WorldWideScience

Sample records for forecasting future realized

  1. The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock and Bond Markets

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper

    We study the forecasting of future realized volatility in the stock, bond, and foreign exchange markets, as well as the continuous sample path and jump components of this, from variables in the information set, including implied volatility backed out from option prices. Recent nonparametric...

  2. On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting

    International Nuclear Information System (INIS)

    Chevallier, Julien; Sevi, Benoit

    2009-01-01

    The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and sub-sampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities. (authors)

  3. Modelling and Forecasting Multivariate Realized Volatility

    DEFF Research Database (Denmark)

    Halbleib, Roxana; Voev, Valeri

    2011-01-01

    This paper proposes a methodology for dynamic modelling and forecasting of realized covariance matrices based on fractionally integrated processes. The approach allows for flexible dependence patterns and automatically guarantees positive definiteness of the forecast. We provide an empirical appl...

  4. A nonparametric approach to forecasting realized volatility

    OpenAIRE

    Adam Clements; Ralf Becker

    2009-01-01

    A well developed literature exists in relation to modeling and forecasting asset return volatility. Much of this relate to the development of time series models of volatility. This paper proposes an alternative method for forecasting volatility that does not involve such a model. Under this approach a forecast is a weighted average of historical volatility. The greatest weight is given to periods that exhibit the most similar market conditions to the time at which the forecast is being formed...

  5. Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice

    NARCIS (Netherlands)

    Callot, Laurent A.F.; Kock, Anders B.; Medeiros, Marcelo C.

    2017-01-01

    We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast

  6. Forecasting stock market volatility: Do realized skewness and kurtosis help?

    Science.gov (United States)

    Mei, Dexiang; Liu, Jing; Ma, Feng; Chen, Wang

    2017-09-01

    In this study, we investigate the predictability of the realized skewness (RSK) and realized kurtosis (RKU) to stock market volatility, that has not been addressed in the existing studies. Out-of-sample results show that RSK, which can significantly improve forecast accuracy in mid- and long-term, is more powerful than RKU in forecasting volatility. Whereas these variables are useless in short-term forecasting. Furthermore, we employ the realized kernel (RK) for the robustness analysis and the conclusions are consistent with the RV measures. Our results are of great importance for portfolio allocation and financial risk management.

  7. Modelling and Forecasting Multivariate Realized Volatility

    DEFF Research Database (Denmark)

    Chiriac, Roxana; Voev, Valeri

    . We provide an empirical application of the model, in which we show by means of stochastic dominance tests that the returns from an optimal portfolio based on the model's forecasts second-order dominate returns of portfolios optimized on the basis of traditional MGARCH models. This result implies...

  8. Forecasting the future of biodiversity

    DEFF Research Database (Denmark)

    Fitzpatrick, M. C.; Sanders, Nate; Ferrier, Simon

    2011-01-01

    , but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single-species models to those from a multi-species modeling approach, Generalized Dissimilarity Modeling (GDM...... climate change impacts on biodiversity....

  9. Modeling and forecasting petroleum futures volatility

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2006-01-01

    Forecasts of oil price volatility are important inputs into macroeconometric models, financial market risk assessment calculations like value at risk, and option pricing formulas for futures contracts. This paper uses several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum futures price returns. The out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. Despite the increased complexity, models like state space, vector autoregression and bivariate GARCH do not perform as well as the single equation GARCH model. Most models out perform a random walk and there is evidence of market timing. Parametric and non-parametric value at risk measures are calculated and compared. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests. These results are useful for anyone needing forecasts of petroleum futures volatility. (author)

  10. Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Patton, Andrew J.; Quaedvlieg, Rogier

    We propose a new framework for modeling and forecasting common financial risks based on (un)reliable realized covariance measures constructed from high-frequency intraday data. Our new approach explicitly incorporates the effect of measurement errors and time-varying attenuation biases into the c......We propose a new framework for modeling and forecasting common financial risks based on (un)reliable realized covariance measures constructed from high-frequency intraday data. Our new approach explicitly incorporates the effect of measurement errors and time-varying attenuation biases...

  11. Credibility of management earnings forecasts and future returns

    OpenAIRE

    Norio Kitagawa; Akinobu Shuto

    2015-01-01

    This study investigates the effect of managerial discretion over their initial earnings forecasts on future performance. First, by estimating the discretionary portion of initial management earnings forecasts (defined as discretionary forecasts) based on the findings of fundamental analysis research, we find that firms with higher discretionary forecasts are more likely to miss their earnings forecast at the end of the fiscal year and revise their forecasts downward to meet their earnings for...

  12. Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors

    DEFF Research Database (Denmark)

    Halbleib, Roxana; Voev, Valeri

    2011-01-01

    This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates......, regardless of the type of utility function or return distribution, would be better-off from using this model than from using some standard approaches....

  13. Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance

    NARCIS (Netherlands)

    M. Asai (Manabu); M.J. McAleer (Michael)

    2014-01-01

    markdownabstract__Abstract__ Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates

  14. Investigate Volatility Jumps in Chinese Stock Index Future and Spot Markets Based on Realized Volatility

    Institute of Scientific and Technical Information of China (English)

    Zhang qiang

    2014-01-01

    This paper aims to investigate Chinese stock index future and spot market's volatility jumps characteristics by using recentlydeveloped jumpstest(Barndorff-Nielsenand Shephard,2004).Thedataisoneyearhigh frequencydatafromthe period19/04/2012 to 19/04/2013. The empirical results show two important points. Firstly, the logarithm of adjusted realized volatility shows a high degree of autocorrelation and folows a normal distribution nearly perfect. These characteristics show a potential high forecast ability. Secondly,thedailyrealizedvolatilityjumpsshowalowdegreeofautocorrealtionbutwithsignificantvolatilityclusters.Ingeneral,thejumps component has a low percentage in realized volatility estimation for both future and spot market. On average, there is one significant jumpswithinevery ten continue trading days.Spotmarkets showshigherdegree of jumps,anda rapidly jumpscharacterises.It implies that jumps may transmission from spot to future market, and spot market dominate future market at some degree.

  15. Adjusting Futures Forecasts of Federal Reserve Policy

    DEFF Research Database (Denmark)

    Chun, Albert Lee; Chun, Olfa Maalaoui

    Our results challenge the traditional way we interpret empirical measures of risk premia, as a signicant part of the predictable component of excess returns is strongly correlated with predictability in survey forecast errors. Using survey forecasts of the federal funds rate to proxy for market e...

  16. Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice

    DEFF Research Database (Denmark)

    Callot, Laurent; Kock, Anders Bredahl; Medeiros, Marcelo C.

    stocks and find that these dynamics are not stable as the data is aggregated from the daily to the weekly and monthly frequency. The theoretical performance guarantees on our forecasts are illustrated on the Dow Jones index. In particular, we can beat our benchmark by a wide margin at the longer forecast...

  17. Modeling returns volatility: Realized GARCH incorporating realized risk measure

    Science.gov (United States)

    Jiang, Wei; Ruan, Qingsong; Li, Jianfeng; Li, Ye

    2018-06-01

    This study applies realized GARCH models by introducing several risk measures of intraday returns into the measurement equation, to model the daily volatility of E-mini S&P 500 index futures returns. Besides using the conventional realized measures, realized volatility and realized kernel as our benchmarks, we also use generalized realized risk measures, realized absolute deviation, and two realized tail risk measures, realized value-at-risk and realized expected shortfall. The empirical results show that realized GARCH models using the generalized realized risk measures provide better volatility estimation for the in-sample and substantial improvement in volatility forecasting for the out-of-sample. In particular, the realized expected shortfall performs best for all of the alternative realized measures. Our empirical results reveal that future volatility may be more attributable to present losses (risk measures). The results are robust to different sample estimation windows.

  18. Forecasting oil price movements with crack spread futures

    International Nuclear Information System (INIS)

    Murat, Atilim; Tokat, Ekin

    2009-01-01

    In oil markets, the crack spread refers to the crude-product price relationship. Refiners are major participants in oil markets and they are primarily exposed to the crack spread. In other words, refiner activity is substantially driven by the objective of protecting the crack spread. Moreover, oil consumers are active participants in the oil hedging market and they are frequently exposed to the crack spread. From another perspective, hedge funds are heavily using crack spread to speculate in oil markets. Based on the high volume of crack spread futures trading in oil markets, the question we want to raise is whether the crack spread futures can be a good predictor of oil price movements. We investigated first whether there is a causal relationship between the crack spread futures and the spot oil markets in a vector error correction framework. We found the causal impact of crack spread futures on spot oil market both in the long- and the short-run after April 2003 where we detected a structural break in the model. To examine the forecasting performance, we use the random walk model (RWM) as a benchmark, and we also evaluate the forecasting power of crack spread futures against the crude oil futures. The results showed that (a) both the crack spread futures and the crude oil futures outperformed the RWM; and (b) the crack spread futures are almost as good as the crude oil futures in predicting the movements in spot oil markets. (author)

  19. Assimilating the Future for Better Forecasts and Earlier Warnings

    Science.gov (United States)

    Du, H.; Wheatcroft, E.; Smith, L. A.

    2016-12-01

    Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

  20. Leading the 21st-century academic library successful strategies for envisioning and realizing preferred futures

    CERN Document Server

    Eden, Bradford Lee

    2015-01-01

    Leading the 21st Century Academic Library: Successful Strategies for Envisioning and Realizing Preferred Futures will explore the new roles and directions academic libraries are taking in the 21st century as a consequence of visionary leadership in exploring diverse futures.

  1. On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model

    Czech Academy of Sciences Publication Activity Database

    Čech, František; Baruník, Jozef

    2017-01-01

    Roč. 36, č. 1 (2017), s. 181-206 ISSN 0277-6693 R&D Projects: GA ČR GA13-32263S Institutional support: RVO:67985556 Keywords : Multivariate volatility * realized covariance * portfolio optimisation Subject RIV: AH - Economic s OBOR OECD: Economic Theory Impact factor: 0.747, year: 2016 http://library.utia.cas.cz/separaty/2017/E/barunik-0478479.pdf

  2. Wind power forecasting: IEA Wind Task 36 & future research issues

    DEFF Research Database (Denmark)

    Giebel, Gregor; Cline, J.; Frank, Helmut Paul

    2016-01-01

    the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD...

  3. Multiresolution forecasting for futures trading using wavelet decompositions.

    Science.gov (United States)

    Zhang, B L; Coggins, R; Jabri, M A; Dersch, D; Flower, B

    2001-01-01

    We investigate the effectiveness of a financial time-series forecasting strategy which exploits the multiresolution property of the wavelet transform. A financial series is decomposed into an over complete, shift invariant scale-related representation. In transform space, each individual wavelet series is modeled by a separate multilayer perceptron (MLP). We apply the Bayesian method of automatic relevance determination to choose short past windows (short-term history) for the inputs to the MLPs at lower scales and long past windows (long-term history) at higher scales. To form the overall forecast, the individual forecasts are then recombined by the linear reconstruction property of the inverse transform with the chosen autocorrelation shell representation, or by another perceptron which learns the weight of each scale in the prediction of the original time series. The forecast results are then passed to a money management system to generate trades.

  4. Satellites, tweets, forecasts: the future of flood disaster management?

    Science.gov (United States)

    Dottori, Francesco; Kalas, Milan; Lorini, Valerio; Wania, Annett; Pappenberger, Florian; Salamon, Peter; Ramos, Maria Helena; Cloke, Hannah; Castillo, Carlos

    2017-04-01

    Floods have devastating effects on lives and livelihoods around the world. Structural flood defence measures such as dikes and dams can help protect people. However, it is the emerging science and technologies for flood disaster management and preparedness, such as increasingly accurate flood forecasting systems, high-resolution satellite monitoring, rapid risk mapping, and the unique strength of social media information and crowdsourcing, that are most promising for reducing the impacts of flooding. Here, we describe an innovative framework which integrates in real-time two components of the Copernicus Emergency mapping services, namely the European Flood Awareness System and the satellite-based Rapid Mapping, with new procedures for rapid risk assessment and social media and news monitoring. The integrated framework enables improved flood impact forecast, thanks to the real-time integration of forecasting and monitoring components, and increases the timeliness and efficiency of satellite mapping, with the aim of capturing flood peaks and following the evolution of flooding processes. Thanks to the proposed framework, emergency responders will have access to a broad range of timely and accurate information for more effective and robust planning, decision-making, and resource allocation.

  5. Oil price assumptions in macroeconomic forecasts: should we follow future market expectations?

    International Nuclear Information System (INIS)

    Coimbra, C.; Esteves, P.S.

    2004-01-01

    In macroeconomic forecasting, in spite of its important role in price and activity developments, oil prices are usually taken as an exogenous variable, for which assumptions have to be made. This paper evaluates the forecasting performance of futures market prices against the other popular technical procedure, the carry-over assumption. The results suggest that there is almost no difference between opting for futures market prices or using the carry-over assumption for short-term forecasting horizons (up to 12 months), while, for longer-term horizons, they favour the use of futures market prices. However, as futures market prices reflect market expectations for world economic activity, futures oil prices should be adjusted whenever market expectations for world economic growth are different to the values underlying the macroeconomic scenarios, in order to fully ensure the internal consistency of those scenarios. (Author)

  6. Can the dynamics of the term structure of petroleum futures be forecasted? Evidence from major markets

    International Nuclear Information System (INIS)

    Skiadopoulos, George; Chantziara, Thalia

    2008-01-01

    We investigate whether the daily evolution of the term structure of petroleum futures can be forecasted. To this end, the principal components analysis is employed. The retained principal components describe the dynamics of the term structure of futures prices parsimoniously and are used to forecast the subsequent daily changes of futures prices. Data on the New York Mercantile Exchange (NYMEX) crude oil, heating oil, gasoline, and the International Petroleum Exchange (IPE) crude oil futures are used. We find that the retained principal components have small forecasting power both in-sample and out-of-sample. Similar results are obtained from standard univariate and vector autoregression models. Spillover effects between the four petroleum futures markets are also detected. (author)

  7. How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

    Science.gov (United States)

    Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J

    2018-03-23

    Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.

  8. Internet pharmaceutical sales: attributes, concerns, and future forecast.

    Science.gov (United States)

    Bruckel, Katy; Capozzoli, Ernest A

    2003-01-01

    Internet pharmaceutical sales continue to skyrocket as healthcare providers and consumers are increasingly relying on the efficiencies and convenience that is available via such transactions. Managed care companies, increasing demands to reduce healthcare inefficiencies while maximizing the quality of patient care is a significant contributing factor to the expanding utilization and success of online pharmaceutical sales. However, with the expansion of Internet pharmaceutical sales, healthcare providers, pharmacy benefit management and insurance companies, and consumers realize new opportunities and risks. This paper will review the attributes and concerns associated with online pharmaceutical sales, discussing current and pending legislation intended to more effectively manage these parameters.

