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Sample records for prices forecast comparison aeo

  1. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) 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 play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO

  2. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) 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 play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we

  3. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, 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 play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below

  4. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 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 itigating 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.

  5. 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

  6. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) 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), differences in capital costs and O&M expenses, 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 or nuclear 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; 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, uranium, and

  7. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  8. Uranium price forecasting methods

    SciTech Connect

    Fuller, D.M.

    1994-03-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again.

  9. 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.

  10. 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.

  11. Energy price forecasting: a look at two methods

    SciTech Connect

    Brown, R.J.

    1983-07-01

    Energy price forecasts can be effectively employed for cost-effectiveness analyses of all types of products which use energy or affect energy use. This report details two of the best-known methods in which forecasts may be incorporated into savings analysis.

  12. 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

  13. Oil price forecasting in the 1980`s: What went wrong?

    SciTech Connect

    Huntington, H.G.

    1994-12-31

    This paper reviews forecasts of oil prices over the 1980s that were made in 1980. It identifies the sources of errors due to such factors as erogenous GNP assumptions, resource supply conditions outside the cartel, and demand adjustments to price changes. Through 1986, the first two factors account for most of the difference between projected and actual prices. After 1986, misspecification of the demand adjustments becomes a particularly troublesome problem. 21 refs., 7 figs., 6 tabs.

  14. 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.

  15. 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.

  16. Price forecast in the competitive electricity market by support vector machine

    NASA Astrophysics Data System (ADS)

    Gao, Ciwei; Bompard, Ettore; Napoli, Roberto; Cheng, Haozhong

    2007-08-01

    The electricity market has been widely introduced in many countries all over the world and the study on electricity price forecast technology has drawn a lot of attention. In this paper, with different parameter C i and ε i assigned to each training data, the flexible C i Support Vector Regression (SVR) model is developed in terms of the particularity of the price forecast in electricity market. For Day Ahead Market (DAM) price forecast, the load, time of use index and index of day type are taken as the major factors to characterize the market price, therefore, they are selected as the inputs for the flexible SVR forecast model. For the long-term price forecast, we take the reserve margin Rm, HHI and the fuel price index as the inputs, since they are the major factors that drive the market price variation in long run. For short-term price forecast, besides the detailed analysis with the young Italian electricity market, the new model is tested on the experimental stage of the Spanish market, the New York market and the New England market. The long-term forecast with the SVR model presented is justified by the forecast with the data from the Long Run Market Simulator (LREMS).

  17. Using artificial neural networks to forecast the futures prices of crude oil

    NASA Astrophysics Data System (ADS)

    Khazem, Hassan A.

    Crude oil is the commodity de jour and its pricing is of paramount importance to the layperson as well as to any responsible government. However, one of the main challenges facing econometric pricing models is the forecasting accuracy. Historically, linear and non-linear time series models were used. Although, a great success was achieved in that regard, yet there were no definite and universal conclusions drawn. The crude oil forecasting field is still wide open for improvement, especially when applying different forecasting models and alternative techniques. Toward this end, the proposed research implemented Artificial Neural Network models (ANN). The models will forecast the daily crude oil futures prices from 1996 to 2006, listed in NYMEX. Due to the nonlinearity presented by the test results of the crude oil pricing, it is expected that the ANN models will improve forecasting accuracy. An evaluation of the outcomes of the forecasts among different models was done to authenticate that this is undeniably the situation.

  18. 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.

  19. Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets

    SciTech Connect

    Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

    2005-06-30

    The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

  20. 16 CFR 233.5 - Miscellaneous price comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set forth... principles. For example, retailers should not advertise a retail price as a “wholesale” price. They...

  1. 16 CFR 233.1 - Former price comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of bargain..., not for the purpose of establishing a fictitious higher price on which a deceptive comparison might...

  2. 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

  3. 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. PMID:24744773

  4. 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... DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set forth... principles. For example, retailers should not advertise a retail price as a “wholesale” price. They...

  5. 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.

  6. 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.

  7. Stock price forecasting using secondary self-regression model and wavelet neural networks

    NASA Astrophysics Data System (ADS)

    Yang, Chi-I.; Wang, Kai-Cheng; Chang, Kuei-Fang

    2015-07-01

    We have established a DWT-based secondary self-regression model (AR(2)) to forecast stock value. This method requires the user to decide upon the trend of the stock prices. We later used WNN to forecast stock prices which does not require the user to decide upon the trend. When comparing these two methods, we could see that AR(2) does not perform as well if there are no trends for the stock prices. On the other hand, WNN would not be influenced by the presence of trends.

  8. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 3 2012-04-01 2012-04-01 false Comparison of normal value with export price (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...

  9. 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.

  10. 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. PMID:26539722

  11. 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

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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.

  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. Comparison of Forecast and Observed Energetics

    NASA Technical Reports Server (NTRS)

    Baker, W. E.; Brin, Y.

    1985-01-01

    An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; and (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum Eddy conversion 12 h earlier is noted.

  19. Comparison of Forecast and Observed Energetics

    NASA Technical Reports Server (NTRS)

    Baker, W. E.; Brin, Y.

    1984-01-01

    An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast fields of the GLAS fourth order model for the 13 to 15 January 1979 cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum ddy conversion 12 h earlier is noted.

  20. 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.

  1. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... GUIDES AGAINST DECEPTIVE PRICING § 233.2 Retail price comparisons; comparable value comparisons. (a... fountain pens at $10, it is not dishonest for retailer Doe to advertise: “Brand X Pens, Price Elsewhere $10... here would be deceptive, since the price charged by the small suburban outlets would have no...

  2. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 3 2013-04-01 2013-04-01 false Comparison of normal value with export price (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...

  3. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 3 2011-04-01 2011-04-01 false Comparison of normal value with export price (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...

  4. 19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 3 2014-04-01 2014-04-01 false Comparison of normal value with export price (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...

  5. 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... Price, Fair Value, and Normal Value § 351.414 Comparison of normal value with export price (constructed... characteristics and that is sold to the United States at the same level of trade. In identifying sales to...

  6. Forecasting jet fuel prices using artificial neural networks. Master`s thesis

    SciTech Connect

    Kasprzak, M.A.

    1995-03-01

    Artificial neural networks provide a new approach to commodity forecasting that does not require algorithm or rule development. Neural networks have been deemed successful in applications involving optimization, classification, identification, pattern recognition and time series forecasting. With the advent of user friendly, commercially available software packages that work in a spreadsheet environment, such as Neural Works Predict by NeuralWare, more people can take advantage of the power of artificial neural networks. This thesis provides an introduction to neural networks, and reviews two recent studies of forecasting commodities prices. This study also develops a neural network model using Neural Works Predict that forecasts jet fuel prices for the Defense Fuel Supply Center (DFSC). In addition, the results developed are compared to the output of an econometric regression model, specifically, the Department of Energy`s Short-Term Integrated Forecasting System (STWS) model. The Predict artificial neural network model produced more accurate results and reduced the contribution of outliers more effectively than the STIFS model, thus producing a more robust model.

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

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

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

  8. Black-Scholes finite difference modeling in forecasting of call warrant prices in Bursa Malaysia

    NASA Astrophysics Data System (ADS)

    Mansor, Nur Jariah; Jaffar, Maheran Mohd

    2014-07-01

    Call warrant is a type of structured warrant in Bursa Malaysia. It gives the holder the right to buy the underlying share at a specified price within a limited period of time. The issuer of the structured warrants usually uses European style to exercise the call warrant on the maturity date. Warrant is very similar to an option. Usually, practitioners of the financial field use Black-Scholes model to value the option. The Black-Scholes equation is hard to solve analytically. Therefore the finite difference approach is applied to approximate the value of the call warrant prices. The central in time and central in space scheme is produced to approximate the value of the call warrant prices. It allows the warrant holder to forecast the value of the call warrant prices before the expiry date.

  9. 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

  10. ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

    PubMed

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-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 ℓ(p)-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 ℓ(1)-norm multiple support vector regression model. PMID:23365561

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. Comparison of Five Weather Forecast Methods at Four California Locations

    NASA Astrophysics Data System (ADS)

    Dempsey, D. P.; Garcia, O.; Frieberg, E.; Tidwell, W.; Chow, B.; Daquigan, D.; Long, D.; Tan, K.

