonableness of the oil and gas supply model can be judged, however, by analyzing how well its assumptions and predictions correspond to accepted economic principles. This is the approach taken in this critique. The remainder of this paper describes the general structure of the oil and gas supply model and how it functions to project the quantity of oil and gas forthcoming at given prices in a particular year, then discusses the economic soundness of the model, and finally suggests model changes to improve its performance.

  16. An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

    NASA Astrophysics Data System (ADS)

    Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

    2013-12-01

    One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset

  17. Ionospheric data assimilation and forecasting during storms

    NASA Astrophysics Data System (ADS)

    Chartier, Alex T.; Matsuo, Tomoko; Anderson, Jeffrey L.; Collins, Nancy; Hoar, Timothy J.; Lu, Gang; Mitchell, Cathryn N.; Coster, Anthea J.; Paxton, Larry J.; Bust, Gary S.

    2016-01-01

    Ionospheric storms can have important effects on radio communications and navigation systems. Storm time ionospheric predictions have the potential to form part of effective mitigation strategies to these problems. Ionospheric storms are caused by strong forcing from the solar wind. Electron density enhancements are driven by penetration electric fields, as well as by thermosphere-ionosphere behavior including Traveling Atmospheric Disturbances and Traveling Ionospheric Disturbances and changes to the neutral composition. This study assesses the effect on 1 h predictions of specifying initial ionospheric and thermospheric conditions using total electron content (TEC) observations under a fixed set of solar and high-latitude drivers. Prediction performance is assessed against TEC observations, incoherent scatter radar, and in situ electron density observations. Corotated TEC data provide a benchmark of forecast accuracy. The primary case study is the storm of 10 September 2005, while the anomalous storm of 21 January 2005 provides a secondary comparison. The study uses an ensemble Kalman filter constructed with the Data Assimilation Research Testbed and the Thermosphere Ionosphere Electrodynamics General Circulation Model. Maps of preprocessed, verticalized GPS TEC are assimilated, while high-latitude specifications from the Assimilative Mapping of Ionospheric Electrodynamics and solar flux observations from the Solar Extreme Ultraviolet Experiment are used to drive the model. The filter adjusts ionospheric and thermospheric parameters, making use of time-evolving covariance estimates. The approach is effective in correcting model biases but does not capture all the behavior of the storms. In particular, a ridge-like enhancement over the continental USA is not predicted, indicating the importance of predicting storm time electric field behavior to the problem of ionospheric forecasting.

  18. Monthly streamflow forecasting using Gaussian Process Regression

    NASA Astrophysics Data System (ADS)

    Sun, Alexander Y.; Wang, Dingbao; Xu, Xianli

    2014-04-01

    Streamflow forecasting plays a critical role in nearly all aspects of water resources planning and management. In this work, Gaussian Process Regression (GPR), an effective kernel-based machine learning algorithm, is applied to probabilistic streamflow forecasting. GPR is built on Gaussian process, which is a stochastic process that generalizes multivariate Gaussian distribution to infinite-dimensional space such that distributions over function values can be defined. The GPR algorithm provides a tractable and flexible hierarchical Bayesian framework for inferring the posterior distribution of streamflows. The prediction skill of the algorithm is tested for one-month-ahead prediction using the MOPEX database, which includes long-term hydrometeorological time series collected from 438 basins across the U.S. from 1948 to 2003. Comparisons with linear regression and artificial neural network models indicate that GPR outperforms both regression methods in most cases. The GPR prediction of MOPEX basins is further examined using the Budyko framework, which helps to reveal the close relationships among water-energy partitions, hydrologic similarity, and predictability. Flow regime modification and the resulting loss of predictability have been a major concern in recent years because of climate change and anthropogenic activities. The persistence of streamflow predictability is thus examined by extending the original MOPEX data records to 2012. Results indicate relatively strong persistence of streamflow predictability in the extended period, although the low-predictability basins tend to show more variations. Because many low-predictability basins are located in regions experiencing fast growth of human activities, the significance of sustainable development and water resources management can be even greater for those regions.

  19. On the reliability of seasonal climate forecasts.

    PubMed

    Weisheimer, A; Palmer, T N

    2014-07-01

    Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time.

  20. How hospitals approach price transparency.

    PubMed

    Houk, Scott; Cleverley, James O

    2014-09-01

    A survey of finance leaders found that hospitals with lower charges were more likely than other hospitals to emphasize making prices defensible rather than simply transparent. Finance leaders of hospitals with higher charges were more likely to express concern that price transparency would cause a reduction in hospital revenue by forcing them to lower charges. Those respondents said commercial payers likely will have to agree to renegotiate contracts for price transparency to be a financially viable proposition. PMID:25647890