  9. EnerFuture: Long Term Energy Scenarios 'Understanding our energy future'. Key graphs and analysis, Enerdata - Global Energy Forecasting

    International Nuclear Information System (INIS)

    2011-01-01

    Enerdata analyses 4 future energy scenarios accounting for 2 economic growth assumptions combined with 2 alternative carbon emission mitigation policies. In this study, a series of analyses supported by graphs assess the energy consumption and intensity forecasts in emerging and developed markets. In particular, one analysis is dedicated to energies competition, including gas, coal and renewable energies. (authors)

  10. Forecasting European Wildfires Today and in the Future

    Science.gov (United States)

    Navarro Abellan, Maria; Porras Alegre, Ignasi; María Sole, Josep; Gálvez, Pedro; Bielski, Conrad; Nurmi, Pertti

    2017-04-01

    Society as a whole is increasingly exposed and vulnerable to natural disasters due to extreme weather events exacerbated by climate change. The increased frequency of wildfires is not only a result of a changing climate, but wildfires themselves also produce a significant amount of greenhouse gases that, in-turn, further contribute to global warming. I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) is an innovation project funded by the European Commission , which aims to use social media, smartphones and wearables to improve natural disaster management by integrating existing services, both local and European, into a platform that supports the entire emergency management cycle. In order to assess the impact of climate change on wildfire hazards, METEOSIM designed two different System Processes (SP) that will be integrated into the I-REACT service that can provide information on a variety of time scales. SP1 - Climate Change Impact The climate change impact on climate variables related to fires is calculated by building an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CORDEX data. A validation and an Empirical-Statistical Downscaling (ESD) calibration are done to assess the changes in the past of the climatic variables related to wildfires (temperature, precipitation, wind, relative humidity and Fire Weather Index). Calculations in the trend and the frequency of extreme events of those variables are done for three time scales: near-term (2011-2040), mid-term (2041-2070) and long term (2071-2100). SP2 - Operational daily forecast of the Canadian Forest Fire Weather Index (FWI) Using ensemble data from the ECMWF and from the GLAMEPS (multi-model ensemble) models, both supplied by the Finnish Meteorological Institute (FMI), the Fire Weather Index (FWI) and its index components are produced for each ensemble member within a wide forecast time range, from a few hours up to 10 days resulting in a

  11. Forecasting the volatility of crude oil futures using intra-day data

    International Nuclear Information System (INIS)

    Sevi, Benoit

    2013-01-01

    We use the information in intra-day data to forecast the volatility of crude oil at a horizon of 1 to 66 days using a variety of models relying on the decomposition of realized variance in its positive or negative (semi-variances) part and its continuous or discontinuous part (jumps). We show the importance of these decompositions in predictive regressions using a number of specifications. Nevertheless, an important empirical finding comes from an out-of-sample analysis which unambiguously shows the limited interest of considering these components. Overall, our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance. (author)

  12. SSMA Science Reviewers' Forecasts for the Future of Science Education.

    Science.gov (United States)

    Jinks, Jerry; Hoffer, Terry

    1989-01-01

    Described is a study which was conducted as an exploratory assessment of science reviewers' perceptions for the future of science education. Arrives at interpretations for identified categories of computers and high technology, science curriculum, teacher education, training, certification, standards, teaching methods, and materials. (RT)

  13. Forecasting volatility and spillovers in crude oil spot, forward and future markets

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael); R. Tansuchat (Roengchai)

    2009-01-01

    textabstractCrude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas

  14. Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael); R. Tansuchat (Roengchai)

    2010-01-01

    textabstractCrude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas

  15. Exploring the applicability of future air quality predictions based on synoptic system forecasts

    International Nuclear Information System (INIS)

    Yuval; Broday, David M.; Alpert, Pinhas

    2012-01-01

    For a given emissions inventory, the general levels of air pollutants and the spatial distribution of their concentrations are determined by the physiochemical state of the atmosphere. Apart from the trivial seasonal and daily cycles, most of the variability is associated with the atmospheric synoptic scale. A simple methodology for assessing future levels of air pollutants' concentrations based on synoptic forecasts is presented. At short time scales the methodology is comparable and slightly better than persistence and seasonal forecasts at categorical classification of pollution levels. It's utility is shown for air quality studies at the long time scale of a changing climate scenario, where seasonality and persistence cannot be used. It is demonstrated that the air quality variability due to changes in the pollution emissions can be expected to be much larger than that associated with the effects of climatic changes. - Highlights: ► A method for short and long term air quality forecasts is introduced. ► The method is based on prediction of synoptic systems. ► The method beats simple benchmarks in short term forecasts. ► Assessment of future air pollution in a changing climate scenario is demonstrated. - Air quality in a changing climate scenario can be studied using air pollution predictions based on synoptic system forecasts.

  16. Forecasting future prevalence of type 2 diabetes mellitus in Syria.

    Science.gov (United States)

    Al Ali, Radwan; Mzayek, Fawaz; Rastam, Samer; M Fouad, Fouad; O'Flaherty, Martin; Capewell, Simon; Maziak, Wasim

    2013-05-25

    Type 2 diabetes mellitus (T2DM) is increasingly becoming a major public health problem worldwide. Estimating the future burden of diabetes is instrumental to guide the public health response to the epidemic. This study aims to project the prevalence of T2DM among adults in Syria over the period 2003-2022 by applying a modelling approach to the country's own data. Future prevalence of T2DM in Syria was estimated among adults aged 25 years and older for the period 2003-2022 using the IMPACT Diabetes Model (a discrete-state Markov model). According to our model, the prevalence of T2DM in Syria is projected to double in the period between 2003 and 2022 (from 10% to 21%). The projected increase in T2DM prevalence is higher in men (148%) than in women (93%). The increase in prevalence of T2DM is expected to be most marked in people younger than 55 years especially the 25-34 years age group. The future projections of T2DM in Syria put it amongst countries with the highest levels of T2DM worldwide. It is estimated that by 2022 approximately a fifth of the Syrian population aged 25 years and older will have T2DM.

  17. Oil Price Forecasting Using Crack Spread Futures and Oil Exchange Traded Funds

    Directory of Open Access Journals (Sweden)

    Hankyeung Choi

    2015-04-01

    Full Text Available Given the emerging consensus from previous studies that crude oil and refined product (as well as crack spread prices are cointegrated, this study examines the link between the crude oil spot and crack spread derivatives markets. Specifically, the usefulness of the two crack spread derivatives products (namely, crack spread futures and the ETF crack spread for modeling and forecasting daily OPEC crude oil spot prices is evaluated. Based on the results of a structural break test, the sample is divided into pre-crisis, crisis, and post-crisis periods. We find a unidirectional relationship from the two crack spread derivatives markets to the crude oil spot market during the post-crisis period. In terms of forecasting performance, the forecasting models based on crack spread futures and the ETF crack spread outperform the Random Walk Model (RWM, both in-sample and out-of-sample. In addition, on average, the results suggest that information from the ETF crack spread market contributes more to the forecasting models than information from the crack spread futures market.

  18. Dollarization in East Africa: Causes, Consequences, and Future Forecasts

    Directory of Open Access Journals (Sweden)

    Osman Sayid Hassan Musse

    2017-05-01

    Full Text Available The dollarization phenomenon has been widespread among the East African countries for many decades. This trend results in several consequences that might be either beneficial or harmful to these countries and their likes.The objective of this research was to empirically examine the causes, consequences and the future scenarios of dollarization in one of the leading regional countries such as Somalia. The research used a survey of over 100respondents and applied descriptive statistics and t-tests to achieve the above objectives. The findings show that the main causes of Dollarization in Somalia are the implementation of the Hawallah (money transfer system,the remarkable absence of the central bank and other monitoring financial authorities, the increasing exports and imports of the Somalian economy, the loss of confidence in the local Somalian Shilling, and the relative ease atwhich the Somalian Shilling can be printed and manipulated by selected market players. These causes are found to be mainly triggered by the revenue from exports, the policies and regulations implemented by the Somali government, the Somali Diaspora, and the international aid organizations. This has resulted in the foreign traders buying Somali goods at a relatively lower price and taking advantage of the depreciated Somali Shilling against most international currencies.

  19. Future Missions for Space Weather Specifications and Forecasts

    Science.gov (United States)

    Onsager, T. G.; Biesecker, D. A.; Anthes, R. A.; Maier, M. W.; Gallagher, F. W., III; St Germain, K.

    2017-12-01

    The progress of technology and the global integration of our economic and security infrastructures have introduced vulnerabilities to space weather that demand a more comprehensive ability to specify and to predict the dynamics of the space environment. This requires a comprehensive network of real-time space-based and ground-based observations with long-term continuity. In order to determine the most cost effective space architectures for NOAA's weather, space weather, and environmental missions, NOAA conducted the NOAA Satellite Observing System Architecture (NSOSA) study. This presentation will summarize the process used to document the future needs and the relative priorities for NOAA's operational space-based observations. This involves specifying the most important observations, defining the performance attributes at different levels of capability, and assigning priorities for achieving the higher capability levels. The highest priority observations recommended by the Space Platform Requirements Working Group (SPRWG) for improvement above a minimal capability level will be described. Finally, numerous possible satellite architectures have been explored to assess the costs and benefits of various architecture configurations.

  20. Detection and forecasting of oyster norovirus outbreaks: recent advances and future perspectives.

    Science.gov (United States)

    Wang, Jiao; Deng, Zhiqiang

    2012-09-01

    Norovirus is a highly infectious pathogen that is commonly found in oysters growing in fecally contaminated waters. Norovirus outbreaks can cause the closure of oyster harvesting waters and acute gastroenteritis in humans associated with consumption of contaminated raw oysters. Extensive efforts and progresses have been made in detection and forecasting of oyster norovirus outbreaks over the past decades. The main objective of this paper is to provide a literature review of methods and techniques for detecting and forecasting oyster norovirus outbreaks and thereby to identify the future directions for improving the detection and forecasting of norovirus outbreaks. It is found that (1) norovirus outbreaks display strong seasonality with the outbreak peak occurring commonly in December-March in the U.S. and April-May in the Europe; (2) norovirus outbreaks are affected by multiple environmental factors, including but not limited to precipitation, temperature, solar radiation, wind, and salinity; (3) various modeling approaches may be employed to forecast norovirus outbreaks, including Bayesian models, regression models, Artificial Neural Networks, and process-based models; and (4) diverse techniques are available for near real-time detection of norovirus outbreaks, including multiplex PCR, seminested PCR, real-time PCR, quantitative PCR, and satellite remote sensing. The findings are important to the management of oyster growing waters and to future investigations into norovirus outbreaks. It is recommended that a combined approach of sensor-assisted real time monitoring and modeling-based forecasting should be utilized for an efficient and effective detection and forecasting of norovirus outbreaks caused by consumption of contaminated oysters. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. When idols look into the future: fair treatment modulates the affective forecasting error in talent show candidates.

    Science.gov (United States)

    Feys, Marjolein; Anseel, Frederik

    2015-03-01

    People's affective forecasts are often inaccurate because they tend to overestimate how they will feel after an event. As life decisions are often based on affective forecasts, it is crucial to find ways to manage forecasting errors. We examined the impact of a fair treatment on forecasting errors in candidates in a Belgian reality TV talent show. We found that perceptions of fair treatment increased the forecasting error for losers (a negative audition decision) but decreased it for winners (a positive audition decision). For winners, this effect was even more pronounced when candidates were highly invested in their self-view as a future pop idol whereas for losers, the effect was more pronounced when importance was low. The results in this study point to a potential paradox between maximizing happiness and decreasing forecasting errors. A fair treatment increased the forecasting error for losers, but actually made them happier. © 2014 The British Psychological Society.

  2. [Yellow fever in Western Africa, 1973-1987. Observed facts--studies realized, campaign, prevention and forecast].

    Science.gov (United States)

    Cordellier, R

    1990-01-01

    This global analysis of the situation is based on a review of notifications, observations and studies concerning yellow fever in 16 of 17 countries of the West African subregion (Algeria is not affected for the years 1973-1987). In view of this analysis and the epidemiological picture, the author proposes a plan of concerted action to confine yellow fever to its monkey-to-monkey cycle in the wild. Official notifications vary greatly from one country to the next. Any of five major causes could explain this: ecological and ethological conditions that favour circulation of the virus in the wild and man-to-man transmission to different extents; the immune status of the populations; the difficulty of diagnosing especially isolated cases; lack of means for investigation; and negligence. The quantity and gravity of human cases are systematically underestimated, sometimes to a great extent. Lack of resources and difficulty of diagnosis, but also in many instances the attitude of the population, can account for this. Modern means of investigation, faster intervention by specialists, and better knowledge of how the virus is transmitted, have shown recently an increasing gap between notifications and the actual situation. Research and monitoring programmes are particularly important. The programmes under way in Senegal and Côte d'Ivoire have already resulted in considerable improvement in the action against epidemics. Because of these programmes, our knowledge of the very complex pattern of viral circulation is improving, thereby helping us develop systems for prevention and enabling us to forecast epidemics. Priority areas for study and research are: (i) Basic programmes for detailed study of all the topotypes of the virus, and identification of the viral amplification cycles that recur over several years. Such studies are under way in Senegal and Côte d'Ivoire. They would be particularly useful in Ghana and in Nigeria, where the taxonomy and bioecology of A. africanus s

  3. Will the NP workforce grow in the future? New forecasts and implications for healthcare delivery.

    Science.gov (United States)

    Auerbach, David I

    2012-07-01

    The nurse practitioner (NP) workforce has been a focus of considerable policy interest recently, particularly as the Patient Protection and Affordable Care Act may place additional demands on the healthcare professional workforce. The NP workforce has been growing rapidly in recent years, but fluctuation in enrollments in the past decades has resulted in a wide range of forecasts. To forecast the future NP workforce using a novel method that has been applied to the registered nurse and physician workforces and is robust to fluctuating enrollment trends. An age-cohort regression-based model was applied to the current and historical workforce, which was then forecasted to future years assuming stable age effects and a continuation of recent cohort trends. A total of 6798 NPs who were identified as having completed NP training in the National Sample Survey of Registered Nurses between 1992 and 2008. The future workforce is projected to grow to 244,000 in 2025, an increase of 94% from 128,000 in 2008. If NPs are defined more restrictively as those who self-identify their position title as "NP," supply is projected to grow from 86,000 to 198,000 (130%) over this period. The large projected increase in NP supply is higher and more grounded than other forecasts and has several implications: NPs will likely fulfill a substantial amount of future demand for care. Furthermore, as the ratio of NPs to Nurse Practitioners to physicians will surely grow, there could be implications for quality of care and for the configuration of future care delivery systems.

  4. Motivated prediction of future feelings: effects of negative mood and mood orientation on affective forecasts.

    Science.gov (United States)

    Buehler, Roger; McFarland, Cathy; Spyropoulos, Vassili; Lam, Kent C H

    2007-09-01

    This article examines the role of motivational factors in affective forecasting. The primary hypothesis was that people predict positive emotional reactions to future events when they are motivated to enhance their current feelings. Three experiments manipulated participants' moods (negative vs. neutral) and orientation toward their moods (reflective vs. ruminative) and then assessed the positivity of their affective predictions for future events. As hypothesized, when participants adopted a reflective orientation, and thus should have been motivated to engage in mood-regulation processes, they predicted more positive feelings in the negative than in the neutral mood condition. This pattern of mood-incongruent affective prediction was not exhibited when participants adopted a ruminative orientation. Additionally, within the negative mood condition, generating affective forecasts had a more positive emotional impact on reflectors than on ruminators. The findings suggest that affective predictions are sometimes driven by mood-regulatory motives.