    2003-12-01

    In this project we compare five methods of forecasting maximum and minimum temperature and probability of precipitation at four California locations: California Academy of Sciences in San Francisco, Oakland Museum, Sacramento Executive Airport, and Truckee Airport. The five methods are applied to make 24-hour forecasts twice weekly during the period from August 18 to December 2, 2003. The five forecast methods include: (1) Persistence. A persistence forecast assumes that tomorrow's weather will be the same as today's. (2) Climatology. Our climatology-based forecasts use weather conditions for the day at or very near each of the four locations, averaged over the 30-year period from 1971 to 2000. (3) Official National Weather Service (NWS) forecasts. We use the official NWS forecasts for Oakland Museum, Sacramento Executive Airport, and Truckee Airport. For The California Academy of Sciences (CAS) we use the NWS's new Prototype Digital Forecast for the CAS's latitude and longitude. (4) Individual student forecasts, made by four 10th grade students from San Francisco's Burton High School. They consulted the most recent meteograms, satellite images, soundings, synoptic analyses, and computer model forecasts, as well as climatology, persistence, and NWS forecasts. (5) A consensus of student forecasts, comprising the average of the four student forecasts. We calculate forecast error by squaring the difference between a forecast and the verifying observation, and compare the forecast methods based on these errors.

  17. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    PubMed Central

    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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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.

  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.

    2013-12-18

    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.

  5. Future world oil prices: review of current forecasts, identification of price-determining factors, and delineation of a quantitative framework for analysis

    SciTech Connect

    Hirshfeld, D.S.; Frye, K.N.; Bendersky, C.; Coleman, K.J.; Montano, W.B.

    1982-09-17

    This study is part of an examination of strategic questions underlying decisions regarding the US' development of new conventional oil and gas reserves and synthetic fuels production. As a baseline, an attempt is made to identify the actual determinants driving foreign oil prices of which production costs are but one element. By examining what foreign suppliers are charging and what latitude they have to change their prices, we should be better able to identify options for dealing with them. Specifically, we need to know what prices OPEC may want to set over time and how low they could allow prices to go without damaging their economies. Also, we need a better understanding of how much domestic oil consumption could be curtailed by substituting gas and a better understanding of the comparative economics of new oil and gas sources. Eventually, we also need a sound basis for strengthening agreements with western hemisphere oil exporters and improving relations with our oil-consuming allies and non-cartel nations in other parts of the world, all in keeping with the President's new program for developing potential economic allies and reducing their dependency on OPEC oil. This report analyzes: (1) Key energy market and non-market forces, including national policies, that will largely determine future world oil prices; (3) recent world oil price forecasts by a number of public-sector and private-sector organizations; and (3) a framework and method of attack, involving energy market equilibrium analysis, for estimating long-term growth rates in world oil prices in relation to alternative energy policies of the oil-consuming and oil-exporting countries. These topics are all facets of the central issue: the prospective interactions between future world oil prices and US energy policies - particularly those policies that can increase long-term domestic energy supplies.

  6. 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.

  7. 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.

  8. A Comparison of the Forecast Skills among Three Numerical Models

    NASA Astrophysics Data System (ADS)

    Lu, D.; Reddy, S. R.; White, L. J.

    2003-12-01

    Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

  9. 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.

  10. 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)

  11. 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.

  12. 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.

  13. Interaction of nonionic surfactant AEO9 with ionic surfactants*

    PubMed Central

    Zhang, Zhi-guo; Yin, Hong

    2005-01-01

    The interaction in two mixtures of a nonionic surfactant AEO9 (C12H25O(CH2CH2O)9H) and different ionic surfactants was investigated. The two mixtures were AEO9/sodium dodecyl sulfate (SDS) and AEO9/cetyltrimethylammonium bromide (CTAB) at molar fraction of AEO9, α AEO9=0.5. The surface properties of the surfactants, critical micelle concentration (CMC), effectiveness of surface tension reduction (γ CMC), maximum surface excess concentration (Γ max) and minimum area per molecule at the air/solution interface (A min) were determined for both individual surfactants and their mixtures. The significant deviations from ideal behavior (attractive interactions) of the nonionic/ionic surfactant mixtures were determined. Mixtures of both AEO9/SDS and AEO9/CTAB exhibited synergism in surface tension reduction efficiency and mixed micelle formation, but neither exhibited synergism in surface tension reduction effectiveness. PMID:15909351

  14. 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.

  15. A Statistical Comparison of the Blossom Blight Forecasts of MARYBLYT and Cougarblight with Receiver Operating Characteristic Curve Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blossom blight forecasting is an important aspect of fire blight, caused by Erwinia amylovora, management for both apple and pear. A comparison of the forecast accuracy of two common fire blight forecasters, MARYBLYT and Cougarblight, was performed with receiver operating characteristic (ROC) curve ...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Assessment of Remotely Sensed Land Surface Phenology Data for North America: Inter-comparison and Forecasting

    NASA Astrophysics Data System (ADS)

    Zhang, G.; Ganguly, S.; White, M. A.; Nemani, R. R.; Hiatt, S. H.; Hashimoto, H.; Milesi, C.; Wang, W.; Michaelis, A.; Votava, P.; Melton, F. S.; Dungan, J. L.

    2010-12-01

    Land surface phenology is widely used as a diagnostic of ecosystem response to global change and influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, a robust framework in classifying the ground phenological events to compare with remotely sensed phenology is lacking. In this research, we develop a methodology to compare the latest Collection 5 500m MODIS phenology data (cardinal dates corresponding to greenup, maturity, senescence and dormancy) with all available ground observed data for North America for the period 2001-2006. Inter-comparison results show that the MODIS phenology product performs well in capturing the “earliest events” corresponding to each of the phenological phases (e.g. budburst, first leaf, first leaf color change) of plant growth in a community. Of all the ground phenological stages, the leaf greenup events are best correlated to the MODIS greenup onset. Establishing confidence in the MODIS greenup onset data through our inter-comparison exercise and exploiting the long-term nature of the data set (2001-present) led us to build a seasonal phenology forecast model within the Terrestrial Observation and Prediction System (TOPS) framework. The available MODIS greenup data serves as a training data to our climate based phenology forecast model. We parameterize the empirical model for each 500m pixel based on the relationship between local climate provided by TOPS and MODIS greenup. As a test case, we have predicted the greenup for 2010 spring by using the seasonal climate forecast data from NECP Climate Forecast System (CFS) to our forecast model. The phenology forecast portal is now available online, which provides a unique platform for community participation in monitoring local phenology forecast events and uploading observed phenological

  3. 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.

  4. AEOS radiometer system: a multichannel imaging radiometer

    NASA Astrophysics Data System (ADS)

    Pritchett, Donald G.; Hendrick, Roy W.; Moore, Douglas K.; Briscoe, David E.; Bishop, Joseph; Medrano, Robert S.; Vigil, Michael L.

    1999-07-01

    A four channel imaging radiometer is now operational as the first sensor on the U.S. Air Force 3.67-meter Advanced Electro Optical System (AEOS) telescope at the Maui Space Surveillance Site on Mt. Haleakala. The four AEOS Radiometer System (ARS) channels cover the visible/near infrared, MWIR (2.0 - 5.5 micrometers ), LWIR (7.9 - 13.2 micrometers ), and VLWIR (16.2 - 23 micrometers ). The bands are separated by dichroic mirrors that direct the visible channel into a cooled enclosure and the infrared channels into a common cryogenic Dewar. Interference filters separate each band into multiple subbands. A novel background suppression technique uses array data and a circular scan generated by the telescope secondary. The ARS design meets challenges in volume constraint on the trunnion, a low vibration cryogenic system, thermal dissipation control, internal calibration, remotely operating four integrated focal plane arrays, high frame rates with their attendant large data handling and processing requirements, and integration into an observatory wide control system. This paper describes the design, integration, and first light test results of the ARS at the AEOS facility.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. Comparison of Observation Impacts in Two Forecast Systems using Adjoint Methods

    NASA Technical Reports Server (NTRS)

    Gelaro, Ronald; Langland, Rolf; Todling, Ricardo

    2009-01-01

    An experiment is being conducted to compare directly the impact of all assimilated observations on short-range forecast errors in different operational forecast systems. We use the adjoint-based method developed by Langland and Baker (2004), which allows these impacts to be efficiently calculated. This presentation describes preliminary results for a "baseline" set of observations, including both satellite radiances and conventional observations, used by the Navy/NOGAPS and NASA/GEOS-5 forecast systems for the month of January 2007. In each system, about 65% of the total reduction in 24-h forecast error is provided by satellite observations, although the impact of rawinsonde, aircraft, land, and ship-based observations remains significant. Only a small majority (50- 55%) of all observations assimilated improves the forecast, while the rest degrade it. It is found that most of the total forecast error reduction comes from observations with moderate-size innovations providing small to moderate impacts, not from outliers with very large positive or negative innovations. In a global context, the relative impacts of the major observation types are fairly similar in each system, although regional differences in observation impact can be significant. Of particular interest is the fact that while satellite radiances have a large positive impact overall, they degrade the forecast in certain locations common to both systems, especially over land and ice surfaces. Ongoing comparisons of this type, with results expected from other operational centers, should lead to more robust conclusions about the impacts of the various components of the observing system as well as about the strengths and weaknesses of the methodologies used to assimilate them.