  5. "Forecasting Volatility and Spillovers in Crude Oil Spot, Forward and Futures Markets"

    OpenAIRE

    Chia-Lin Chang; Michael McAleer; Roengchai Tansuchat

    2009-01-01

    Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at- Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia- Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover effects across and within the four mar...

  6. Past speculations of the future: a review of the methods used for forecasting emerging health technologies.

    Science.gov (United States)

    Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

    2016-03-10

    Forecasting can support rational decision-making around the introduction and use of emerging health technologies and prevent investment in technologies that have limited long-term potential. However, forecasting methods need to be credible. We performed a systematic search to identify the methods used in forecasting studies to predict future health technologies within a 3-20-year timeframe. Identification and retrospective assessment of such methods potentially offer a route to more reliable prediction. Systematic search of the literature to identify studies reported on methods of forecasting in healthcare. People are not needed in this study. The authors searched MEDLINE, EMBASE, PsychINFO and grey literature sources, and included articles published in English that reported their methods and a list of identified technologies. Studies reporting methods used to predict future health technologies within a 3-20-year timeframe with an identified list of individual healthcare technologies. Commercially sponsored reviews, long-term futurology studies (with over 20-year timeframes) and speculative editorials were excluded. 15 studies met our inclusion criteria. Our results showed that the majority of studies (13/15) consulted experts either alone or in combination with other methods such as literature searching. Only 2 studies used more complex forecasting tools such as scenario building. The methodological fundamentals of formal 3-20-year prediction are consistent but vary in details. Further research needs to be conducted to ascertain if the predictions made were accurate and whether accuracy varies by the methods used or by the types of technologies identified. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  7. MEDIA ENVIRONMENT AS FACTOR OF REALIZATION OF CREATIVE POTENTIAL OF FUTURE TEACHERS` IN THE MOUNTAIN SCHOOLS OF THE UKRAINIAN CARPATHIANS

    Directory of Open Access Journals (Sweden)

    Alla Lebedieva

    2015-04-01

    Full Text Available The article shows up “media environment” as a factor of future teachers` creative potential realization in the mountainous schools of the Ukrainian Carpathians. The problem of using media environment as a factor of future teachers` creative potential in the mountainous schools of the Ukrainian Carpathians and the ways of its optimization is the main point of this research. Highlights ways to modernize social and professional orientation training of students in the creative process of nature is situates in information education and educational environment of high school. We consider the causal link use media environment as a factor of future teachers` creative potential and complexity of the teacher in the mountainous schools of the Ukrainian Carpathians. The basic function of the media environment are extensity, instrumental, communicative, interactive, multimedia. Reveals some aspects of training students to creatively active teaching process we describe subjects with objective possibilities in the formation of professional skills of future teachers` and which directly affect the realization of creative potential – “Ukrainian folk art”, “Basic recitation and rhetoric”, “The basis of pedagogical creativity”. The necessity of creating a full-fledged media environment in higher education is important condition of successful education as an important factor that allows the efficiency of the creative potential of future teachers` in the mountainous schools of the Ukrainian Carpathians.

  8. Rate of recovery from perturbations as a means to forecast future stability of living systems.

    Science.gov (United States)

    Ghadami, Amin; Gourgou, Eleni; Epureanu, Bogdan I

    2018-06-18

    Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system's response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds.

  9. Inference from the futures: ranking the noise cancelling accuracy of realized measures

    DEFF Research Database (Denmark)

    Mirone, Giorgio

    We consider the log-linear relationship between futures contracts and their underlying assets and show that in the classical Brownian semi-martingale (BSM) framework the two series must, by no-arbitrage, have the same integrated variance. We then introduce the concept of noise cancelling...... measures in the presence of noise. Moreover, a thorough simulation analysis is employed to evaluate the estimators' sensitivity to different price and noise processes, and sampling frequencies....

  10. Realized Volatility Risk

    NARCIS (Netherlands)

    D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)

    2013-01-01

    textabstractIn this paper we document that realized variation measures constructed from highfrequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive.

  11. Asymmetric Realized Volatility Risk

    NARCIS (Netherlands)

    D.E. Allen (David); M.J. McAleer (Michael); M. Scharth (Marcel)

    2014-01-01

    markdownabstract__Abstract__ In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized

  12. Forecasting of future earthquakes in the northeast region of India considering energy released concept

    Science.gov (United States)

    Zarola, Amit; Sil, Arjun

    2018-04-01

    This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

  13. Technopolis Toward Realization (II) : State-of-the-art and the Future

    Science.gov (United States)

    Okubo, Kaname

    The measures to support technopolis construction taken by the Ministry of International Trade and Industry are introduced at first : for instance, a system of taxation to promote technopolis, a system of special interest for promoting regional development, budgetary measure to support R & D in the regions, subsidy for developmental organizations of technopolis. The purpose of the each system, persons and facilities involved in it, application period and the subsidiary rates are also introduced. As the present status of technopolis construction which has started already smoothly, the following matters are described showing some examples : arrangement of R & D and information functions, active policy development for promoting regional industries taken by Technopolis Development Organization by means of debt guarantee project, human resource fostering project and so on ; present research activities by cooperation among industry, government, academic institution. Reinforcement of parent-megaropolis function and cooperation between industry and academic organizations, and town construction with ideally abundant scope and spare are mentioned as future subjects to be considered.

  14. A general improved methodology to forecasting future oil production: Application to the UK and Norway

    International Nuclear Information System (INIS)

    Fiévet, L.; Forró, Z.; Cauwels, P.; Sornette, D.

    2015-01-01

    We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field discoveries. Compared with the standard methodology that tends to underestimate remaining oil reserves, our method gives a better description of future oil production, as validated by our back-tests starting in 2008. Specifically, we predict remaining reserves extractable until 2030 to be 5.7 ± 0.3 billion barrels for Norway and 3.0 ± 0.3 billion barrels for the UK, which are respectively 45% and 66% above the predictions using an extrapolation of aggregate production. - Highlights: • Two step methodology to forecast a countries oil production. • Nonlinear extrapolation of the performance of individual fields. • Stochastic model of the frequency of future discoveries. • Backtest starting in 2008 of the methodology. • Improvement upon standard extrapolation of aggregate production

  15. Realization of Interdisciplinary Communications of Fundamental Disciplines and Disciplines of Mathematical Cycle in the Preparation of Future Programmers

    Directory of Open Access Journals (Sweden)

    Miсhaеl Lvov

    2016-02-01

    Full Text Available The article is devoted to interdisciplinary communication in the process of preparation of the future programmers and implementation of the basic principles of these relations in the study of disciplines of professional and practical training and math courses. The article deals with the role of interdisciplinary connections, as well as their function and significance for the formation of cognitive activity, independence and positive learning motivation. The focus is on methodological aspects of realization of interdisciplinary communications at studying basic disciplines of training future programmers and disciplines of mathematical cycle. In particular, the issues of realization of interdisciplinary communications during the study such disciplines as "Computer graphics, computational geometry," "Basics of algorithms and programming", "Programming Technologies" and the course "Analytical geometry and linear algebra", which included in to normative part of the training of programmers. This article describes the theoretical aspects of the implementation of interdisciplinary connections in the study of these disciplines, as well as examples of practical tasks with which these relationships can be implemented most effectively during training

  16. Harmful algal blooms and climate change: Learning from the past and present to forecast the future

    CSIR Research Space (South Africa)

    Wells, ML

    2015-11-01

    Full Text Available Harmful algal blooms and climate change: Learning from the past and present to forecast the future Mark L. Wellsa,*, Vera L. Trainerb, Theodore J. Smaydac, Bengt S.O. Karlsond, Charles G. Tricke, Raphael M. Kudelaf, Akira Ishikawag, Stewart Bernardh... and Atmospheric Administration, 2725 Montlake Blvd. E., Seattle, WA 98112, USA c Graduate School of Oceanography, University of Rhode Island, Kingston, RI 02881, USA d SMHI Research & Development, Oceanography, Sven Ka¨llfelts gata 15, 426 71 Va¨stra Fro...

  17. Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

    Directory of Open Access Journals (Sweden)

    Suchithra Naish

    Full Text Available BACKGROUND: Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV disease under climate change scenarios in Queensland, Australia. METHODS/PRINCIPAL FINDINGS: We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall, socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. CONCLUSIONS/SIGNIFICANCE: We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

  18. Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

    Science.gov (United States)

    Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

    2013-01-01

    Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

  19. Forecasts of county-level land uses under three future scenarios: a technical document supporting the Forest Service 2010 RPA Assessment

    Science.gov (United States)

    David N. Wear

    2011-01-01

    Accurately forecasting future forest conditions and the implications for ecosystem services depends on understanding land use dynamics. In support of the 2010 Renewable Resources Planning Act (RPA) Assessment, we forecast changes in land uses for the coterminous United States in response to three scenarios. Our land use models forecast urbanization in response to the...

  20. Tension between SNeIa and BAO: current status and future forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Escamilla-Rivera, Celia [Astrophysics, University of Oxford, DWD, Kebble Road, Oxford, OX1 3RH (United Kingdom); Lazkoz, Ruth; Salzano, Vincenzo; Sendra, Irene, E-mail: celia_escamilla@ehu.es, E-mail: ruth.lazkoz@ehu.es, E-mail: vincenzo.salzano@ehu.es, E-mail: irene.sendra@ehu.es [Fisika Teorikoaren eta Zientziaren Historia Saila, Zientzia eta Teknologia Fakultatea, Euskal Herriko Unibertsitatea, 644 Posta Kutxatila, 48080 Bilbao (Spain)

    2011-09-01

    Using real and synthetic Type Ia SNe (SNeIa) and baryon acoustic oscillations (BAO) data representing current observations forecasts, this paper investigates the tension between those probes in the dark energy equation of state (EoS) reconstruction considering the well known CPL model and Wang's low correlation reformulation. In particular, here we present simulations of BAO data from both the the radial and transverse directions. We also explore the influence of priors on Ω{sub m} and Ω{sub b} on the tension issue, by considering 1σ deviations in either one or both of them. Our results indicate that for some priors there is no tension between a single dataset (either SNeIa or BAO) and their combination (SNeIa+BAO). Our criterion to discern the existence of tension (σ-distance) is also useful to establish which is the dataset with most constraining power; in this respect SNeIa and BAO data switch roles when current and future data are considered, as forecasts predict and spectacular quality improvement on BAO data. We also find that the results on the tension are blind to the way the CPL model is addressed: there is a perfect match between the original formulation and that by the correlation optimized proposed in Wang (2008), but the errors on the parameters are much narrower in all cases of our exhaustive exploration, thus serving the purpose of stressing the convenience of this reparametrization.

  1. Tension between SNeIa and BAO: current status and future forecasts

    International Nuclear Information System (INIS)

    Escamilla-Rivera, Celia; Lazkoz, Ruth; Salzano, Vincenzo; Sendra, Irene

    2011-01-01

    Using real and synthetic Type Ia SNe (SNeIa) and baryon acoustic oscillations (BAO) data representing current observations forecasts, this paper investigates the tension between those probes in the dark energy equation of state (EoS) reconstruction considering the well known CPL model and Wang's low correlation reformulation. In particular, here we present simulations of BAO data from both the the radial and transverse directions. We also explore the influence of priors on Ω m and Ω b on the tension issue, by considering 1σ deviations in either one or both of them. Our results indicate that for some priors there is no tension between a single dataset (either SNeIa or BAO) and their combination (SNeIa+BAO). Our criterion to discern the existence of tension (σ-distance) is also useful to establish which is the dataset with most constraining power; in this respect SNeIa and BAO data switch roles when current and future data are considered, as forecasts predict and spectacular quality improvement on BAO data. We also find that the results on the tension are blind to the way the CPL model is addressed: there is a perfect match between the original formulation and that by the correlation optimized proposed in Wang (2008), but the errors on the parameters are much narrower in all cases of our exhaustive exploration, thus serving the purpose of stressing the convenience of this reparametrization

  2. Taking Risks for the Future of Space Weather Forecasting, Research, and Operations

    Science.gov (United States)

    Jaynes, A. N.; Baker, D. N.; Kanekal, S. G.; Li, X.; Turner, D. L.

    2017-12-01

    Taking Risks for the Future of Space Weather Forecasting, Research, and Operations The need for highly improved space weather modeling and monitoring is quickly becoming imperative as our society depends ever more on the sensitive technology that builds and connects our world. Instead of relying primarily on tried and true concepts, academic institutions and funding agencies alike should be focusing on truly new and innovative ways to solve this pressing problem. In this exciting time, where student-led groups can launch CubeSats for under a million dollars and companies like SpaceX are actively reducing the cost-cap of access to space, the space physics community should be pushing the boundaries of what is possible to enhance our understanding of the space environment. Taking great risks in instrumentation, mission concepts, operational development, collaborations, and scientific research is the best way to move our field forward to where it needs to be for the betterment of science and society.

  3. Latent Patient Cluster Discovery for Robust Future Forecasting and New-Patient Generalization.

    Directory of Open Access Journals (Sweden)

    Ting Qian

    Full Text Available Commonly referred to as predictive modeling, the use of machine learning and statistical methods to improve healthcare outcomes has recently gained traction in biomedical informatics research. Given the vast opportunities enabled by large Electronic Health Records (EHR data and powerful resources for conducting predictive modeling, we argue that it is yet crucial to first carefully examine the prediction task and then choose predictive methods accordingly. Specifically, we argue that there are at least three distinct prediction tasks that are often conflated in biomedical research: 1 data imputation, where a model fills in the missing values in a dataset, 2 future forecasting, where a model projects the development of a medical condition for a known patient based on existing observations, and 3 new-patient generalization, where a model transfers the knowledge learned from previously observed patients to newly encountered ones. Importantly, the latter two tasks-future forecasting and new-patient generalizations-tend to be more difficult than data imputation as they require predictions to be made on potentially out-of-sample data (i.e., data following a different predictable pattern from what has been learned by the model. Using hearing loss progression as an example, we investigate three regression models and show that the modeling of latent clusters is a robust method for addressing the more challenging prediction scenarios. Overall, our findings suggest that there exist significant differences between various kinds of prediction tasks and that it is important to evaluate the merits of a predictive model relative to the specific purpose of a prediction task.

  4. Latent Patient Cluster Discovery for Robust Future Forecasting and New-Patient Generalization.

    Science.gov (United States)

    Qian, Ting; Masino, Aaron J

    2016-01-01

    Commonly referred to as predictive modeling, the use of machine learning and statistical methods to improve healthcare outcomes has recently gained traction in biomedical informatics research. Given the vast opportunities enabled by large Electronic Health Records (EHR) data and powerful resources for conducting predictive modeling, we argue that it is yet crucial to first carefully examine the prediction task and then choose predictive methods accordingly. Specifically, we argue that there are at least three distinct prediction tasks that are often conflated in biomedical research: 1) data imputation, where a model fills in the missing values in a dataset, 2) future forecasting, where a model projects the development of a medical condition for a known patient based on existing observations, and 3) new-patient generalization, where a model transfers the knowledge learned from previously observed patients to newly encountered ones. Importantly, the latter two tasks-future forecasting and new-patient generalizations-tend to be more difficult than data imputation as they require predictions to be made on potentially out-of-sample data (i.e., data following a different predictable pattern from what has been learned by the model). Using hearing loss progression as an example, we investigate three regression models and show that the modeling of latent clusters is a robust method for addressing the more challenging prediction scenarios. Overall, our findings suggest that there exist significant differences between various kinds of prediction tasks and that it is important to evaluate the merits of a predictive model relative to the specific purpose of a prediction task.

  5. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    KAUST Repository

    El-Samra, R.

    2017-02-15

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  6. Intelligible seminar on fusion reactors. (12) Next step toward the realization of fusion reactors. Future vision of fusion energy research and development

    International Nuclear Information System (INIS)

    Okano, Kunihiko; Kurihara, Kenichi; Tobita, Kenji

    2006-01-01

    In the last session of this seminar the progress of research and development for the realization of fusion reactors and future vision of fusion energy research and development are summarized. The some problems to be solved when the commercial fusion reactors would be realized, (1) production of deuterium as the fuel, (2) why need the thermonuclear reactors, (3) environmental problems, and (4) ITER project, are described. (H. Mase)

  7. Forecasting the density of oil futures returns using model-free implied volatility and high-frequency data

    International Nuclear Information System (INIS)

    Ielpo, Florian; Sevi, Benoit

    2013-09-01

    Forecasting the density of returns is useful for many purposes in finance, such as risk management activities, portfolio choice or derivative security pricing. Existing methods to forecast the density of returns either use prices of the asset of interest or option prices on this same asset. The latter method needs to convert the risk-neutral estimate of the density into a physical measure, which is computationally cumbersome. In this paper, we take the view of a practitioner who observes the implied volatility under the form of an index, namely the recent OVX, to forecast the density of oil futures returns for horizons going from 1 to 60 days. Using the recent methodology in Maheu and McCurdy (2011) to compute density predictions, we compare the performance of time series models using implied volatility and either daily or intra-daily futures prices. Our results indicate that models based on implied volatility deliver significantly better density forecasts at all horizons, which is in line with numerous studies delivering the same evidence for volatility point forecast. (authors)

  8. Linear and non-linear Modified Gravity forecasts with future surveys

    Science.gov (United States)

    Casas, Santiago; Kunz, Martin; Martinelli, Matteo; Pettorino, Valeria

    2017-12-01

    Modified Gravity theories generally affect the Poisson equation and the gravitational slip in an observable way, that can be parameterized by two generic functions (η and μ) of time and space. We bin their time dependence in redshift and present forecasts on each bin for future surveys like Euclid. We consider both Galaxy Clustering and Weak Lensing surveys, showing the impact of the non-linear regime, with two different semi-analytical approximations. In addition to these future observables, we use a prior covariance matrix derived from the Planck observations of the Cosmic Microwave Background. In this work we neglect the information from the cross correlation of these observables, and treat them as independent. Our results show that η and μ in different redshift bins are significantly correlated, but including non-linear scales reduces or even eliminates the correlation, breaking the degeneracy between Modified Gravity parameters and the overall amplitude of the matter power spectrum. We further apply a Zero-phase Component Analysis and identify which combinations of the Modified Gravity parameter amplitudes, in different redshift bins, are best constrained by future surveys. We extend the analysis to two particular parameterizations of μ and η and consider, in addition to Euclid, also SKA1, SKA2, DESI: we find in this case that future surveys will be able to constrain the current values of η and μ at the 2-5% level when using only linear scales (wavevector k < 0 . 15 h/Mpc), depending on the specific time parameterization; sensitivity improves to about 1% when non-linearities are included.

  9. Forecasting of future changes of state with the aid of Markov chains; Prognose zukuenftiger Zustandsaenderungen mit Markow-Ketten

    Energy Technology Data Exchange (ETDEWEB)

    Kaflowski, Grzegorz; Kizilcay, Mustafa [Siegen Univ. (Germany). Lehrstuhl fuer Elektrische Energieversorgung

    2010-02-15

    In long-term planning of modernization measures in electric power supplies, forecasting of the future behaviour of the equipment is of great importance for its optimum utilization. Based on limited historical information on the technical condition of a collective of equipment, its future changes of condition can be modelled using Markov chains, which may support an assessment of the time of modernization or replacement. (orig.)

  10. The National Opportunity for Interoperability and its Benefits for a Reliable, Robust, and Future Grid Realized Through Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Office of Energy Efficiency and Renewable Energy

    2016-02-01

    Today, increasing numbers of intermittent generation sources (e.g., wind and photovoltaic) and new mobile intermittent loads (e.g., electric vehicles) can significantly affect traditional utility business practices and operations. At the same time, a growing number of technologies and devices, from appliances to lighting systems, are being deployed at consumer premises that have more sophisticated controls and information that remain underused for anything beyond basic building equipment operations. The intersection of these two drivers is an untapped opportunity and underused resource that, if appropriately configured and realized in open standards, can provide significant energy efficiency and commensurate savings on utility bills, enhanced and lower cost reliability to utilities, and national economic benefits in the creation of new markets, sectors, and businesses being fueled by the seamless coordination of energy and information through device and technology interoperability. Or, as the Quadrennial Energy Review puts it, “A plethora of both consumer-level and grid-level devices are either in the market, under development, or at the conceptual stage. When tied together through the information technology that is increasingly being deployed on electric utilities’ distribution grids, they can be an important enabling part of the emerging grid of the future. However, what is missing is the ability for all of these devices to coordinate and communicate their operations with the grid, and among themselves, in a common language — an open standard.” In this paper, we define interoperability as the ability to exchange actionable information between two or more systems within a home or building, or across and within organizational boundaries. Interoperability relies on the shared meaning of the exchanged information, with agreed-upon expectations and consequences, for the response to the information exchange.

  11. Higgs-dilaton cosmology: An inflation-dark-energy connection and forecasts for future galaxy surveys

    Science.gov (United States)

    Casas, Santiago; Pauly, Martin; Rubio, Javier

    2018-02-01

    The Higgs-dilaton model is a scale-invariant extension of the Standard Model nonminimally coupled to gravity and containing just one additional degree of freedom on top of the Standard Model particle content. This minimalistic scenario predicts a set of measurable consistency relations between the inflationary observables and the dark-energy equation-of-state parameter. We present an alternative derivation of these consistency relations that highlights the connections and differences with the α -attractor scenario. We study how far these constraints allow one to distinguish the Higgs-dilaton model from Λ CDM and w CDM cosmologies. To this end we first analyze existing data sets using a Markov chain Monte Carlo approach. Second, we perform forecasts for future galaxy surveys using a Fisher matrix approach, both for galaxy clustering and weak lensing probes. Assuming that the best fit values in the different models remain comparable to the present ones, we show that both Euclid- and SKA2-like missions will be able to discriminate a Higgs-dilaton cosmology from Λ CDM and w CDM .

  12. Harmful algal blooms and climate change: Learning from the past and present to forecast the future

    Science.gov (United States)

    Wells, Mark L.; Trainer, Vera L.; Smayda, Theodore J.; Karlson, Bengt S.O.; Trick, Charles G.; Kudela, Raphael M.; Ishikawa, Akira; Bernard, Stewart; Wulff, Angela; Anderson, Donald M.; Cochlan, William P.

    2015-01-01

    Climate change pressures will influence marine planktonic systems globally, and it is conceivable that harmful algal blooms may increase in frequency and severity. These pressures will be manifest as alterations in temperature, stratification, light, ocean acidification, precipitation-induced nutrient inputs, and grazing, but absence of fundamental knowledge of the mechanisms driving harmful algal blooms frustrates most hope of forecasting their future prevalence. Summarized here is the consensus of a recent workshop held to address what currently is known and not known about the environmental conditions that favor initiation and maintenance of harmful algal blooms. There is expectation that harmful algal bloom (HAB) geographical domains should expand in some cases, as will seasonal windows of opportunity for harmful algal blooms at higher latitudes. Nonetheless there is only basic information to speculate upon which regions or habitats HAB species may be the most resilient or susceptible. Moreover, current research strategies are not well suited to inform these fundamental linkages. There is a critical absence of tenable hypotheses for how climate pressures mechanistically affect HAB species, and the lack of uniform experimental protocols limits the quantitative cross-investigation comparisons essential to advancement. A HAB “best practices” manual would help foster more uniform research strategies and protocols, and selection of a small target list of model HAB species or isolates for study would greatly promote the accumulation of knowledge. Despite the need to focus on keystone species, more studies need to address strain variability within species, their responses under multifactorial conditions, and the retrospective analyses of long-term plankton and cyst core data; research topics that are departures from the norm. Examples of some fundamental unknowns include how larger and more frequent extreme weather events may break down natural biogeographic

  13. Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models

    Science.gov (United States)

    2016-01-01

    The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today’s increasingly difficult and volatile financial futures markets. The main focus of this study is to facilitate forecasting by using an enhanced denoising process on market data, taken as a multivariate signal, in order to deduct the same noise from the open-high-low-close signal of a market. This research offers evidence on the predictive ability and the profitability of abnormal returns of a new hybrid forecasting model using Wavelet-PCA denoising and ANN (named WPCA-NN) on futures contracts of Hong Kong’s Hang Seng futures, Japan’s NIKKEI 225 futures, Singapore’s MSCI futures, South Korea’s KOSPI 200 futures, and Taiwan’s TAIEX futures from 2005 to 2014. Using a host of technical analysis indicators consisting of RSI, MACD, MACD Signal, Stochastic Fast %K, Stochastic Slow %K, Stochastic %D, and Ultimate Oscillator, empirical results show that the annual mean returns of WPCA-NN are more than the threshold buy-and-hold for the validation, test, and evaluation periods; this is inconsistent with the traditional random walk hypothesis, which insists that mechanical rules cannot outperform the threshold buy-and-hold. The findings, however, are consistent with literature that advocates technical analysis. PMID:27248692

  14. A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

    Science.gov (United States)

    Yasami, Yasser; Safaei, Farshad

    2018-02-01

    The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of

  15. Forecasting Financial Resources for Future Traumatic Spinal Cord Injury Care Using Simulation Modeling.

    Science.gov (United States)

    Ahn, Henry; Lewis, Rachel; Santos, Argelio; Cheng, Christiana L; Noonan, Vanessa K; Dvorak, Marcel F; Singh, Anoushka; Linassi, A Gary; Christie, Sean; Goytan, Michael; Atkins, Derek

    2017-10-15

    Survivors of traumatic spinal cord injury (tSCI) have intense healthcare needs during acute and rehabilitation care and often through the rest of life. To prepare for a growing and aging population, simulation modeling was used to forecast the change in healthcare financial resources and long-term patient outcomes between 2012 and 2032. The model was developed with data from acute and rehabilitation care facilities across Canada participating in the Access to Care and Timing project. Future population and tSCI incidence for 2012 and 2032 were predicted with data from Statistics Canada and the Canadian Institute for Health Information. The projected tSCI incidence for 2012 was validated with actual data from the Rick Hansen SCI Registry of the participating facilities. Using a medium growth scenario, in 2032, the projected median age of persons with tSCI is 57 and persons 61 and older will account for 46% of injuries. Admissions to acute and rehabilitation facilities in 2032 were projected to increase by 31% and 25%, respectively. Because of the demographic shift to an older population, an increase in total population life expectancy with tSCI of 13% was observed despite a 22% increase in total life years lost to tSCI between 2012 and 2032. Care cost increased 54%, and rest of life cost increased 37% in 2032, translating to an additional CAD $16.4 million. With the demographics and management of tSCI changing with an aging population, accurate projections for the increased demand on resources will be critical for decision makers when planning the delivery of healthcare after tSCI.

  16. Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan

    Science.gov (United States)

    Chen, Brian K.; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

    2016-01-01

    Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan’s future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model – the Japanese Future Elderly Model (FEM) – for Japan. We use the model to forecast disability and health for Japan’s future elderly. Our simulation suggests that by 2040, over 27 percent of Japan’s elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan’s future. PMID:28580275

  17. Cost Optimization of Water Resources in Pernambuco, Brazil: Valuing Future Infrastructure and Climate Forecasts

    Science.gov (United States)

    Kumar, Ipsita; Josset, Laureline; Lall, Upmanu; Cavalcanti e Silva, Erik; Cordeiro Possas, José Marcelo; Cauás Asfora, Marcelo

    2017-04-01

    Optimal management of water resources is paramount in semi-arid regions to limit strains on the society and economy due to limited water availability. This problem is likely to become even more recurrent as droughts are projected to intensify in the coming years, causing increasing stresses to the water supply in the concerned areas. The state of Pernambuco, in the Northeast Brazil is one such case, where one of the largest reservoir, Jucazinho, has been at approximately 1% capacity throughout 2016, making infrastructural challenges in the region very real. To ease some of the infrastructural stresses and reduce vulnerabilities of the water system, a new source of water from Rio São Francisco is currently under development. Till its development, water trucks have been regularly mandated to cover water deficits, but at a much higher cost, thus endangering the financial sustainability of the region. In this paper, we propose to evaluate the sustainability of the considered water system by formulating an optimization problem and determine the optimal operations to be conducted. We start with a comparative study of the current and future infrastructures capabilities to face various climate. We show that while the Rio Sao Francisco project mitigates the problems, both implementations do not prevent failure and require the reliance on water trucks during prolonged droughts. We also study the cost associated with the provision of water to the municipalities for several streamflow forecasts. In particular, we investigate the value of climate predictions to adapt operational decisions by comparing the results with a fixed policy derived from historical data. We show that the use of climate information permits the reduction of the water deficit and reduces overall operational costs. We conclude with a discussion on the potential of the approach to evaluate future infrastructure developments. This study is funded by the Inter-American Development Bank (IADB), and in

  18. Asymmetric Realized Volatility Risk

    Directory of Open Access Journals (Sweden)

    David E. Allen

    2014-06-01

    Full Text Available In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.

  19. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  20. FINANCIAL FUTURE PROSPECT INVESTIGATION USING BANKRUPTCY FORECASTING MODELS IN HUNGARIAN MEAT PROCESSING INDUSTRY

    Directory of Open Access Journals (Sweden)

    Dalma Peto

    2015-07-01

    Full Text Available Our main research topic is the analysis of leading companies in the Hungarian meat processing industry in terms of liquidity criteria. We examine this scientific subject by application of financial indicators and several important bankruptcy forecasting models. In our thesis the emphasis is placed on the presentation and evaluation of business failure models. The topicality of the research subject is rooted in the economic crisis and recession, which made solvency a key issue. Maintaining the competitive position in the market and the ability to stay in competition depend on the capability to generate an appropriate level of net operative cash flow. The most important research questions are the following. Which financial methods can be used to predict and estimate the situation when a company is facing bankruptcy? Do bankruptcy forecasting models provide accurate forecasts and what conclusions can be drawn based on these results? In our study we present the actual economic situation and the main problems of the sector, select the sample companies, calculate and compare the applied financial ratios and the most relevant bankruptcy forecasting models. On the basis of annual reports concerning 2010-2013 interval we investigate the financial position of leading pork processing companies. We make a comprehensive and comparative analysis concerning capital structure, liquidity, and profitability; consequently identify risky processes and companies having high probability of insolvency. Finally, we demonstrate and evaluate the results of three traditional bankruptcy forecasting models (Altman, Springate, and Fulmer and four modern models (DA, LR, industrial DA and industrial LR.