  10. 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.

  11. 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.

  12. 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.

  13. Performance Comparison of the European Storm Surge Models and Chaotic Model in Forecasting Extreme Storm Surges

    NASA Astrophysics Data System (ADS)

    Siek, M. B.; Solomatine, D. P.

    2009-04-01

    Storm surge modeling has rapidly developed considerably over the past 30 years. A number of significant advances on operational storm surge models have been implemented and tested, consisting of: refining computational grids, calibrating the model, using a better numerical scheme (i.e. more realistic model physics for air-sea interaction), implementing data assimilation and ensemble model forecasts. This paper addresses the performance comparison between the existing European storm surge models and the recently developed methods of nonlinear dynamics and chaos theory in forecasting storm surge dynamics. The chaotic model is built using adaptive local models based on the dynamical neighbours in the reconstructed phase space of observed time series data. The comparison focused on the model accuracy in forecasting a recently extreme storm surge in the North Sea on November 9th, 2007 that hit the coastlines of several European countries. The combination of a high tide, north-westerly winds exceeding 50 mph and low pressure produced an exceptional storm tide. The tidal level was exceeded 3 meters above normal sea levels. Flood warnings were issued for the east coast of Britain and the entire Dutch coast. The Maeslant barrier's two arc-shaped steel doors in the Europe's biggest port of Rotterdam was closed for the first time since its construction in 1997 due to this storm surge. In comparison to the chaotic model performance, the forecast data from several European physically-based storm surge models were provided from: BSH Germany, DMI Denmark, DNMI Norway, KNMI Netherlands and MUMM Belgium. The performance comparison was made over testing datasets for two periods/conditions: non-stormy period (1-Sep-2007 till 14-Oct-2007) and stormy period (15-Oct-2007 till 20-Nov-2007). A scalar chaotic model with optimized parameters was developed by utilizing an hourly training dataset of observations (11-Sep-2005 till 31-Aug-2007). The comparison results indicated the chaotic

  14. Betting on the Future: The authors compare natural gas forecaststo futures buys

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2006-01-20

    On December 12, 2005, the reference case projections from Annual Energy Outlook 2006 (AEO 2006) 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. The goal is better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. Below is a discussion of our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this article we update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Dynamic linear model and SARIMA: a comparison of their forecasting performance in epidemiology.

    PubMed

    Nobre, F F; Monteiro, A B; Telles, P R; Williamson, G D

    2001-10-30

    One goal of a public health surveillance system is to provide a reliable forecast of epidemiological time series. This paper describes a study that used data collected through a national public health surveillance system in the United States to evaluate and compare the performances of a seasonal autoregressive integrated moving average (SARIMA) and a dynamic linear model (DLM) for estimating case occurrence of two notifiable diseases. The comparison uses reported cases of malaria and hepatitis A from January 1980 to June 1995 for the United States. The residuals for both predictor models show that they were adequate tools for use in epidemiological surveillance. Qualitative aspects were considered for both models to improve the comparison of their usefulness in public health. Our comparison found that the two forecasting modelling techniques (SARIMA and DLM) are comparable when long historical data are available (at least 52 reporting periods). However, the DLM approach has some advantages, such as being more easily applied to different types of time series and not requiring a new cycle of identification and modelling when new data become available. PMID:11590632

  1. 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.

  2. A statistical comparison of the reliability of the blossom blight forecasts of MARYBLYT and cougarblight with receiver operating characteristic (ROC) curve analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blossom blight forecasting is an important aspect of fire blight, caused by Erwinia amylovora, management for both apple and pear. A comparison of the forecast accuracy of two common fire blight forecasters, MARYBLYT and Cougarblight, was performed with receiver operating characteristic (ROC) curve...

  3. 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

  4. 16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    .... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X fountain pens at $10, it is not dishonest for retailer Doe to advertise: “Brand X Pens, Price Elsewhere $10... technique. Retailer Doe advertises Brand X pens as having a “Retail Value $15.00, My Price $7.50,” when...

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

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    .... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X fountain pens at $10, it is not dishonest for retailer Doe to advertise: “Brand X Pens, Price Elsewhere $10... technique. Retailer Doe advertises Brand X pens as having a “Retail Value $15.00, My Price $7.50,” when...

  6. 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.

  7. Comparison of two operational long-range transport air pollution forecast models

    NASA Astrophysics Data System (ADS)

    Brandt, J.; Geels, C.; Christensen, J. C.; Frohn, L. M.; Hansen, K. M.; Skjøth, C. A.; Hertel, O.

    2003-04-01

    An operational air pollution forecast system, THOR, covering scales from regional over urban background to urban street scales has been developed. The long-range transport model, The Danish Eulerian Operational Model (DEOM) is presently used in the system to calculate the long-range transported air pollution from European sources to the areas of interest. DEOM is an Eulerian model covering Europe and includes 35 chemical compounds. In order to carry out fast computations in operational mode, the model is applied with three vertical layers (bottom layer representing the mixing height, second layer representing the old advected mixing height from the day before and finally a reservoir top layer). In the last years, computer power has increased to a level where real 3-D calculations are possible for forecasting. Therefore a new comprehensive 3-D model, The Danish Eulerian Hemispheric Model (DEHM), including 62 chemical species and 18 vertical layers has been developed. Both models operate on the same polar stereographic projection with a 50 km x 50 km horizontal resolution and uses the same meteorological data from the Eta model as input. The models have been run for the year of 1999, and comparisons of model results with measurements from the European Monitoring and Evaluation Programme (EMEP) will be shown. The differences in the model characteristics will be described together with an intercomparison of the models, using different statistical tests.

  8. 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.

  9. 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.

  10. 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.

  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. 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

  13. Analyzing the Stability of Price Response Functions: Measuring the Influence of Different Parameters in a Monte Carlo Comparison

    NASA Astrophysics Data System (ADS)

    Brusch, Michael; Baier, Daniel

    The usage and the estimation of price response function is very important for strategic marketing decisions. Typically price response functions with an empirical basis are used. However, such price response functions are subject to a lot of disturbing influence factors, e.g., the assumed profit maximum price and the assumed corresponding quantity of sales. In such cases, the question how stable the found price response function is was not answered sufficiently up to now. In this paper, the question will be pursued how much (and what kind of) errors in market research are pardonable for a stable price response function. For the comparisons, a factorial design with synthetically generated and disturbed data is used.

  14. 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.

  15. 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.

  16. 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,…

  17. 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.

  18. 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…

  19. 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…

  20. Active Optics Modernization of the AEOS Telescope

    NASA Astrophysics Data System (ADS)

    Greenwald, D.

    2012-09-01

    Since first light in 1997, the Advanced Electro-Optical System (AEOS) telescope at the Maui Space Surveillance Site has used an active system for figure control that applies forces on the primary mirror and positions the secondary mirror to minimize wavefront aberrations. Periodically a wavefront optimization loop is closed with a Shack-Hartmann WaveFront Sensor (WFS), 84 primary mirror force actuators and three secondary mirror translation actuators. This optimization loop is used with a series of stellar targets to find coefficients for each force or position in a sine and cosine of elevation model. During normal telescope operation when the WFS is not in use, this elevation angle dependant model is used to control the primary mirror forces and secondary mirror positions. Recently the system was upgraded with new computers, electronics and algorithms. The primary goal of the upgrade was to replace obsolete and no longer maintainable hardware with secondary goals of reducing the effort required to update the wavefront model, and improving the final operational wavefront performance. This paper discusses the algorithms implemented to achieve the secondary goals and initial performance results. In order to eliminate erroneous data from the WFS, the processing algorithms were modified to dynamically assign pixels on the WFS camera to lenslets, and closed loop tracking of the gimbal was implemented using a camera that shares the focal plane with the WFS. These changes permit the elimination of human operator review from the wavefront optimization loop. The original system collected data for either a single star or a series of stars and then replaced either the constant or the complete model at the end of a data collection session. In the revised system, each wavefront measurement is used for a Kalman update to the model. Operationally, the Kalman updates allow data to be collected intermittently as time is available between other telescope tasks. By combining the

  1. An Observational Case Study of Persistent Fog and Comparison with an Ensemble Forecast Model

    NASA Astrophysics Data System (ADS)

    Price, Jeremy; Porson, Aurore; Lock, Adrian

    2015-05-01

    We present a study of a persistent case of fog and use the observations to evaluate the UK Met Office ensemble model. The fog appeared to form initially in association with small patches of low-level stratus and spread rapidly across southern England during 11 December 2012, persisting for 24 h. The low visibility and occurrence of fog associated with the event was poorly forecast. Observations show that the surprisingly rapid spreading of the layer was due to a circulation at the fog edge, whereby cold cloudy air subsided into and mixed with warmer adjacent clear air. The resulting air was saturated, and hence the fog layer grew rapidly outwards from its edge. Measurements of fog-droplet deposition made overnight show that an average of 12 g m h was deposited but that the liquid water content remained almost constant, indicating that further liquid was condensing at a similar rate to the deposition, most likely due to the slow cooling. The circulation at the fog edge was also present during its dissipation, by which time the fog top had lowered by 150 m. During this period the continuing circulation at the fog edge, and increasing wind shear at fog top, acted to dissipate the fog by creating mixing with, by then, the drier adjacent and overlying air. Comparisons with a new, high resolution Met Office ensemble model show that this type of case remains challenging to simulate. Most ensemble members successfully simulated the formation and persistence of low stratus cloud in the region, but produced too much cloud initially overnight, which created a warm bias. During the daytime, ensemble predictions that had produced fog lifted it into low stratus, whilst in reality the fog remained present all day. Various aspects of the model performance are discussed further.