  1. Future wind power forecast errors, need for regulating power, and costs in the Swedish system

    Energy Technology Data Exchange (ETDEWEB)

    Carlsson, Fredrik [Vattenfall Research and Development AB, Stockholm (Sweden). Power Technology

    2011-07-01

    Wind power is one of the renewable energy sources in the electricity system that grows most rapid in Sweden. There are however two market challenges that need to be addressed with a higher proportion of wind power - that is variability and predictability. Predictability is important since the spot market Nord Pool Spot requires forecasts of production 12 - 36 hours ahead. The forecast errors must be regulated with regulating power, which is expensive for the actors causing the forecast errors. This paper has investigated a number of scenarios with 10 - 55 TWh of wind power installed in the Swedish system. The focus has been on a base scenario with 10 TWh new wind power consisting of 3,5 GW new wind power and 1,5 GW already installed power, which gives 5 GW. The results show that the costs for the forecast errors will increase as more intermittent production is installed. However, the increase can be limited by for instance trading on intraday market or increase quality of forecasts. (orig.)

  2. The economic value of realized volatility

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Feunou, Bruno; Jacobs, Kris

    2014-01-01

    Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so, we ...

  3. Securing America’s Future. Realizing the Potential of the Department of Energy’s National Laboratories

    Energy Technology Data Exchange (ETDEWEB)

    Glauthier, T. J. [TJG Energy Associates, LLC, Bloomberg, VA (United States); Cohon, Jared L. [Carnegie Mellon Univ., Pittsburgh, PA (United States); Augustine, Norman R. [U.S. Dept. of Homeland Security, Washington, DC (United States); Austin, Wanda M. [Aerospace Corporation, El Segundo, CA (United States); Elachi, Charles [California Inst. of Technology (CalTech), Pasadena, CA (United States); Fleury, Paul A. [Yale Univ., New Haven, CT (United States); Hockfield, Susan J. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Meserve, Richard A. [Covington and Burling LLP, Washington, DC (United States); Murray, Cherry A. [Harvard Univ., Cambridge, MA (United States)

    2015-10-23

    The Department of Energy (DOE) laboratories are national assets that have contributed profoundly to the Nation’s security, scientific leadership, and economic competitiveness. In recognition of the continuing and evolving threats to our security and the dramatic increase in global economic and scientific competition, the laboratories are and will continue to be vitally important. Yet, the contributions of the National Laboratories are not inevitable, nor have they realized their full potential. This final report of the Commission to Review the Effectiveness of the National Energy Laboratories recommends ways the laboratories could overcome challenges to more efficiently and effectively accomplish the work for which they are uniquely suited.

  4. Forecasting with Option-Implied Information

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Jacobs, Kris; Chang, Bo Young

    2013-01-01

    This chapter surveys the methods available for extracting information from option prices that can be used in forecasting. We consider option-implied volatilities, skewness, kurtosis, and densities. More generally, we discuss how any forecasting object that is a twice differentiable function...... of the future realization of the underlying risky asset price can utilize option-implied information in a well-defined manner. Going beyond the univariate option-implied density, we also consider results on option-implied covariance, correlation and beta forecasting, as well as the use of option......-implied information in cross-sectional forecasting of equity returns. We discuss how option-implied information can be adjusted for risk premia to remove biases in forecasting regressions....

  5. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  6. An Improved Approach for Forecasting Ecological Impacts from Future Drilling in Unconventional Shale Oil and Gas Plays.

    Science.gov (United States)

    Wolaver, Brad D; Pierre, Jon Paul; Ikonnikova, Svetlana A; Andrews, John R; McDaid, Guinevere; Ryberg, Wade A; Hibbitts, Toby J; Duran, Charles M; Labay, Benjamin J; LaDuc, Travis J

    2018-04-13

    Directional well drilling and hydraulic fracturing has enabled energy production from previously inaccessible resources, but caused vegetation conversion and landscape fragmentation, often in relatively undisturbed habitats. We improve forecasts of future ecological impacts from unconventional oil and gas play developments using a new, more spatially-explicit approach. We applied an energy production outlook model, which used geologic and economic data from thousands of wells and three oil price scenarios, to map future drilling patterns and evaluate the spatial distribution of vegetation conversion and habitat impacts. We forecast where future well pad construction may be most intense, illustrating with an example from the Eagle Ford Shale Play of Texas. We also illustrate the ecological utility of this approach using the Spot-tailed Earless Lizard (Holbrookia lacerata) as the focal species, which historically occupied much of the Eagle Ford and awaits a federal decision for possible Endangered Species Act protection. We found that ~17,000-45,500 wells would be drilled 2017‒2045 resulting in vegetation conversion of ~26,485-70,623 ha (0.73-1.96% of pre-development vegetation), depending on price scenario ($40-$80/barrel). Grasslands and row crop habitats were most affected (2.30 and 2.82% areal vegetation reduction). Our approach improves forecasts of where and to what extent future energy development in unconventional plays may change land-use and ecosystem services, enabling natural resource managers to anticipate and direct on-the-ground conservation actions to places where they will most effectively mitigate ecological impacts of well pads and associated infrastructure.

  7. Forecasting Exchange Rate Volatility in the Presence of Jumps

    DEFF Research Database (Denmark)

    Busch, Thomas; Christensen, Bent Jesper; Nielsen, Morten Ørregaard

    We study measures of foreign exchange rate volatility based on high-frequency (5-minute) $/DM exchange rate returns using recent nonparametric statistical techniquesto compute realized return volatility and its separate continuous sample path and jumpcomponents, and measures based on prices...... of exchange rate futures options, allowingcalculation of option implied volatility. We find that implied volatility is an informationallyefficient but biased forecast of future realized exchange rate volatility. Furthermore,we show that log-normality is an even better distributional approximation...... for impliedvolatility than for realized volatility in this market. Finally, we show that the jump componentof future realized exchange rate volatility is to some extent predictable, and thatoption implied volatility is the dominant forecast of the future jump component....

  8. Future mission studies: Forecasting solar flux directly from its chaotic time series

    Science.gov (United States)

    Ashrafi, S.

    1991-01-01

    The mathematical structure of the programs written to construct a nonlinear predictive model to forecast solar flux directly from its time series without reference to any underlying solar physics is presented. This method and the programs are written so that one could apply the same technique to forecast other chaotic time series, such as geomagnetic data, attitude and orbit data, and even financial indexes and stock market data. Perhaps the most important application of this technique to flight dynamics is to model Goddard Trajectory Determination System (GTDS) output of residues between observed position of spacecraft and calculated position with no drag (drag flag = off). This would result in a new model of drag working directly from observed data.

  9. Ten-year operational dust forecasting - Recent model development and future plans

    International Nuclear Information System (INIS)

    Kallos, G; Spyrou, C; Astitha, M; Mitsakou, C; Solomos, S; Kushta, J; Pytharoulis, I; Katsafados, P; Mavromatidis, E; Papantoniou, N; Vlastou, G

    2009-01-01

    The Sahara desert is one of the major sources of mineral dust on Earth, producing up to 2x10 8 t yr- 1 . A combined effort has been devoted during the last ten years at the University of Athens (UOA) from the Atmospheric Modeling and Weather Forecasting Group (AM and WFG) to the development of an analysis and forecasting tool that will provide early warning of Saharan dust outbreaks. The developed tool is the SKIRON limited-area forecasting system, based on the Eta limited area modeling system with embedded algorithms describing the dust cycle. A new version of the model is currently available, with extra features like eight-size particle bins, radiative transfer corrections, new dust source identification and utilization of rocky soil characterization and incorporation of more accurate deposition schemes. The new version of SKIRON modeling system is coupled with the photochemical model CAMx in order to study processes like the shading effect of dust particles on photochemical processes and the production of second and third generation of aerosols. Moreover, another new development in the AM and WFG is based on the RAMS model, with the incorporation of processes like dust and sea-salt production, gas and aqueous phase chemistry and particle formation. In this study, the major characteristics of the developed (and under development) modeling systems are presented, as well as the spatiotemporal distribution of the transported dust amounts, the interaction with anthropogenically-produced particles and the potential implications on radiative transfer.

  10. Ten-year operational dust forecasting - Recent model development and future plans

    Energy Technology Data Exchange (ETDEWEB)

    Kallos, G; Spyrou, C; Astitha, M; Mitsakou, C; Solomos, S; Kushta, J; Pytharoulis, I; Katsafados, P; Mavromatidis, E; Papantoniou, N; Vlastou, G [University of Athens, School of Physics, Atmospheric Modeling and Weather Forecasting Group - UOA/AM and WFG, University Campus, Bldg. PHYS-V, Athens 15784 (Greece)], E-mail: kallos@mg.uoa.gr

    2009-03-01

    The Sahara desert is one of the major sources of mineral dust on Earth, producing up to 2x10{sup 8} t yr-{sup 1}. A combined effort has been devoted during the last ten years at the University of Athens (UOA) from the Atmospheric Modeling and Weather Forecasting Group (AM and WFG) to the development of an analysis and forecasting tool that will provide early warning of Saharan dust outbreaks. The developed tool is the SKIRON limited-area forecasting system, based on the Eta limited area modeling system with embedded algorithms describing the dust cycle. A new version of the model is currently available, with extra features like eight-size particle bins, radiative transfer corrections, new dust source identification and utilization of rocky soil characterization and incorporation of more accurate deposition schemes. The new version of SKIRON modeling system is coupled with the photochemical model CAMx in order to study processes like the shading effect of dust particles on photochemical processes and the production of second and third generation of aerosols. Moreover, another new development in the AM and WFG is based on the RAMS model, with the incorporation of processes like dust and sea-salt production, gas and aqueous phase chemistry and particle formation. In this study, the major characteristics of the developed (and under development) modeling systems are presented, as well as the spatiotemporal distribution of the transported dust amounts, the interaction with anthropogenically-produced particles and the potential implications on radiative transfer.

  11. Latent Integrated Stochastic Volatility, Realized Volatility, and Implied Volatility: A State Space Approach

    DEFF Research Database (Denmark)

    Bach, Christian; Christensen, Bent Jesper

    process is downward biased. Implied volatility performs better than any of the alternative realized measures when forecasting future integrated volatility. The results are largely similar across the stock market (S&P 500), bond market (30-year U.S. T-bond), and foreign currency exchange market ($/£ )....

  12. Draft Forecasts from Real-Time Runs of Physics-Based Models - A Road to the Future

    Science.gov (United States)

    Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

    2008-01-01

    The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. After consultations with NOAA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

  13. Not all past events are equal: biased attention and emerging heuristics in children's past-to-future forecasting.

    Science.gov (United States)

    Lagattuta, Kristin Hansen; Sayfan, Liat

    2013-01-01

    Four- to 10-year-olds and adults (N = 265) responded to eight scenarios presented on an eye tracker. Each trial involved a character who encounters a perpetrator who had previously enacted positive (P), negative (N), or both types of actions toward him or her in varying sequences (NN, PP, PN, and NP). Participants predicted the character's thoughts about the likelihood of future events, emotion type and intensity, and decision to approach or avoid. All ages made more positive forecasts for PP > NP > PN > NN trials, with differentiation by past experience widening with age. Age-related increases in weighting the most recent past event also appeared in eye gaze. Individual differences in biased visual attention correlated with verbal judgments. Findings contribute to research on risk assessment, person perception, and heuristics in judgment and decision making. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

  14. The future of the Bonny Method – A Perspective on Danish Practice with a Forecast to the Future

    DEFF Research Database (Denmark)

    Bonde, Lars Ole

    2017-01-01

    The article presents the present situation of the Bonny Method of Guided Imagery and Music (GIM) in Denmark, with an outlook to the international context. The presentation is based on a survey (2016) with Danish GIM practitioners (n = 20) and relevant international surveys are introduced as compa...... as comparisons. Clinical applications of the different formats within the “Spectrum of GIM” are also presented and discussed in a Danish context; future potential of the many Bonny Method session formats is outlined, and implications for training are discussed....

  15. Forecasting the term structure of crude oil futures prices with neural networks

    Czech Academy of Sciences Publication Activity Database

    Baruník, Jozef; Malinská, B.

    2016-01-01

    Roč. 164, č. 1 (2016), s. 366-379 ISSN 0306-2619 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : Term structure * Nelson–Siegel model * Dynamic neural networks * Crude oil futures Subject RIV: AH - Economics Impact factor: 7.182, year: 2016 http://library.utia.cas.cz/separaty/2016/E/barunik-0453168.pdf

  16. FORECASTING COSMOLOGICAL PARAMETER CONSTRAINTS FROM NEAR-FUTURE SPACE-BASED GALAXY SURVEYS

    International Nuclear Information System (INIS)

    Pavlov, Anatoly; Ratra, Bharat; Samushia, Lado

    2012-01-01

    The next generation of space-based galaxy surveys is expected to measure the growth rate of structure to a level of about one percent over a range of redshifts. The rate of growth of structure as a function of redshift depends on the behavior of dark energy and so can be used to constrain parameters of dark energy models. In this work, we investigate how well these future data will be able to constrain the time dependence of the dark energy density. We consider parameterizations of the dark energy equation of state, such as XCDM and ωCDM, as well as a consistent physical model of time-evolving scalar field dark energy, φCDM. We show that if the standard, specially flat cosmological model is taken as a fiducial model of the universe, these near-future measurements of structure growth will be able to constrain the time dependence of scalar field dark energy density to a precision of about 10%, which is almost an order of magnitude better than what can be achieved from a compilation of currently available data sets.

  17. Forecast Informed Reservoir Operations: Bringing Science and Decision-Makers Together to Explore Use of Hydrometeorological Forecasts to Support Future Reservoir Operations

    Science.gov (United States)

    Ralph, F. M.; Jasperse, J.

    2017-12-01

    Forecast Informed Reservoir Operations (FIRO) is a proposed strategy that is exploring inorporation of improved hydrometeorological forecasts of land-falling atmospheric rivers on the U.S. West Coast into reservoir operations. The first testbed for this strategy is Lake Mendocino, which is located in the East Fork of the 1485 mi2 Russian River Watershed in northern California. This project is guided by the Lake Mendocino FIRO Steering Committee (SC). The SC is an ad hoc committee that consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current or improved technology and scientific understanding can be utilized to improve water supply reliability, enhance flood mitigation and support recovery of listed salmon for the Russian River of northern California. In 2015, the SC created a detailed work plan, which included a Preliminary Viability Assessment, which has now been completed. The SC developed a vision that operational efficiency would be improved by using forecasts to inform decisions about releasing or storing water. FIRO would use available reservoir storage in an efficient manner by (1) better forecasting inflow (or lack of inflow) with enhanced technology, and (2) adapting operation in real time to meet the need for storage, rather than making storage available just in case it is needed. The envisioned FIRO strategy has the potential to simultaneously improve water supply reliability, flood protection, and ecosystem outcomes through a more efficient use of existing infrastructure while requiring minimal capital improvements in the physical structure of the dam. This presentation will provide an overview of the creation of the FIRO SC and how it operates, and describes the lessons learned through this partnership. Results in the FIRO Preliminary Viability Assessment will be summarized and next steps described.

  18. Using ecological forecasting of future vegetation transition and fire frequency change in the Sierra Nevada to assess fire management strategies

    Science.gov (United States)

    Thorne, J. H.; Schwartz, M. W.; Holguin, A. J.; Moritz, M.; Batllori, E.; Folger, K.; Nydick, K.

    2013-12-01

    Ecological systems may respond in complex manners as climate change progresses. Among the responses, site-level climate conditions may cause a shift in vegetation due to the physiological tolerances of plant species, and the fire return interval may change. Natural resource managers challenged with maintaining ecosystem health need a way to forecast how these processes may affect every location, in order to determine appropriate management actions and prioritize locations for interventions. We integrated climate change-driven vegetation type transitions with projected change in fire frequency for 45,203 km2 of the southern Sierra Nevada, California, containing over 10 land management agencies as well as private lands. This Magnitude of Change (MOC) approach involves classing vegetation types in current time according to their climate envelopes, and identifying which sites will in the future have climates beyond what that vegetation currently occurs in. Independently, fire models are used to determine the change in fire frequency for each site. We examined 82 vegetation types with >50 grid cell occurrences. We found iconic resources such as the giant sequoia, lower slope oak woodlands, and high elevation conifer forests are projected as highly vulnerable by models that project a warmer drier future, but not as much by models that project a warmer future that is not drier than current conditions. Further, there were strongly divergent vulnerabilities of these forest types across land ownership (National Parks versus US Forest Service lands), and by GCM. For example, of 50 giant sequoia (Sequoiadendron giganteum) groves and complexes, all but 3 (on Sierra National Forest) were in the 2 highest levels of risk of climate and fire under the GFDL A2 projection, while 15 groves with low-to-moderate risk were found on both the National Parks and National Forests 18 in the 2 under PCM A2. Landscape projections of potential MOC suggest that the region is likely to experience

  19. Future forecast for life-cycle greenhouse gas emissions of LNG and city gas 13A

    International Nuclear Information System (INIS)

    Okamura, Tomohito; Furukawa, Michinobu; Ishitani, Hisashi

    2007-01-01

    The objective of this paper is to analyze the most up-to-date data available on total greenhouse-gas emissions of a LNG fuel supply chain and life-cycle of city gas 13A based on surveys of the LNG projects delivering to Japan, which should provide useful basic-data for conducting life-cycle analyses of other product systems as well as future alternative energy systems, because of highly reliable data qualified in terms of its source and representativeness. In addition, the life-cycle greenhouse-gas emissions of LNG and city-gas 13A in 2010 were also predicted, taking into account not only the improvement of technologies, but also the change of composition of LNG projects. As a result of this analysis, the total amount of greenhouse-gas emissions of the whole city-gas 13A chain at present was calculated to be 61.91 g-CO 2 /MJ, and the life-cycle greenhouse-gas emissions of LNG and city-gas 13A in 2010 could be expected to decrease by about 1.1% of the current emissions

  20. Future sustainability forecasting by exchange markets: basic theory and an application.

    Science.gov (United States)

    Malyshkina, Nataliya; Niemeier, Deb

    2010-12-01

    Setting sustainability targets and evaluating systems progress are of great importance nowadays due to threats to the human society, to economic development and to ecosystems, posed by unsustainable human activities. This research establishes a probabilistic theoretical approach based on market expectations reflected in prices of publicly traded securities to estimate the time horizon until the appearance of new technologies related to replacement of nonrenewable resources, for example, crude oil and oil products. To assess time T when technological innovations are likely to appear, we apply advanced pricing equations, based on a stochastic discount factor to those traded securities whose future cash flows critically depend on appearance of such innovations. In a simple approximation of the proposed approach applied to replacement of crude oil and oil products, we obtain T ≈ (P(0)(oil)/C(0))·ln (Δ·P(0)(oil)/P(0)(alt)), where P(0)(oil) and P(0)(alt) are the current aggregate market capitalizations of oil and alternative-energy companies, C(0) is the annual aggregate dividends that oil companies pay to their shareholders at the present, and Δ is the fraction of the oil (oil products) replaced at time T. This formula gives T ≈ 131 years for replacement of gasoline and diesel. The proposed market-expectations approach may allow policymakers to effectively develop policies and plan for long-term changes.

  1. Past speculations of future health technologies: a description of technologies predicted in 15 forecasting studies published between 1986 and 2010.

    Science.gov (United States)

    Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

    2017-07-31

    To describe and classify health technologies predicted in forecasting studies. A portrait describing health technologies predicted in 15 forecasting studies published between 1986 and 2010 that were identified in a previous systematic review. Health technologies are classified according to their type, purpose and clinical use; relating these to the original purpose and timing of the forecasting studies. All health-related technologies predicted in 15 forecasting studies identified in a previously published systematic review. Outcomes related to (1) each forecasting study including country, year, intention and forecasting methods used and (2) the predicted technologies including technology type, purpose, targeted clinical area and forecast timeframe. Of the 896 identified health-related technologies, 685 (76.5%) were health technologies with an explicit or implied health application and included in our study. Of these, 19.1% were diagnostic or imaging tests, 14.3% devices or biomaterials, 12.6% information technology systems, eHealth or mHealth and 12% drugs. The majority of the technologies were intended to treat or manage disease (38.1%) or diagnose or monitor disease (26.1%). The most frequent targeted clinical areas were infectious diseases followed by cancer, circulatory and nervous system disorders. The most frequent technology types were for: infectious diseases-prophylactic vaccines (45.8%), cancer-drugs (40%), circulatory disease-devices and biomaterials (26.3%), and diseases of the nervous system-equally devices and biomaterials (25%) and regenerative medicine (25%). The mean timeframe for forecasting was 11.6 years (range 0-33 years, median=10, SD=6.6). The forecasting timeframe significantly differed by technology type (p=0.002), the intent of the forecasting group (p<0.001) and the methods used (p<001). While description and classification of predicted health-related technologies is crucial in preparing healthcare systems for adopting new innovations

  2. EnerFuture Energy Scenarios to 2035 'Understanding our Energy Future'. Key graphs and analysis, Enerdata - Global Energy Forecasting - February 2014

    International Nuclear Information System (INIS)

    2014-01-01

    The EnerFuture service provides projections to 2035 of energy supply and demand across the world, powered by the POLES model, to help you with what to expect in the energy industry in the mid-term. Our energy forecasting team have developed three key energy scenarios (Balance, Emergence and Renaissance) to illustrate possible futures. Balance scenario: Balance provides an outlook of the energy system up to 2035 based on current policies and trends. Sustained growth of China and other emerging countries is a powerful driver of global energy demand, but confirmed energy policy commitments in several regions play a key role in controlling the pace of growth. However, non-coordinated policies result in soaring CO_2 emissions across the world and energy prices rise. Emergence scenario: This scenario explores the implications of more stringent climate policies, with more ambitious efforts on energy efficiency, initiatives to phase out fossil fuel subsidies and a real emergence of renewable technologies. Europe goes beyond its -20% targets by 2020, and the OECD and emerging countries meet their Copenhagen objectives. Following this, a new green deal is launched to reduce world emissions by a factor of 2 by 2050. Renaissance scenario: With strong efforts in the exploitation and production of unconventional oil and gas resources, the world encounters a fossil fuels renaissance with the appearance of new key actors and ultimately new geopolitical configurations changing the energy independence of several countries. For climate efforts, this new paradigm leads to progressively weaker policies. Further analysis and key findings are available here: - Increasing economic activity and wealth drives energy consumption, in a balance between energy prices and innovation; - As Non-OECD exceeds OECD oil demand, massive financial flows underlie the shifts in global oil trade; - Optimistic resource assumptions and moderate production costs would lead to an oil production Renaissance

  3. Future healthy life expectancy among older adults in the US: a forecast based on cohort smoking and obesity history.

    Science.gov (United States)

    Cao, Bochen

    2016-01-01

    In the past three decades, the elderly population in the United States experienced increase in life expectancy (LE) and disability-free life expectancy (LE(ND)), but decrease in life expectancy with disability (LE(D)). Smoking and obesity are two major risk factors that had negative impacts on these trends. While smoking prevalence continues to decline in recent decades, obesity prevalence has been growing and is currently at a high level. This study aims to forecast the healthy life expectancy for older adults aged 55 to 85 in the US from 2011 to 2040, in relation to their smoking and obesity history. First, population-level mortality data from the Human Mortality Database (HMD) and individual-level disability data from the US National Health Interview Survey (NHIS) were used to estimate the transition rates between different health states from 1982 to 2010, using a multi-state life table (MSLT) model. Second, the estimated transition rates were fitted and projected up to 2040, using a modified Lee-Carter model that incorporates cohort smoking and obesity history from NHIS. Mortality and morbidity for both sexes will continue to decline in the next decades. Relative to 2010, men are expected to have 3.2 years gain in LE(ND) and 0.8 years loss in LE(D). For women, there will be 1.8 years gain in LE(ND) and 0.8 years loss in LE(D). By 2040, men and women are expected to spend respectively 80 % and 75 % of their remaining life expectancy between 55 and 85 disability-free. Smoking and obesity have independent negative impacts on both the survival and disability of the US older population in the coming decades, and are responsible for the present and future gender disparity in mortality and morbidity. Overall, the US older population is expected to enjoy sustained health improvements and compression of disability, largely due to decline in smoking.

  4. ECONOMIC FORECASTS BASED ON ECONOMETRIC MODELS USING EViews 5

    Directory of Open Access Journals (Sweden)

    Cornelia TomescuDumitrescu,

    2009-05-01

    Full Text Available The forecast of evolution of economic phenomena represent on the most the final objective of econometrics. It withal represent a real attempt of validity elaborate model. Unlike the forecasts based on the study of temporal series which have an recognizable inertial character the forecasts generated by econometric model with simultaneous equations are after to contour the future of ones of important economic variables toward the direct and indirect influences bring the bear on their about exogenous variables. For the relief of the calculus who the realization of the forecasts based on the econometric models its suppose is indicate the use of the specialized informatics programs. One of this is the EViews which is applied because it reduces significant the time who is destined of the econometric analysis and it assure a high accuracy of calculus and of the interpretation of results.

  5. High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

    Science.gov (United States)

    Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

    2017-12-01

    For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

  6. Analysis and evaluation of forecasting methods and tools to predict future demand for secondary chemical-biological configuration items

    OpenAIRE

    Ritchey, Chris D.

    2013-01-01

    Approved for public release; distribution is unlimited As the Engineering Support Activity (ESA) for numerous consumable Chemical Biological items managed by the Defense Logistics Agency (DLA), Edgewood Chemical Biological Center (ECBC) must be able to complete reviews of all procurement packages within 15 calendar days. With such little lead time, it would be very beneficial if ECBC had the ability to forecast when DLA procurement actions will occur. This thesis presents an evaluation of ...

  7. Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future

    Science.gov (United States)

    Homer, Collin G.; Xian, George Z.; Aldridge, Cameron L.; Meyer, Debra K.; Loveland, Thomas R.; O'Donnell, Michael S.

    2015-01-01

    Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus

  8. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  9. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  10. Evaluating long term forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Lady, George M. [Department of Economics, College of Liberal Arts, Temple University, Philadelphia, PA 19122 (United States)

    2010-03-15

    The U.S. Department of Energy's Energy Information Administration (EIA), and its predecessor organizations, has published projections of U.S. energy production, consumption, distribution and prices annually for over 30 years. A natural issue to raise in evaluating the projections is an assessment of their accuracy compared to eventual outcomes. A related issue is the determination of the sources of 'error' in the projections that are due to differences between the actual versus realized values of the associated assumptions. One way to do this would be to run the computer-based model from which the projections are derived at the time the projected values are realized, using actual rather than assumed values for model assumptions; and, compare these results to the original projections. For long term forecasts, this approach would require that the model's software and hardware configuration be archived and available for many years, possibly decades, into the future. Such archival creates many practical problems; and, in general, it is not being done. This paper reports on an alternative approach for evaluating the projections. In the alternative approach, the model is run many times for cases in which important assumptions are changed individually and in combinations. A database is assembled from the solutions and a regression analysis is conducted for each important projected variable with the associated assumptions chosen as exogenous variables. When actual data are eventually available, the regression results are then used to estimate the sources of the differences in the projections of the endogenous variables compared to their eventual outcomes. The results presented here are for residential and commercial sector natural gas and electricity consumption. (author)

  11. Forecasting the Future Food Service World of Work. Final Report. Volume II. Centralized Food Service Systems. Service Management Reports.

    Science.gov (United States)

    Powers, Thomas F., Ed.; Swinton, John R., Ed.

    Volume II of a three-volume study on the future of the food service industry considers the effects that centralized food production will have on the future of food production systems. Based on information from the Fair Acres Project and the Michigan State University Vegetable Processing Center, the authors describe the operations of a centralized…

  12. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  13. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  14. Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression

    OpenAIRE

    Barunik, Jozef; Barunikova, Michaela

    2015-01-01

    This paper revisits the fractional co-integrating relationship between ex-ante implied volatility and ex-post realized volatility. Previous studies on stock index options have found biases and inefficiencies in implied volatility as a forecast of future volatility. It is argued that the concept of corridor implied volatility (CIV) should be used instead of the popular model-free option-implied volatility (MFIV) when assessing the relation as the latter may introduce bias to the estimation. In...

  15. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  16. TRAINING FUTURE TEACHERS OF COMPUTER SCIENCE FOR WORKING OUT TECHNOLOGICAL CARDS OF LESSONS IN THE CONDITIONS OF REALIZATION OF THE FEDERAL STATE EDUCATIONAL STANDARD FOR GENERAL EDUCATION

    Directory of Open Access Journals (Sweden)

    Екатерина Николаевна Кувшинова

    2017-12-01

    Full Text Available This article is devoted to a problem of readiness of future teachers of informatics for development of flow charts of the lessons displaying the main requirements of Federal state educational standards of the main general education (FGOS of Ltd company to planning and the organization of educational process taking into account system and activity approach in training. Content of system and activity approach in training, the universal educational actions (UEA reveals. Main units of the flow chart of a lesson of informatics are considered. The substantial block of the flow chart of a lesson of informatics determined by a training material which provides achievement of the planned subject results of training, and also forming and development of UUD, all-educational skills, ICT competences, competences of educational and research and project activities is stated.Subject results of training to which the abilities specific to a subject, types of activity on receipt of new knowledge within a subject, to its transformation and application in educational, educational and project and social and project situations, forming of scientific type of thinking, scientific ideas of key theories, types and types of the relations, ownership of scientific terminology, key concepts, methods and acceptances belong [10] are analyzed.Step-by-step training of future teachers of informatics for development of flow charts of lessons is discussed.

  17. BUSINESS DEPARTMENTS OF STATE UNIVERSITIES IN TURKEY: LAST FIVE YEARS, CURRENT SITUATION AND FORECASTING FOR THEIR FUTURE

    OpenAIRE

    Paylar, Onder Ziya; Oturakci, Murat

    2015-01-01

    In recent years, when increasing numbers of universities all across the country and accordingly increasing the number of university faculties and departments and rising unemployment rate considered together, a threatening phase will arise about future of some departments in higher education. This future concern has become a common issue intensely in business departments.  In the first part of the study, preference percentages, placements of success, minimum and maximum scores and filling rate...

  18. Forecasting Covariance Matrices: A Mixed Frequency Approach

    DEFF Research Database (Denmark)

    Halbleib, Roxana; Voev, Valeri

    This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...