  2. A price and use comparison of generic versus originator cardiovascular medicines: a hospital study in Chongqing, China

    PubMed Central

    2013-01-01

    Background Developed countries use generic competition to contain pharmaceutical expenditure. China, as a developing and transitional country, has not yet deemed an increase in the use of generic products as important; otherwise, much effort has been made to decrease the drug prices. This paper aims to explore dynamically the price and use comparison of generic and originator drugs in China, and estimate the potential savings of patients from switching originator drugs to generics. Methods A typical hospital in Chongqing, China, was selected to examine the price and use comparisons of 12 cardiovascular drugs from 2006 to 2011. Results The market share of the 12 generic medicines studied in this paper was 34.37% for volume and 31.33% for value in the second half of 2011. The price ratio of generic to originator drugs was between 0.34 and 0.98, and the volume price index of originators to generics was 1.63. The potential savings of patients from switching originator drugs to generics is 65%. Conclusion The market share of the generics was lowering and the weighted mean price kept increasing in face of the strict price control. Under the background of hospitals both prescribing and dispensing medicines, China’s comprehensive healthcare policy makers should take measures from supply and demand sides to promote the consumption of generic medicines. PMID:24093493

  3. Population forecasts and confidence intervals for Sweden: a comparison of model-based and empirical approaches.

    PubMed

    Cohen, J E

    1986-02-01

    This paper compares several methods of generating confidence intervals for forecasts of population size. Two rest on a demographic model for age-structured populations with stochastic fluctuations in vital rates. Two rest on empirical analyses of past forecasts of population sizes of Sweden at five-year intervals from 1780 to 1980 inclusive. Confidence intervals produced by the different methods vary substantially. The relative sizes differ in the various historical periods. The narrowest intervals offer a lower bound on uncertainty about the future. Procedures for estimating a range of confidence intervals are tentatively recommended. A major lesson is that finitely many observations of the past and incomplete theoretical understanding of the present and future can justify at best a range of confidence intervals for population projections. Uncertainty attaches not only to the point forecasts of future population, but also to the estimates of those forecasts' uncertainty. PMID:3484356

  4. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect

    United States. Bonneville Power Administration.

    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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine

    NASA Astrophysics Data System (ADS)

    Kolotii, A.; Kussul, N.; Shelestov, A.; Skakun, S.; Yailymov, B.; Basarab, R.; Lavreniuk, M.; Oliinyk, T.; Ostapenko, V.

    2015-04-01

    Winter wheat crop yield forecasting at national, regional and local scales is an extremely important task. This paper aims at assessing the efficiency (in terms of prediction error minimization) of satellite and biophysical model based predictors assimilation into winter wheat crop yield forecasting models at different scales (region, county and field) for one of the regions in central part of Ukraine. Vegetation index NDVI, as well as different biophysical parameters (LAI and fAPAR) derived from satellite data and WOFOST crop growth model are considered as predictors of winter wheat crop yield forecasting model. Due to very short time series of reliable statistics (since 2000) we consider single factor linear regression. It is shown that biophysical parameters (fAPAR and LAI) are more preferable to be used as predictors in crop yield forecasting regression models at each scale. Correspondent models possess much better statistical properties and are more reliable than NDVI based model. The most accurate result in current study has been obtained for LAI values derived from SPOT-VGT (at 1 km resolution) on county level. At field level, a regression model based on satellite derived LAI significantly outperforms the one based on LAI simulated with WOFOST.

  12. 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.

  13. 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)

  14. High and low or close to close prices? Evidence from the multifractal volatility

    NASA Astrophysics Data System (ADS)

    Liu, Zhichao; Ma, Feng; Long, Yujia

    2015-06-01

    In this study, we examine the daily returns and daily range returns dependent on close-close and the high-low prices when forecasting multifractal volatility in the Chinese stock market. In in-sample forecasting we find that both the daily returns and range returns have a significant impact on the future multifractal volatility, existing the well-established phenomenon of "leverage effects" of the positive and negative returns. Moreover, using the MF-DFA method, we find that both the two series present the persistence and exhibit the multifractal features. Furthermore, our MCS test results show that the ARFIMA-lnMFV-R and ARFIMA-lnMFV-LR models provide relatively superior volatility forecasts in comparison to all other models. Finally, we find that the daily returns calculated by close to close prices have a greater power than the daily range return calculated by high and low prices in forecasting.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    1983-10-01

    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.

  18. 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.

  19. 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.

  20. 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.

  1. Comparison of two water pricing policies in hydro-economic modeling study

    NASA Astrophysics Data System (ADS)

    Riegels, N.; Pulido Velazquez, M.; Doulgeris, C.; Sturm, V.; Jensen, R.; Møller, F.; Bauer-Gottwein, P.

    2012-04-01

    A study is presented comparing two different water pricing policies that are applied to wholesale water users throughout a river basin. The purpose of the study is to test policies that meet some of the water pricing objectives of the European Union Water Framework Directive (WFD). In the first policy, a single volumetric water price is applied to all wholesale water users throughout a case study river basin located in northern Greece. The same price is applied consistently to all surface water and groundwater users regardless of water use type and does not vary in space or time. In the second policy surface water is priced at a uniform volumetric price, while groundwater is priced using the price of energy as a surrogate for a volumetric water price. The policies are compared using a hydro-economic modeling approach in which wholesale water users are assumed to respond to water price changes according to microeconomic theory. A hydrological model of the case study river basin is used to estimate the impact of water use changes on river flow patterns, which are then used to assess the ecological status of the basin. WFD ecological status requirements are imposed as a constraint in the model, and an optimization approach is used to identify prices that meet the WFD requirements while minimizing opportunity costs (in terms of total welfare losses). Model results suggest that there is little difference between the two approaches in terms of the total opportunity costs of meeting the ecological status requirements of the WFD. However, the distribution of opportunity costs is different, with the second approach reducing the economic impact on producers of low value crops and small urban/domestic users. Because growers of low value crops will suffer the most from water price increases, the second policy offers the advantage of reducing this burden. In addition, because of difficulties associated with monitoring groundwater use, the second policy may be easier to

  2. 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

  3. 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.

  4. Petroleum-reserve responsiveness in the United States: A comparison of alternate forecasting methods

    SciTech Connect

    Ferry, J.R.

    1988-01-01

    In measuring petroleum-reserve responsiveness, this thesis meets three specific goals: (a) it provides a post mortem of the Epple model first introduced in Petroleum Discoveries and Government Policies, (b) it develops an effective alternate forecasting model that follows along the lines of Fisher's seminal piece, and (c) it provides a plausible framework for measuring the impact of federal tax policy with in each model. Epple provides a forecasting framework within a strict theoretical model that explicitly accounts for depletion through an aggregate supply function for oil-bearing land. The post mortem of Epple's work first duplicates results presented in Petroleum Discoveries and Government Policy. Modifications focus on improved data. A primary concern with the model is that t-statistics values are low, for both Epple's original model and the modified model. Data corrections and data extensions improve the coefficient values, but fail to improve the coefficient's significance. The Fisher type model performs much better. The importance of industry specific traits is apparent in the estimation of each component of reserve change. New field discoveries, old field discoveries, extensions, revisions, and production equations are estimated.

  5. 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.

  6. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

    NASA Astrophysics Data System (ADS)

    Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

    2009-08-01

    SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

  7. 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.

  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. 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

    ...''), which was published in the Federal Register on December 24, 2008. 73 FR 79072. The 2008 analysis... collected sales data from 2010 for the first annual comparison. 76 FR 18425. Similarly, DOE published... updated spreadsheet models and 2011 sales data related to the second annual comparison. 77 FR 16183....

  10. 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, 2013 CFR

    2013-04-01

    ... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Comparison of Selected... Part 281 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF... data 1976-1979) and Monthly Report for January 1980). Note: All prices are delivered prices to...

  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, 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... data 1976-1979) and Monthly Report for January 1980). Note: All prices are delivered prices to...

  12. 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.

  13. A comparison of operational Lagrangian particle and adaptive puff models for plume dispersion forecasting

    NASA Astrophysics Data System (ADS)

    Souto, M. J.; Souto, J. A.; Pérez-Muñuzuri, V.; Casares, J. J.; Bermúdez, J. L.

    Transport and dispersion of pollutants in the lower atmosphere are predicted by using both a Lagrangian particle model (LPM) and an adaptive puff model (APM2) coupled to the same mesoscale meteorological prediction model PMETEO. LPM and APM2 apply the same numerical solutions for plume rise; but, for advection and plume growth, LPM uses a stochastic surrogate to the pollutant conservation equation, and APM2 applies interpolated winds and standard deviations from the meteorological model, using a step-wise Gaussian approach. The results of both models in forecasting the SO 2 ground level concentration (glc) around the 1400 MWe coal-fired As Pontes Power Plant are compared under unstable conditions. In addition, meteorological and SO 2 glc numerical results are compared to field measurements provided by 17 fully automated SO 2 glc remote stations, nine meteorological towers and one Remtech PA-3 SODAR, from a meteorological and air quality monitoring network located 30 km around the power plant.

  14. Comparison of machine learning methods for data infilling in hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Chacon Hurtado, Juan Carlos; Alfonso, Leonardo; Solomatine, Dimitri

    2014-05-01

    The continuous measurement of hydrological variables requires sensors that must be deployed in the field, increasing the risk of failure due to natural or anthropic conditions inherent to its deployment. The failure of these sensors will interrupt the data stream, which in operational hydrological systems might lead to unsatisfactory performance of forecasting models, or biases due to lack of information in simulation models. To mitigate this, various techniques to fill these missing values can be used, varying from simple regression techniques, to more complex machine learning methods. This research aims at exploring the performance of the latter, considering particular properties of the measurements, length of the missing data series and particular properties of the missing variable. This study is carried out in two different European catchments which differ in geographical conditions, mechanisms and monitoring frequency.

  15. 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.

  16. Comparison of results of Chinese and American forecasting of nursing curriculum needs.

    PubMed

    Story, D K; Smola, B K; Liu, K H

    1990-11-01

    This study used Mengel's (1987) Round Three Questionnaire results from the Fellows of the American Academy of Nursing and baccalaureate nurse educators of Taiwan to compare perceived importance of nursing curriculum needs. The t-test was used as a test of difference between the two groups. Ninety-nine of 129 items were significantly different (p less than .05). This result showed that the forecasting of nursing curriculum needs between R.O.C. and the U.S. generic baccalaureate nursing faculty are different in many ways; specific content areas, sites for clinical experience, and perceived baccalaureate nursing curriculum needs by the year 1995. R.O.C. nurse educators value more highly than the American group six specific content areas: midwifery, nuclear medicine/nursing, space medicine/nursing, geropsychiatry, critical care nursing, and cardiac rehabilitation. American nurse educators pay more attention to 16 specific content areas: palliative care, family and social support systems for the adult, human responses to actual and potential health problems, alcohol, substance abuse and toxicology, life cycle effects on family dynamics, gerentology, health needs of the adolescent, and increasing patient compliance. The emergency care units are placed higher by the R.O.C. nurse educators than by the American group for clinical experiences. R.O.C. nurse educators rated as more important than the American group the ability to speak a second language, the management of contracted nursing services, entrepreneurial activities, and occupational nursing.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:2176681

  17. 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

  18. 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

    ...\\ which was published in the Federal Register on December 24, 2008. 73 FR 79072. The 2008 analysis... collected sales data from 2010 for the first annual comparison.\\2\\ 76 FR 18425. Today's NODA presents the... Federal Trade Commission issued the lamp labeling requirements in 1994 (see 59 FR 25176 (May 13,...

  19. Performance Comparison of Attribute Set Reduction Algorithms in Stock Price Prediction - A Case Study on Indian Stock Data

    NASA Astrophysics Data System (ADS)

    Sivakumar, P. Bagavathi; Mohandas, V. P.

    Stock price prediction and stock trend prediction are the two major research problems of financial time series analysis. In this work, performance comparison of various attribute set reduction algorithms were made for short term stock price prediction. Forward selection, backward elimination, optimized selection, optimized selection based on brute force, weight guided and optimized selection based on the evolutionary principle and strategy was used. Different selection schemes and cross over types were explored. To supplement learning and modeling, support vector machine was also used in combination. The algorithms were applied on a real time Indian stock data namely CNX Nifty. The experimental study was conducted using the open source data mining tool Rapidminer. The performance was compared in terms of root mean squared error, squared error and execution time. The obtained results indicates the superiority of evolutionary algorithms and the optimize selection algorithm based on evolutionary principles outperforms others.

  20. A Multiseason Comparison of the Forecast Skills among Three Numerical Models over Southcentral United States

    NASA Astrophysics Data System (ADS)

    Lu, D.; Reddy, S.

    2005-05-01

    During the summer 2003 and winter 2003-2004, three mesoscale numerical models, the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), Navy's Coupled Ocean/Atmospheric Mesoscale Prediction System (COAMPS) and the Weather Research and Forecasting model (WRF), were operationally run at a horizontal resolution of 27 km twice daily in Jackson State University (JSU). Three models were run by the initial and lateral boundary conditions from AVN data. The purpose of this paper is to evaluate the performances of three models during these two seasons. It was found that the temporal variation of distribution and strength of mean error (ME) biases at 12, 24 and 36h was rather weak for surface temperature, sea level pressure and surface wind speed. During two seasons, the MM5 underpredicted the seasonal precipitation while the COAMPS and WRF overpredicted. This is consistent with the statistical score analyses of rainfall. The Bias scores revealed that the MM5 yielded an underprediction of precipitation, especially for heavier rainfall events. Due to the under estimate of rainfall areas and strength, the MM5 presented the lower TS, POD and KSS scores at lighter rainfall events compared to the COAMPS and WRF. At moderate to heavier thresholds, three models produced rather low KSS and POD scores that are consistent with the high FAR values. The WRF skills in predicting precipitation heavily depend on the performance of cumulus parameterization scheme. Instead of Kain-Fritsch scheme, using other two schemes, Grell-Devenyi and Bette-Miller-Janjic, in the WRF for warm season 2003 demonstrated that the precipitation overprediction had been efficiently suppressed. Overall, the performances of three models revealed that the best skill is at 12h and the worst at 36h.

  1. Hybrid model of price pair comparisons: evidence from an event-related potential study.

    PubMed

    Cao, Bihua; Gao, Heming; Li, Fuhong

    2015-09-30

    It remains unclear whether number and unit are represented holistically (i.e. number and unit were processed as a whole) or compositionally (number and unit were processed separately) in the brain. The current study asked participants to compare price pairs with different monetary units that were presented serially. The close and far distances were defined in terms of the overall magnitude between two prices. Electrophysiological results showed that the distance effects were observed on the N2 component at the frontal regions, with far distances eliciting more negativity than close distances. This result suggests that participants compute the holistic price magnitudes before comparing them. Furthermore, a congruence effect was observed in the parietal regions. Incongruent prices elicited more negative amplitude than congruent prices on the N2 component, which implied that numbers and monetary units were processed separately over the same time course. Taken together, these findings suggest that numbers and monetary units are represented holistically and compositionally, which supports the hybrid model. PMID:26237244

  2. A Comparison of Forecasting the Index of the Korean Stock Market

    NASA Astrophysics Data System (ADS)

    Shin, Young-Geun; Park, Sang-Sung; Jang, Dong-Sik

    2009-08-01

    According to the increase of an impact foreigner investor have on the Korean stock market, it is very importance to analyze the investment pattern of the foreigner investors in order to predict the movement of the Korean stock market. Firstly, in this study we collected various factors which influence the Korean stock market in the previous literatures about the movement of stock market. Secondly, Factors which influence significantly to KOPSI 200 Index among the collected factors are extracted through the stepwise selection used in regression analysis. Finally we predicted the movement of the Korean stock market using Back-Propagation Neural Network (BPN) and Support Vector Machine (SVM). And we have done a comparison analysis of obtained results through these methods. As a result of the experiments, prediction accuracy using SVM showed better result than using BPN.

  3. 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

  4. 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.