  19. Towards a low-carbon future in China's building sector-A review of energy and climate models forecast

    International Nuclear Information System (INIS)

    Li Jun

    2008-01-01

    This article investigates the potentials of energy saving and greenhouse gases emission mitigation offered by implementation of building energy efficiency policies in China. An overview of existing literature regarding long-term energy-demand and carbon dioxide (CO 2 ) emission forecast scenarios is presented. Energy consumption in buildings could be reduced by 100-300 million tons of oil equivalent (mtoe) in 2030 compared with the business-as-usual (BAU) scenario, which means that 600-700 million metric tons of CO 2 emissions could be saved by implementing appropriate energy policies within an adapted institutional framework. The main energy-saving potentials in buildings can be achieved by improving a building's thermal performance and district heating system efficiency. The analyses also reveal that the energy interchange systems are effective especially in the early stage of penetration. Our analysis on the reviewed models suggests that more ambitious efficiency improvement policies in both supply- and demand-side as well as the carbon price should be taken into account in the policy scenarios to address drastic reduction of CO 2 emission in the building sector to ensure climate security over the next decades

  20. Forecasts, scenarios, visions, backcasts and roadmaps to the hydrogen economy: A review of the hydrogen futures literature

    International Nuclear Information System (INIS)

    McDowall, William; Eames, Malcolm

    2006-01-01

    Scenarios, roadmaps and similar foresight methods are used to cope with uncertainty in areas with long planning horizons, such as energy policy, and research into the future of hydrogen energy is no exception. Such studies can play an important role in the development of shared visions of the future: creating powerful expectations of the potential of emerging technologies and mobilising resources necessary for their realisation. This paper reviews the hydrogen futures literature, using a six-fold typology to map the state of the art of scenario construction. The paper then explores the expectations embodied in the literature, through the 'answers' it provides to questions about the future of hydrogen. What are the drivers, barriers and challenges facing the development of a hydrogen economy? What are the key technological building blocks required? In what kinds of futures does hydrogen become important? What does a hydrogen economy look like, how and when does it evolve, and what does it achieve? The literature describes a diverse range of possible futures, from decentralised systems based upon small-scale renewables, through to centralised systems reliant on nuclear energy or carbon-sequestration. There is a broad consensus that the hydrogen economy emerges only slowly, if at all, under 'Business as Usual' scenarios. Rapid transitions to hydrogen occur only under conditions of strong governmental support combined with, or as a result of, major 'discontinuities' such as shifts in society's environmental values, 'game changing' technological breakthroughs, or rapid increases in the oil price or speed and intensity of climate change

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

    Science.gov (United States)

    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.

  2. Adaptive Weather Forecasting using Local Meteorological Information

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2005-01-01

    In general, meteorological parameters such as temperature, rain and global radiation are important for agricultural systems. Anticipating on future conditions is most often needed in these systems. Weather forecasts then become of substantial importance. As weather forecasts are subject to

  3. Urban runoff forecasting with ensemble weather predictions

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

  4. Using high-resolution future climate scenarios to forecast Bromus tectorum invasion in Rocky Mountain National Park.

    Science.gov (United States)

    West, Amanda M; Kumar, Sunil; Wakie, Tewodros; Brown, Cynthia S; Stohlgren, Thomas J; Laituri, Melinda; Bromberg, Jim

    2015-01-01

    National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass), which is found in Rocky Mountain National Park (hereafter, the Park), Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211), current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2) and at a fine spatial resolution (90 m) is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum.

  5. Using High-Resolution Future Climate Scenarios to Forecast Bromus tectorum Invasion in Rocky Mountain National Park

    Science.gov (United States)

    West, Amanda M.; Kumar, Sunil; Wakie, Tewodros; Brown, Cynthia S.; Stohlgren, Thomas J.; Laituri, Melinda; Bromberg, Jim

    2015-01-01

    National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass), which is found in Rocky Mountain National Park (hereafter, the Park), Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211), current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2) and at a fine spatial resolution (90 m) is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum. PMID:25695255

  6. Using high-resolution future climate scenarios to forecast Bromus tectorum invasion in Rocky Mountain National Park.

    Directory of Open Access Journals (Sweden)

    Amanda M West

    Full Text Available National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass, which is found in Rocky Mountain National Park (hereafter, the Park, Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211, current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2 and at a fine spatial resolution (90 m is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum.

  7. Realizability: a historical essay

    NARCIS (Netherlands)

    Oosten, J. van

    2000-01-01

    The purpose of this short paper is to sketch the development of a few basic topics in the history of Realizability The number of topics is quite limited and reects very much my own personal taste biases and prejudices Realizability has over the past years developed into a subject of such dimensions

  8. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  9. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  10. Energy forecasts, perspectives and methods

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J E; Mogren, A

    1984-01-01

    The authors have analyzed different methods for long term energy prognoses, in particular energy consumption forecasts. Energy supply and price prognoses are also treated, but in a less detailed manner. After defining and discussing the various methods/models used in forecasts, a generalized discussion of the influence on the prognoses from the perspectives (background factors, world view, norms, ideology) of the prognosis makers is given. Some basic formal demands that should be asked from any rational forecast are formulated and discussed. The authors conclude that different forecasting methodologies are supplementing each other. There is no best method, forecasts should be accepted as views of the future from differing perspectives. The primary prognostic problem is to show the possible futures, selecting the wanted future is a question of political process.

  11. Realized Cost Savings 2016

    Data.gov (United States)

    Department of Veterans Affairs — This dataset is provided as a requirement of OMB’s Integrated Data Collection (IDC) and links to VA’s Realized Cost Savings and Avoidances data in JSON format. Cost...

  12. Design and realization

    International Nuclear Information System (INIS)

    1986-01-01

    Most typical papers on the Ganil construction have been gathered in this book to somehow notice the success of its realization. Papers concern the accelerator and beam line, excluding experimental areas

  13. Using population viability analysis, genomics, and habitat suitability to forecast future population patterns of Little Owl Athene noctua across Europe.

    Science.gov (United States)

    Andersen, Line Holm; Sunde, Peter; Pellegrino, Irene; Loeschcke, Volker; Pertoldi, Cino

    2017-12-01

    The agricultural scene has changed over the past decades, resulting in a declining population trend in many species. It is therefore important to determine the factors that the individual species depend on in order to understand their decline. The landscape changes have also resulted in habitat fragmentation, turning once continuous populations into metapopulations. It is thus increasingly important to estimate both the number of individuals it takes to create a genetically viable population and the population trend. Here, population viability analysis and habitat suitability modeling were used to estimate population viability and future prospects across Europe of the Little Owl Athene noctua , a widespread species associated with agricultural landscapes. The results show a high risk of population declines over the coming 100 years, especially toward the north of Europe, whereas populations toward the southeastern part of Europe have a greater probability of persistence. In order to be considered genetically viable, individual populations must count 1,000-30,000 individuals. As Little Owl populations of several countries count <30,000, and many isolated populations in northern Europe count <1,000 individuals, management actions resulting in exchange of individuals between populations or even countries are probably necessary to prevent losing <1% genetic diversity over a 100-year period. At a continental scale, a habitat suitability analysis suggested Little Owl to be affected positively by increasing temperatures and urban areas, whereas an increased tree cover, an increasing annual rainfall, grassland, and sparsely vegetated areas affect the presence of the owl negatively. However, the low predictive power of the habitat suitability model suggests that habitat suitability might be better explained at a smaller scale.

  14. The metallurgy dross of the past: analogues to forecast the behaviour of present wastes in the course of their future aging

    International Nuclear Information System (INIS)

    Anon.

    2000-01-01

    The production of wastes is continuously increasing. Since they are a potential source of pollution, they must be stabilised, generally by vitrification. In order to know the long term behavior of these new products, several ways have been investigated, and among them, the study of analogues, either natural or resulting from the human activity. In this paper, are studied metallurgy drosses of the past which are regularly found during archaeological excavations; their ages range from 100 to 4000 years. The mineralogical, macroscopical and chemical characterisation of these materials and of some vitrified present wastes (from municipal wastes incineration plants and nuclear wastes), showed a great analogy of chemical and mineralogical composition between these present wastes and these materials of the past. Both are generally made of similar mineral phases (spinels, silicates, sulfides, metallic alloys), surrounded by a glassy matrix, and containing in many cases high percentages of contaminants. This matrix being the main cohesion factor of these materials, which brings them to weathering resistance. This led to study the glass weathering mechanisms. The results have shown a continuous weathering in three successive steps: the departure of large glass cations (Ca, Mg), the dissolution of the glassy structure, the precipitation of new phases. The average speeds range from 20 to 180 mm/1000 years, showing a good resistance of these materials in a natural environment. Future investigations should concern the study of a global site including its surroundings, in order to know the behaviour of contaminants after weathering during a period of several hundred years. These metallurgical sites of the past may thus be considered as analogues to forecast the future behaviour of abandoned industrial sites. (authors)

  15. The Latest Forecast.

    Science.gov (United States)

    Laurence, David

    2002-01-01

    Discusses the "latest forecast" for the future of English departments. Addresses departmental and institutional staffing practices, employment opportunities for PhDs, the acceleration of change in the institution, and the general state of the study and teaching of English. (RS)

  16. Long-term forecast 2010; Laangsiktsprognos 2010

    Energy Technology Data Exchange (ETDEWEB)

    2011-07-01

    This report presents the energy forecast to the year 2030, and two different sensitivity scenarios. The forecast is based on existing instruments, which means that the report's findings should not be considered a proper forecast of the future energy use, but as an impact assessment of existing policy instruments, given different circumstances such as economic growth and fuel prices

  17. Bayesian flood forecasting methods: A review

    Science.gov (United States)

    Han, Shasha; Coulibaly, Paulin

    2017-08-01

    Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been

  18. The role of forecasts in monetary policy

    OpenAIRE

    Jeffery D. Amato; Thomas Laubach

    2000-01-01

    Forecasts of future economic developments play an important role for the monetary policy decisions of central banks. For example, forecasts of goal variables can help central banks achieve their goals and make them more accountable to the public. There are two primary explanations for the benefits of forecasts. The first is that monetary policy affects goal variables such as inflation and output only with substantial lags. Policy actions should, therefore, be based on forecasts of goal variab...

  19. Realized kernels in practice

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger

    2009-01-01

    and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...

  20. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  1. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  2. Modelos de previsão de preços aplicados aos contratos futuros de boi gordo na BM&F Models of price forecasting applied to futures contracts of live cattle at the Brazilian Futures Market - BM&F

    Directory of Open Access Journals (Sweden)

    Aureliano Angel Bressan

    2002-01-01

    Full Text Available This paper studies the applicability of time series models as a decision tool of buy and sell orders of live cattle futures contracts in the Brazilian Futures Market (BM&F, on dates close to expiration. The models considered are: ARIMA, Neural Networks and Dynamic Linear Models - DLM (this in the classic and bayesian approach. Weekly data, of the spot and futures markets, from 1996 to 1999, are used to calculate the forecasts. The main purpose is to calculate the returns, in buy/sell orders of live cattle futures between 1998 and 1999, in order to show the potentials or limitations of each model. The results show positive returns in almost all contracts analyzed, indicating the potential of the models as a decision tool in operating with futures contracts close to expiration date, with distinction on the performance of the Classic DLM and ARIMA models, although some differences in forecasting accuracy.

  3. The Supply of Medical Radioisotopes. Medical Isotope Supply in the Future: Production Capacity and Demand. Forecast for the 99Mo/99mTc Market, 2015-2020

    International Nuclear Information System (INIS)

    Peykov, Pavel; Cameron, Ron

    2014-04-01

    This document presents a forecast of 99 Mo/ 99m Tc production capacity and demand in 2015-2020, when two major irradiators - the OSIRIS and NRU reactors in France and Canada - are expected to exit the global supply chain and new alternative technology projects may be commissioned. The forecast does not attempt to predict shortages, but identify periods when there is an increased risk of disrupted supply, to inform policy makers and other stakeholders. (authors)

  4. Forecast for the Future: Telecommunications.

    Science.gov (United States)

    Sekaquaptewa, Sam; Yawakie, Madonna; Scheer, Roger; Yawakie, Mel

    1999-01-01

    Four telecommunications experts comment on changes in the industry and how these changes may result in career opportunities for American Indians. American Indian reservations have limited access to telecommunications and information technology and would benefit from the advocacy of Native professionals. (CDS)

  5. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  6. Forecasting interest rates with shifting endpoints

    DEFF Research Database (Denmark)

    Van Dijk, Dick; Koopman, Siem Jan; Wel, Michel van der

    2014-01-01

    We consider forecasting the term structure of interest rates with the assumption that factors driving the yield curve are stationary around a slowly time-varying mean or ‘shifting endpoint’. The shifting endpoints are captured using either (i) time series methods (exponential smoothing) or (ii......) long-range survey forecasts of either interest rates or inflation and output growth, or (iii) exponentially smoothed realizations of these macro variables. Allowing for shifting endpoints in yield curve factors provides substantial and significant gains in out-of-sample predictive accuracy, relative...... to stationary and random walk benchmarks. Forecast improvements are largest for long-maturity interest rates and for long-horizon forecasts....

  7. Forecasting potential crises

    International Nuclear Information System (INIS)

    Neufeld, W.P.

    1984-01-01

    Recently, the Trend Analysis Program (TAP) of the American Council of Life Insurance commissioned the Futures Group of Glastonbury, Connecticut, to examine the potential for large-scale catastrophic events in the near future. TAP was specifically concerned with five potential crises: the warming of the earth's atmosphere, the water shortage, the collapse of the physical infrastructure, the global financial crisis, and the threat of nuclear war. We are often unprepared to take action; in these cases, we lose an advantage we might have otherwise had. This is the whole idea behind forecasting: to foresee possibilities and to project how we can respond. If we are able to create forecasts against which we can test policy options and choices, we may have the luxury of adopting policies ahead of events. Rather than simply fighting fires, we have the option of creating a future more to our choosing. Short descriptions of these five potential crises and, in some cases, possible solutions are presented

  8. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  9. Realizing the Witch

    OpenAIRE

    Baxstrom, Richard; Meyers, Todd

    2016-01-01

    Benjamin Christensen’s Häxan (The Witch, 1922) stands as a singular film within the history of cinema. Deftly weaving contemporary scientific analysis and powerfully staged historical scenes of satanic initiation, confession under torture, possession, and persecution, Häxan creatively blends spectacle and argument to provoke a humanist re-evaluation of witchcraft in European history as well as the contemporary treatment of female “hysterics” and the mentally ill. In Realizing the Witch, Baxst...

  10. Exploring heterogeneous market hypothesis using realized volatility

    Science.gov (United States)

    Chin, Wen Cheong; Isa, Zaidi; Mohd Nor, Abu Hassan Shaari

    2013-04-01

    This study investigates the heterogeneous market hypothesis using high frequency data. The cascaded heterogeneous trading activities with different time durations are modelled by the heterogeneous autoregressive framework. The empirical study indicated the presence of long memory behaviour and predictability elements in the financial time series which supported heterogeneous market hypothesis. Besides the common sum-of-square intraday realized volatility, we also advocated two power variation realized volatilities in forecast evaluation and risk measurement in order to overcome the possible abrupt jumps during the credit crisis. Finally, the empirical results are used in determining the market risk using the value-at-risk approach. The findings of this study have implications for informationally market efficiency analysis, portfolio strategies and risk managements.