  5. 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.

  6. 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?

  7. Use of comparative effectiveness research in drug coverage and pricing decisions: a six-country comparison.

    PubMed

    Sorenson, Corinna

    2010-07-01

    Comparative effectiveness research (CER) has assumed an increasing role in drug coverage and, in some cases, pricing decisions in Europe, as decision-makers seek to obtain better value for money. This issue brief comparatively examines the use of CER across six countries--Denmark, England, France, Germany, the Netherlands, and Sweden. With CER gaining traction in the United States, these international experiences offer insights and potential lessons. Investing in CER can help address the current gap in publicly available, credible, up-to-date, and scientifically based comparative information on the effectiveness of drugs and other health interventions. This information can be used to base coverage and pricing decisions on evidence of value, thereby facilitating access to and public and private investment in the most beneficial new drugs and technologies. In turn, use of CER creates incentives for more efficient, high-quality health care and encourages development of innovative products that offer measurable value to patients. PMID:20614655

  8. Imaging of Uranus' Atmosphere in 2003 with Keck and AEOS

    NASA Astrophysics Data System (ADS)

    Hammel, H. B.; Rages, K. A.; Lockwood, G. W.; de Pater, I.; Gibbard, S.

    2003-12-01

    Adaptive optics (AO) imaging of Uranus was obtained with NIRC2 on the Keck II 10-meter telescope on 3-6 October 2003 through J, H, and K' filters, and the Air Force AEOS system on Maui on 2-3 October 2003 through Bessel I and other narrower filters. Many discrete features were detected in the atmosphere of Uranus. Detection of low-contrast features was possible because the Keck AO system has improved dramatically over the past six months. We will report wind speeds for all trackable features, and compare them with results from previous years. Preliminary inspection of the data shows features at latitudes where no features have been previously seen; tracking these features may fill significant gaps in the zonal wind profile. We will also discuss the wavelength dependence of discrete features, and the consequent implications for feature altitudes. The south polar collar at 45 S latitude is clearly visible at I, J, and H, and is still undetected at K' (as in previous years). There is no sign yet of a similar polar collar in the northern hemisphere at these wavelengths. The observations were supported in part from NASA grant NAG5-10451, from Air Force Award F49620-03-1-0125, and by the NSF Center for Adaptive Optics, managed by UCSC under cooperative agreement No. AST-9876783. The Keck Observatory is operated as a scientific partnership by Caltech, UC, and NASA, and was made possible by the financial support of the W.M. Keck Foundation.

  9. A Kalman filter and 3dVAR inter-comparison with NCEP's new operational forecasting system

    NASA Astrophysics Data System (ADS)

    Fukumori, I.; Behringer, D.; Wang, O.; Wang, J.

    2008-12-01

    The ECCO Kalman filter is adapted to the Modular Ocean Model (MOM4) employed in the latest operational ocean analyses of the National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration. The ocean state estimates of the Kalman filter are compared with those of NCEP's 3dVAR method to assess the relative impact of the different approaches on analyzing and forecasting seasonal-to-interannual climate variability. The ECCO filter employs partitioned, reduced-state, and time-asymptotic approximations of the model state error covariance matrix associated with inaccuracies in atmospheric wind forcing. The filter assimilates temporal anomalies of satellite sea level and in situ temperature profile measurements over the world's oceans. New advancements are devised in filter implementation including use of adjoint codes and improvements in spatial interpolation around land masses and in estimating effects of vertical heaving motion. The next operational model of NCEP is based on MOM4 and employs a tripolar grid that spans the entire globe including the Arctic Ocean with a nominal 0.5-degree grid with 40 vertical levels. A 3dVAR method is employed to assimilate temperature and synthetic salinity profiles. The salinity profiles are constructed from the temperature profiles and a local TS relationship. The model error variances are assumed to be proportional to the local temperature and salinity gradients and are computed from the most recent 5-day model average. Utilizing identical models, the inter-comparison provides a unique assessment of the two assimilation methods independent of potential differences in models that are used. The two ocean state estimates will be compared with respect to various observations. Circulation indexes will be analyzed such as strengths of subtropical cells, meridional overturning circulation, and integrated upper ocean heat content changes. The assimilations' impact on subsequent variability of the ocean

  10. Comparison of short-term rainfall forecasts for model-based flow prediction in urban drainage systems.

    PubMed

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas; Borup, Morten; Ahm, Malte; Nielsen, Jesper Ellerbæk; Grum, Morten; Rasmussen, Michael R; Gill, Rasphall; Mikkelsen, Peter Steen

    2013-01-01

    Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real-time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 h. The best performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times. PMID:23863443

  11. 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.…

  12. 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.

  13. 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.

  14. Low flow forecasting with data driven models that include and models that do not include hydrological knowledge - a comparison study

    NASA Astrophysics Data System (ADS)

    Stravs, L.; Brilly, M.

    2009-04-01

    Good and accurate long-term low flow forecasting is important in the fields of sustainable water management, water rights, water supply management, industrial use of freshwater, optimization of the reservoir operations for the production of electric energy and other water-related disciplines. Today, low flow forecasting is usually performed as an integrated part of calibrated rainfall-runoff models, but in our research we developed two types of simple empirical 7-day ahead low flow forecasting models by using the M5 machine learning method for the generation of regression and model trees. Development of the first type of models was based solely on the application of the M5 machine learning method (1-, 2-, 3-, 4-, 5-, 6-and 7-day lead time low flow forecasting model trees were developed from using only past flow data and then combined to produce 7-day ahead forecast curve), while the development of the other type of models included the conceptual knowledge of linear reservoir recession functions AND application of the M5 machine learning method (we modelled the streamflow recession coefficient k as a function of the flow rate at which the 7-day low flow forecast is made and the decrease in the flow rate from the previous day). Both types of 7-day ahead low flow forecasting models were developed by using the same type and amount of data and were built for the Podhom gauging station on the Radovna River and the Medvode gauging station on the Sora River (both are Slovenian tributaries of the Sava River, which itself is a Danube River tributary). The results were compared and tested both visually and numerically.

  15. 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

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976-January 1980 A Appendix A 1 to Part 281 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT...

  16. 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, 2012 CFR

    2012-04-01

    ... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976-January 1980 A Appendix A 1 to Part 281 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT...

  17. 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

    ... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Comparison of Selected Fuel Price Data, FPC Form No. 423 Versus Monthly Energy Review, 1976-January 1980 A Appendix A 1 to Part 281 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT...

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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 ...

  3. 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.

  4. 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.

  5. Comparison of two ways for representation of the forecast probability density function in ensemble-based sequential data assimilation

    NASA Astrophysics Data System (ADS)

    Nakano, Shinya

    2013-04-01

    In the ensemble-based sequential data assimilation, the probability density function (PDF) at each time step is represented by ensemble members. These ensemble members are usually assumed to be Monte Carlo samples drawn from the PDF, and the probability density is associated with the concentration of the ensemble members. On the basis of the Monte Carlo approximation, the forecast ensemble, which is obtained by applying the dynamical model to each ensemble member, provides an approximation of the forecast PDF on the basis of the Chapman-Kolmogorov integral. In practical cases, however, the ensemble size is limited by available computational resources, and it is typically much less than the system dimension. In such situations, the Monte Carlo approximation would not well work. When the ensemble size is less than the system dimension, the ensemble would form a simplex in a subspace. The simplex can not represent the third or higher-order moments of the PDF, but it can represent only the Gaussian features of the PDF. As noted by Wang et al. (2004), the forecast ensemble, which is obtained by applying the dynamical model to each member of the simplex ensemble, provides an approximation of the mean and covariance of the forecast PDF where the Taylor expansion of the dynamical model up to the second-order is considered except that the uncertainties which can not represented by the ensemble members are ignored. Since the third and higher-order nonlinearity is discarded, the forecast ensemble would provide some bias to the forecast. Using a small nonlinear model, the Lorenz 63 model, we also performed the experiment of the state estimation with both the simplex representation and the Monte Carlo representation, which corresponds to the limited-sized ensemble case and the large-sized ensemble case, respectively. If we use the simplex representation, it is found that the estimates tend to have some bias which is likely to be caused by the nonlinearity of the system rather

  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. Bonneville Power Administration Forecasts of Electricity Consumption in the Pacific Northwest; Technical Documentation.

    SciTech Connect

    United States. Bonneville Power Administration.

    1983-10-01

    A 20-year forecast of electricity consumption in the Pacific Northwest is presented for the years 1982-2003. Projections are expressed as a baseline, with alternative cases representing situations of high and low electricity consumption. All three projections are produced by merging separate long-term and midterm forecasts. The long-term forecast is produced using a series of demand models (each addressing a specific consuming sector) in conjunction with an electricity supply pricing model. These models provide a detailed breakdown of energy use and permit long-range comparisons of alternative power planning policy decisions. They are not, however, sensitive to weather conditions, business cycles, or economic fluctuations which might prove significant in the near future. BPA's midterm forecasting models are designed specifically to be responsive to such factors, allowing them to be captured in the final load forecast which merges the long-term and midterm projections. These midterm models econometrically forecast energy demand by state but without any detail by consuming sector. The midterm forecast will be updated quarterly to reflect the mot current regional projections of near-term economic activity.

  8. 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

  9. 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.

  10. 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…

  11. 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

  12. Demand 80/81: Forecasts of energy consumption to the year 2000. Volume 2: Appendixes

    NASA Astrophysics Data System (ADS)

    Borges, A. M.; Boyce, C. M.; Crow, R. T.

    1981-10-01

    The forecasts cover each sector of the economy and are conditional upon alternative assumptions concerning national economic growth, energy prices, other prices, and conservation policy. The forecasts also include forms of energy other than electricity to provide a comprehensive energy picture. Although the forecasts proceed through time in one-year increments, their primary focus is on the period from 1985 to 2000.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  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)

    López López, P.; Verkade, J. S.; Weerts, A. H.; Solomatine, D. P.

    2014-09-01

    The present study comprises an intercomparison of different configurations of a statistical post-processor that is used to estimate predictive hydrological uncertainty. It builds on earlier work by Weerts, Winsemius and Verkade (2011; hereafter referred to as WWV2011), who used the quantile regression technique to estimate predictive hydrological uncertainty using a deterministic water level forecast as a predictor. The various configurations are designed to address two issues with the WWV2011 implementation: (i) quantile crossing, which causes non-strictly rising cumulative predictive distributions, and (ii) the use of linear quantile models to describe joint distributions that may not be strictly linear. Thus, four configurations were built: (i) a ''classical" quantile regression, (ii) a configuration that implements a non-crossing quantile technique, (iii) a configuration where quantile models are built in normal space after application of the normal quantile transformation (NQT) (similar to the implementation used by WWV2011), and (iv) a configuration that builds quantile model separately on separate domains of the predictor. Using each configuration, four reforecasting series of water levels at 14 stations in the upper Severn River were established. The quality of these four series was intercompared using a set of graphical and numerical verification metrics. Intercomparison showed that reliability and sharpness vary across configurations, but in none of the configurations do these two forecast quality aspects improve simultaneously. Further analysis shows that skills in terms of the Brier skill score, mean continuous ranked probability skill score and relative operating characteristic score is very similar across the four configurations.

  18. 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...

  19. 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.

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

    SciTech Connect

    Ross, M.H.; 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.

  1. 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

  2. Demand 80/81: Forecasts of energy consumption to the year 2000. Volume 1: Forecasts and description of the forecasting model

    NASA Astrophysics Data System (ADS)

    Borges, A. M.; Crow, R. T.

    1981-10-01

    National forecasts of end use consumption of electricity, liquid hydrocarbons, gaseous hydrocarbons, and coal are presented. The forecasts are based on an econometric model whose equations represent energy consumption of each form of energy in each end use sector. Each forecast is conditional upon a common forecast of long run economic growth, coupled with a scenario concerning energy prices and conservation policy. The scenarios are composed of four alternative sets of assumptions about energy prices and three alternative sets of assumptions on conservation policy.

  3. 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.

  4. Medium-term Earthquake Forecasting with Numerical Earthquake Simulators: A Feasibility Study with a Comparison to the WGCEP

    NASA Astrophysics Data System (ADS)

    Rundle, J. B.; van Aalsburg, J.; Morein, G.; Turcotte, D. L.; Grant-Ludwig, L.; Donnellan, A.; Tiampo, K. F.; Klein, W.

    2008-12-01

    Topologically realistic earthquake simulations are now possible using numerical codes such as Virtual California (VC). Currently, VC is written in modern object-oriented C++ code, and runs under MPI-II protocols on parallel HPC machines such as the NASA Columbia supercomputer. In VC, an earthquake fault system is modeled by a large number of Boundary Elements interacting by means of linear elasticity. A friction law is prescribed for each boundary element, and the faults are driven at a stressing rate that is consistent with their observed long-term average offset rate. We note that the parameters that enter into the model are set using the long term average properties of the fault system -- earthquake and plate rate variability are not used at this stage of the simulation. We have carried out simulations for earthquakes on models of California's fault system for simulation runs over time intervals from tens of thousands of years to millions of years. Using these simulations, we have now developed techniques to assimilate observed earthquake variability into the simulations. Our technique is based on mining the simulation data to identify time intervals that look most like the recent past history of earthquakes on the California fault system. We then use these optimal time intervals to "look into the future" and forecast the likely locations of future major earthquakes. Here we describe this method and carry out a feasibility study of its application. We develop fault-based relative spatial probabilities that can be compared with recent results from the Working Group on California Earthquake Probabilities (WGCEP 2008). Both VC and WGCEP forecast elevated relative probabilities for the Southern San Andreas fault (40.4% VC; 35.5% WGCEP). However, the relative probabilities are significantly different for the Northern San Andreas fault (22.6% VC; 12.7% WGCEP); the Calaveras fault (13.5% VC; 4.2% WGCEP); the Hayward-Rodgers Creek faults (5.0% VC; 18.7% WGCEP); and the

  5. Daily Simulations of O3 and PM2.5 Over New York State: Seasonal and Interannual Differences and Comparison to Routine Air Quality Index (AQI) Forecasts

    NASA Astrophysics Data System (ADS)

    Hogrefe, C.; Hao, W.; Civerolo, K.; Ku, J.; Sistla, G.; Sedefian, L.; Gaza, R.; Schere, K.; Gilliland, A.; Mathur, R.

    2005-12-01

    This paper presents the application and evaluation of an air quality modeling system designed to simulate O3 and PM2.5 on a near-realtime basis over the northeastern United States with a focus on New York State. The air quality modeling system consists of operational weather forecasts from the National Weather Services (NWS) ETA model at a horizontal resolution of 12 km, the PREMAQ emissions and meteorology pre-processor, and the Community Multiscale Air Quality (CMAQ) model. The simulations are being performed as part of a pilot study between the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), and the New York State Department of Environmental Conservation (NYSDEC) utilizing resources from the operational NWS/NOAA/EPA air quality forecasts. To date, daily simulations have been performed for two summer seasons (2004 and 2005) and one winter season (2004). Model performance for PM2.5 is analyzed for intra- and interannual variability by comparing predictions from these three time periods against both continuous total PM2.5 mass measurements and speciation data. Results of this analysis indicate that the performance of the ETA/CMAQ modeling system is within the range of current regulatory air quality modeling studies employing meteorological data assimilation. Furthermore, there is no pronounced seasonality in model performance for total PM2.5 over New York State, but model performance for individual species shows seasonal behavior. The model evaluation results also reveal a significant overestimation of the inert PM2.5 species in New York State. Therefore, in an effort to improve model performance, we present the results of sensitivity simulations in which primary PM2.5 emissions were modified. Finally, ETA/CMAQ simulations of O3 and PM2.5 for New York State are compared against NYSDEC-issued non-model based routine air quality forecasts. This comparison focuses on the air quality index (AQI), a quantity used

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    NASA Astrophysics Data System (ADS)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  13. Stochastic speculative price.

    PubMed

    Samuelson, P A

    1971-02-01

    Because a commodity like wheat can be carried forward from one period to the next, speculative arbitrage serves to link its prices at different points of time. Since, however, the size of the harvest depends on complicated probability processes impossible to forecast with certainty, the minimal model for understanding market behavior must involve stochastic processes. The present study, on the basis of the axiom that it is the expected rather than the known-for-certain prices which enter into all arbitrage relations and carryover decisions, determines the behavior of price as the solution to a stochastic-dynamic-programming problem. The resulting stationary time series possesses an ergodic state and normative properties like those often observed for real-world bourses. PMID:16591903

  14. Forecasting Future Social Needs

    ERIC Educational Resources Information Center

    Abt, Clark C.

    1971-01-01

    Describes briefly why social forecasting is easier than technological forecasting, offers four approaches to social forecasting (judgment, extrapolation, speculation, analysis), and suggests a procedure recommended for social forecasting. (CJ)

  15. 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,…

  16. 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…

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Flexible procurement strategies smooth price spikes

    SciTech Connect

    Gaalaas, T.

    2006-12-15

    Pace Global Energy Services has been predicting for some time that the recent peaks in spot coal prices were not sustainable and this has been borne out. The latest available data on coal supply and demand fundamental suggest that spot coal prices may decline even more rapidly than previously forecast. Price volatility over the last five years suggests that a flexible procurement strategy that is well adapted to volatile market conditions may be just as important as knowledge of market fundamentals. 3 figs.

  19. Statistical Earthquake Focal Mechanism Forecasts

    NASA Astrophysics Data System (ADS)

    Kagan, Y. Y.; Jackson, D. D.

    2013-12-01

    The new whole Earth focal mechanism forecast, based on the GCMT catalog, has been created. In the present forecast, the sum of normalized seismic moment tensors within 1000 km radius is calculated and the P- and T-axes for the focal mechanism are evaluated on the basis of the sum. Simultaneously we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms. This average angle shows tectonic complexity of a region and indicates the accuracy of the prediction. The method was originally proposed by Kagan and Jackson (1994, JGR). Recent interest by CSEP and GEM has motivated some improvements, particularly to extend the previous forecast to polar and near-polar regions. The major problem in extending the forecast is the focal mechanism calculation on a spherical surface. In the previous forecast as our average focal mechanism was computed, it was assumed that longitude lines are approximately parallel within 1000 km radius. This is largely accurate in the equatorial and near-equatorial areas. However, when one approaches the 75 degree latitude, the longitude lines are no longer parallel: the bearing (azimuthal) difference at points separated by 1000 km reach about 35 degrees. In most situations a forecast point where we calculate an average focal mechanism is surrounded by earthquakes, so a bias should not be strong due to the difference effect cancellation. But if we move into polar regions, the bearing difference could approach 180 degrees. In a modified program focal mechanisms have been projected on a plane tangent to a sphere at a forecast point. New longitude axes which are parallel in the tangent plane are corrected for the bearing difference. A comparison with the old 75S-75N forecast shows that in equatorial regions the forecasted focal mechanisms are almost the same, and the difference in the forecasted focal mechanisms rotation angle is close to zero. However, though the forecasted focal mechanisms are similar

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. Forecaster's dilemma: Extreme events and forecast evaluation

    NASA Astrophysics Data System (ADS)

    Lerch, Sebastian; Thorarinsdottir, Thordis; Ravazzolo, Francesco; Gneiting, Tilmann

    2015-04-01

    In discussions of the quality of forecasts in the media and public, attention often focuses on the predictive performance in the case of extreme events. Intuitively, accurate predictions on the subset of extreme events seem to suggest better predictive ability. However, it can be demonstrated that restricting conventional forecast verification methods to subsets of observations might have unexpected and undesired effects and may discredit even the most skillful forecasters. Hand-picking extreme events is incompatible with the theoretical assumptions of established forecast verification methods, thus confronting forecasters with what we refer to as the forecaster's dilemma. For probabilistic forecasts, weighted proper scoring rules provide suitable alternatives for forecast evaluation with an emphasis on extreme events. Using theoretical arguments, simulation experiments and a case study on probabilistic forecasts of wind speed over Germany, we illustrate the forecaster's dilemma and the use of weighted proper scoring rules.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Modeling spot markets for electricity and pricing electricity derivatives

    NASA Astrophysics Data System (ADS)

    Ning, Yumei

    Spot prices for electricity have been very volatile with dramatic price spikes occurring in restructured market. The task of forecasting electricity prices and managing price risk presents a new challenge for market players. The objectives of this dissertation are: (1) to develop a stochastic model of price behavior and predict price spikes; (2) to examine the effect of weather forecasts on forecasted prices; (3) to price electricity options and value generation capacity. The volatile behavior of prices can be represented by a stochastic regime-switching model. In the model, the means of the high-price and low-price regimes and the probabilities of switching from one regime to the other are specified as functions of daily peak load. The probability of switching to the high-price regime is positively related to load, but is still not high enough at the highest loads to predict price spikes accurately. An application of this model shows how the structure of the Pennsylvania-New Jersey-Maryland market changed when market-based offers were allowed, resulting in higher price spikes. An ARIMA model including temperature, seasonal, and weekly effects is estimated to forecast daily peak load. Forecasts of load under different assumptions about weather patterns are used to predict changes of price behavior given the regime-switching model of prices. Results show that the range of temperature forecasts from a normal summer to an extremely warm summer cause relatively small increases in temperature (+1.5%) and load (+3.0%). In contrast, the increases in prices are large (+20%). The conclusion is that the seasonal outlook forecasts provided by NOAA are potentially valuable for predicting prices in electricity markets. The traditional option models, based on Geometric Brownian Motion are not appropriate for electricity prices. An option model using the regime-switching framework is developed to value a European call option. The model includes volatility risk and allows changes

  11. National Hospital Input Price Index

    PubMed Central

    Freeland, Mark S.; Anderson, Gerard; Schendler, Carol Ellen

    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 percent. 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

  12. 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)

  13. Bidding strategy with forecast technology based on support vector machine in the electricity market

    NASA Astrophysics Data System (ADS)

    Gao, Ciwei; Bompard, Ettore; Napoli, Roberto; Wan, Qiulan; Zhou, Jian

    2008-06-01

    The participants in the electricity market are concerned very much with the market price evolution. Various technologies have been developed for price forecasting. The SVM (Support Vector Machine) has shown its good performance in market price forecasting. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecasting accuracy, with which the rejection risk is defined. The other takes into account the impact of the producer’s own bid. The risks associated with the bidding are controlled by the parameter settings. The proposed approaches have been tested on a numerical example.

  14. 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.

  15. 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…

  16. 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

  17. 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

  18. Quantitative Measurements of the Daytime Near Infrared Sky Brightness at the AEOS 3.6 m Telescope

    NASA Astrophysics Data System (ADS)

    Hart, M.; Jefferies, S.; Hope, D.; Nagy, J.; Williams, S.

    2014-09-01

    We report daytime sky brightness measurements recorded in the near infrared from the 3.6 m AEOS telescope. Measurements were made at various positions in the sky and separation angles from the sun. The detector was an InGaAs focal plane array in a FLIR SC6000 camera, with images taken through a 50 nm wide filter centered at 1250 nm as well as without any optical filter. The brightness measurements have been calibrated by reference to observations of a photometric standard star in the same bands. We discuss how these new results are motivated by the selection of optimal techniques for high-resolution imaging of satellites from the AEOS telescope.

  19. 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.

  20. 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.

  1. 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.

  2. Comparison of Two Machine Learning Regression Approaches (Multivariate Relevance Vector Machine and Artificial Neural Network) Coupled with Wavelet Decomposition to Forecast Monthly Streamflow in Peru

    NASA Astrophysics Data System (ADS)

    Ticlavilca, A. M.; Maslova, I.; McKee, M.

    2011-12-01

    This research presents a modeling approach that incorporates wavelet-based analysis techniques used in statistical signal processing and multivariate machine learning regression to forecast monthly streamflow in Peru. Two machine learning regression approaches, Multivariate Relevance Vector Machine and Artificial Neural Network, are compared in terms of performance and robustness. The inputs of the model utilize information of streamflow and Pacific sea surface temperature (SST). The monthly Pacific SST data (from 1950 to 2010) are obtained from the NOAA Climate Prediction Center website. The inputs are decomposed into meaningful components formulated in terms of wavelet multiresolution analysis (MRA). The outputs are the forecasts of streamflow two, four and six months ahead simultaneously. The proposed hybrid modeling approach of wavelet decomposition and machine learning regression can capture sufficient information at meaningful temporal scales to improve the performance of the streamflow forecasts in Peru. A bootstrap analysis is used to explore the robustness of the hybrid modeling approaches.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 15-Year Enrollment and WSCH Forecast: California Community Colleges Chancellor's Office 1996 Forecast Using Statewide Data.

    ERIC Educational Resources Information Center

    California Community Colleges, Sacramento. Office of the Chancellor.

    In January 1996, the Chancellor's Office of the California Community Colleges prepared a 15-year forecast of enrollment and weekly student contact hours (WSCH) using an econometric model that analyzes real (i.e., price-adjusted) costs facing students, real operating budget expenditures of colleges, population and unemployment projections, and…

  8. A trend discontinuity: The mystery of natural gas prices

    SciTech Connect

    Steffes, D.W.

    1995-12-01

    For the last fifteen years, the natural gas price forecasting experts have had a terrible record of forecasting future natural gas prices. (In the early 80`s, the gas price was forecasted to be over $10/MMBtu in the late 80`s). To make matters even worse, they can`t seem to understand why the price is what it is, even in hindsight. If these experts can`t even get it right in hindsight, how can one ever expect to get it right in foresight? It is concluded that the traditional laws of supply and demand don`t work very well in this new quasi-regulated natural gas industry. Evidently, Social Influences and Political Influences are more important than the Economic Influence on natural gas prices.

  9. 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.

  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…