  11. Realization theory for rational systems: Minimal rational realizations

    NARCIS (Netherlands)

    J. Nemcová (Jana); J.H. van Schuppen (Jan)

    2010-01-01

    htmlabstractThe study of realizations of response maps is a topic of control and system theory. Realization theory is used in system identification and control synthesis. A minimal rational realization of a given response map p is a rational realization of p such that the dimension of its state

  12. PREFACE: Nanospintronics design and realization

    Science.gov (United States)

    Akai, Hisazumi; Katayama-Yoshida, Hiroshi; Kasai, Hideaki

    2004-12-01

    This special issue of Journal of Physics: Condensed Matter contains selected papers from the 1st International Conference on Nanospintronics Design and Realization (ICNDR 2004), which was held in Kyoto, Japan, 24--28 May 2004. This conference was organized by the Nanospintronics Design and Realization project members: Hideaki Kasai, Osaka (Chair of the Conference) Hisazumi Akai, Osaka Hajime Asahi, Osaka Wilson Agerico Diño, Osaka Hiroshi Harima, Kyoto Tomoyuki Kakeshita, Osaka Junjiro Kanamori, Kyoto Hiroshi Katayama-Yoshida, Osaka Koichi Kusakabe, Osaka Hiroshi Nakanishi, Osaka (Secretary) Tamio Oguchi, Hiroshima Teruo Ono, Osaka Naoshi Suzuki, Osaka Hitoshi Tabata, Osaka under the auspices of the Japan Ministry of Education, Culture, Sports, Science and Technology (MEXT) Special Coordination Funds for Promoting Science and Technology, and the sponsorship of Osaka University and the International Institute for Advanced Studies (IIAS). The conference is intended to provide an international forum for experimental and theoretical researchers, in the rapidly developing field of nanospintronics. It aims to: provide an overview of our current understanding of the physics of spin transport in (magnetic) semiconductors and hybrid magnetic/semiconductor structures; provide a venue to present and discuss the latest developments in using spin-dependent phenomena in nano-(opto-) electronics and computing applications; provide a venue for discussion and assessment of other possible means of exploiting the spin-dependent phenomena in future nano-(opto-) electronic and computing applications; address current (and foreseeable future) problems, of fundamental and applied nature, in an effort to bridge the physics and technology gap between semiconducting and magnetic materials. All of these being geared towards bringing about the realization of a functioning nanospintronics. A total of 127 delegates from 15 countries took part in ICNDR 2004, which was comprised of 62 invited

  13. Extravehicular Activity Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2011-01-01

    The goal of NASA s current EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be to reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA hardware life and limited availability of the Extravehicular Mobility Units (EMUs) will eventually become a critical issue. The current EMU has successfully served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability will be needed and the current architectures and technologies under development offer significant improvements over the current flight systems. In addition to ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an

  14. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented.......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...

  15. Concurrency in product realization

    Science.gov (United States)

    Kelly, Michael J.

    1994-03-01

    Technology per se does not provide a competitive advantage. Timely exploitation of technology is what gives the competitive edge, and this demands a major shift in the product development process and management of the industrial enterprise. `Teaming to win' is more than a management theme; it is the disciplined engineering practice that is essential to success in today's global marketplace. Teaming supports the concurrent engineering practices required to integrate the activities of people responsible for product realization through achievement of shorter development cycles, lower costs, and defect-free products.

  16. Oscillators from nonlinear realizations

    Science.gov (United States)

    Kozyrev, N.; Krivonos, S.

    2018-02-01

    We construct the systems of the harmonic and Pais-Uhlenbeck oscillators, which are invariant with respect to arbitrary noncompact Lie algebras. The equations of motion of these systems can be obtained with the help of the formalism of nonlinear realizations. We prove that it is always possible to choose time and the fields within this formalism in such a way that the equations of motion become linear and, therefore, reduce to ones of ordinary harmonic and Pais-Uhlenbeck oscillators. The first-order actions, that produce these equations, can also be provided. As particular examples of this construction, we discuss the so(2, 3) and G 2(2) algebras.

  17. Forecasting military expenditure

    Directory of Open Access Journals (Sweden)

    Tobias Böhmelt

    2014-05-01

    Full Text Available To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

  18. Strategy of VHTR Realization

    International Nuclear Information System (INIS)

    Chang, Jonghwa

    2015-01-01

    High temperature gas cooled reactor has been developed since 1956. Fundamental idea of a gas cooled reactor is to achieve high temperature which is suitable for high efficiency application such as electricity generation. The core is composed of ceramics, graphite blocks which are mechanical stable up to very high temperature. Fuel is ceramics, TRISO ( tri-isotropic coated micro particle) whose dense coating layers work as small radioactivity containment. Coolant is inert gas, helium, which is stable chemically, neutronically, and thermal hydraulically. Several test reactors such as DRE, PB-1, FSV, AVR, THTR, HTTR, HTR-10 were built and demonstrated their safety. Large GA-HTR, RSA-PBMR projects are canceled and US-NGNP project is idling. Only Chinese HTR-PM demonstrator is under construction. HTGR has long history of development. For realization and market penetration, VHTR community should look at niche market such as carbon free energy supply to industry complex, electric power for small grid, carbon free hydrogen production, power source for space colony. Technology Readiness Level should be advanced to get proper investment from industry. For this, cooperation between international R and D institutions is required. Clearly divided role between universities, research institutions, and industries will reduce complication and shorten VHTR realization day

  19. Strategy of VHTR Realization

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Jonghwa [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    High temperature gas cooled reactor has been developed since 1956. Fundamental idea of a gas cooled reactor is to achieve high temperature which is suitable for high efficiency application such as electricity generation. The core is composed of ceramics, graphite blocks which are mechanical stable up to very high temperature. Fuel is ceramics, TRISO ( tri-isotropic coated micro particle) whose dense coating layers work as small radioactivity containment. Coolant is inert gas, helium, which is stable chemically, neutronically, and thermal hydraulically. Several test reactors such as DRE, PB-1, FSV, AVR, THTR, HTTR, HTR-10 were built and demonstrated their safety. Large GA-HTR, RSA-PBMR projects are canceled and US-NGNP project is idling. Only Chinese HTR-PM demonstrator is under construction. HTGR has long history of development. For realization and market penetration, VHTR community should look at niche market such as carbon free energy supply to industry complex, electric power for small grid, carbon free hydrogen production, power source for space colony. Technology Readiness Level should be advanced to get proper investment from industry. For this, cooperation between international R and D institutions is required. Clearly divided role between universities, research institutions, and industries will reduce complication and shorten VHTR realization day.

  20. Forecasts of forest conditions in regions of the United States under future scenarios: a technical document supporting the Forest Service 2012 RPA Assessment

    Science.gov (United States)

    David N. Wear; Robert Huggett; Ruhong Li; Benjamin Perryman; Shan Liu

    2013-01-01

    The 626 million acres of forests in the conterminous United States represent significant reserves of biodiversity and terrestrial carbon and provide substantial flows of highly valued ecosystem services, including timber products, watershed protection benefits, and recreation. This report describes forecasts of forest conditions for the conterminous United States in...

  1. Research on Interval Forecast For Metal Futures Market′s VaR Based on Bootstrap%基于Bootstrap的金属期货市场风险VaR区间预测

    Institute of Scientific and Technical Information of China (English)

    沈盟; 王璐

    2016-01-01

    金属期货市场风险VaR的准确测度对防范期货交易风险及保持市场健康平稳运行有重要作用.传统的VaR测度方法主要以点预测为主,无法反映预测近似值的精确程度及范围. 因此,提出了一种基于Bootstrap的金属期货市场风险VaR区间预测方法,同时引入LR检验区间预测的有效性,最后利用我国铜和铝期货市场数据进行了VaR风险的区间预测. 结果表明,新的VaR区间预测方法能克服点预测的不足,准确有效地描述VaR的估计风险,同时置信区间上下限可用于风险的预警及控制.%The accurate measurement on metal futures market′s VaR is important to prevent the futures′transaction risk and maintain the market healthy and stable operation.The traditional methods measuring VaR focus on point forecast which can't re-flect the accuracy of the predictive value.A new method to measure the interval forecast for metal futures market's VaR based on bootstrap is put forward.LR test is used to test the effectiveness of interval forecast.Finally,we empirical study the interval fore-cast of copper and aluminum futures market's VaR in China.The results show that the new method can overcome the lack of point forecast,while the upper and lower confidence interval can be used for early warning and control financial risks.

  2. Level Shifts in Volatility and the Implied-Realized Volatility Relation

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper; de Magistris, Paolo Santucci

    We propose a simple model in which realized stock market return volatility and implied volatility backed out of option prices are subject to common level shifts corresponding to movements between bull and bear markets. The model is estimated using the Kalman filter in a generalization to the mult......We propose a simple model in which realized stock market return volatility and implied volatility backed out of option prices are subject to common level shifts corresponding to movements between bull and bear markets. The model is estimated using the Kalman filter in a generalization...... to the multivariate case of the univariate level shift technique by Lu and Perron (2008). An application to the S&P500 index and a simulation experiment show that the recently documented empirical properties of strong persistence in volatility and forecastability of future realized volatility from current implied...... volatility, which have been interpreted as long memory (or fractional integration) in volatility and fractional cointegration between implied and realized volatility, are accounted for by occasional common level shifts....

  3. Future Savvy

    DEFF Research Database (Denmark)

    Gordon, Adam

    There's no shortage of predictions available to organizations looking to anticipate and profit from future events or trends. Apparently helpful forecasts are ubiquitous in everyday communications such as newspapers and business magazines, and in specialized sources such as government and think......-tank forecasts, consultant reports, and stock-market guides. These resources are crucial, but they are also of very mixed quality. How can decision-makers know which predictions to take seriously, which to be wary of, and which to throw out entirely? Future Savvy provides analytical filters to judging predictive...... systematic "forecast filtering" to reveal strengths and weakness in the predictions they face. Future Savvy empowers both business and policy/government decision-makers to use forecasts wisely and so improve their judgment in anticipating opportunities, avoiding threats, and managing uncertainty....

  4. Uncertain Climate Forecasts From Multimodel Ensembles: When to Use Them and When to Ignore Them

    OpenAIRE

    Jewson, Stephen; Rowlands, Dan

    2010-01-01

    Uncertainty around multimodel ensemble forecasts of changes in future climate reduces the accuracy of those forecasts. For very uncertain forecasts this effect may mean that the forecasts should not be used. We investigate the use of the well-known Bayesian Information Criterion (BIC) to make the decision as to whether a forecast should be used or ignored.

  5. Simulation of regional day-ahead PV power forecast scenarios

    DEFF Research Database (Denmark)

    Nuno, Edgar; Koivisto, Matti Juhani; Cutululis, Nicolaos Antonio

    2017-01-01

    Uncertainty associated with Photovoltaic (PV) generation can have a significant impact on real-time planning and operation of power systems. This obstacle is commonly handled using multiple forecast realizations, obtained using for example forecast ensembles and/or probabilistic forecasts, often...... at the expense of a high computational burden. Alternatively, some power system applications may require realistic forecasts rather than actual estimates; able to capture the uncertainty of weatherdriven generation. To this end, we propose a novel methodology to generate day-ahead forecast scenarios of regional...... PV production matching the spatio-temporal characteristics while preserving the statistical properties of actual records....

  6. Forecasting global atmospheric CO2

    International Nuclear Information System (INIS)

    Agusti-Panareda, A.; Massart, S.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Engelen, R.; Jones, L.; Peuch, V.H.; Chevallier, F.; Ciais, P.; Paris, J.D.; Sherlock, V.

    2014-01-01

    A new global atmospheric carbon dioxide (CO 2 ) real-time forecast is now available as part of the preoperational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO 2 forecasting system is that the land surface, including vegetation CO 2 fluxes, is modelled online within the IFS. Other CO 2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO 2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO 2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO 2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO 2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO 2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO 2 fluxes also lead to accumulating errors in the CO 2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO 2 fluxes compared to total optimized fluxes and the atmospheric CO 2 compared to observations. The largest biases in the atmospheric CO 2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO 2 analyses based on the assimilation of CO 2 products retrieved from satellite

  7. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  8. Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility

    DEFF Research Database (Denmark)

    Hansen, Peter Reinhard; Huang, Zhuo (Albert); Shek, Howard Howan

    GARCH models have been successful in modeling financial returns. Still, much is to be gained by incorporating a realized measure of volatility in these models. In this paper we introduce a new framework for the joint modeling of returns and realized measures of volatility. The Realized GARCH...... framework nests most GARCH models as special cases and is, in many ways, a natural extension of standard GARCH models. We pay special attention to linear and log-linear Realized GARCH specifications. This class of models has several attractive features. It retains the simplicity and tractability...... to latent volatility. This equation facilitates a simple modeling of the dependence between returns and future volatility that is commonly referred to as the leverage effect. An empirical application with DJIA stocks and an exchange traded index fund shows that a simple Realized GARCH structure leads...

  9. Short-term natural gas consumption forecasting

    International Nuclear Information System (INIS)

    Potocnik, P.; Govekar, E.; Grabec, I.

    2007-01-01

    Energy forecasting requirements for Slovenia's natural gas market were investigated along with the cycles of natural gas consumption. This paper presented a short-term natural gas forecasting approach where the daily, weekly and yearly gas consumption were analyzed and the information obtained was incorporated into the forecasting model for hourly forecasting for the next day. The natural gas market depends on forecasting in order to optimize the leasing of storage capacities. As such, natural gas distribution companies have an economic incentive to accurately forecast their future gas consumption. The authors proposed a forecasting model with the following properties: two submodels for the winter and summer seasons; input variables including past consumption data, weather data, weather forecasts and basic cycle indexes; and, a hierarchical forecasting structure in which a daily model was used as the basis, with the hourly forecast obtained by modeling the relative daily profile. This proposed method was illustrated by a forecasting example for Slovenia's natural gas market. 11 refs., 11 figs

  10. Open-source Software for Demand Forecasting of Clinical Laboratory Test Volumes Using Time-series Analysis.

    Science.gov (United States)

    Mohammed, Emad A; Naugler, Christopher

    2017-01-01

    Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. This tool will allow anyone with historic test volume data to model future demand.

  11. Open-source software for demand forecasting of clinical laboratory test volumes using time-series analysis

    Directory of Open Access Journals (Sweden)

    Emad A Mohammed

    2017-01-01

    Full Text Available Background: Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. Method: In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. Results: This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. Conclusion: This tool will allow anyone with historic test volume data to model future demand.

  12. Fashion Forward: Forecasting Visual Style in Fashion

    OpenAIRE

    Al-Halah, Ziad; Stiefelhagen, Rainer; Grauman, Kristen

    2017-01-01

    What is the future of fashion? Tackling this question from a data-driven vision perspective, we propose to forecast visual style trends before they occur. We introduce the first approach to predict the future popularity of styles discovered from fashion images in an unsupervised manner. Using these styles as a basis, we train a forecasting model to represent their trends over time. The resulting model can hypothesize new mixtures of styles that will become popular in the future, discover styl...

  13. Futures

    DEFF Research Database (Denmark)

    Pedersen, Michael Haldrup

    2017-01-01

    Currently both design thinking and critical social science experience an increased interest in speculating in alternative future scenarios. This interest is not least related to the challenges issues of global sustainability present for politics, ethics and design. This paper explores the potenti......Currently both design thinking and critical social science experience an increased interest in speculating in alternative future scenarios. This interest is not least related to the challenges issues of global sustainability present for politics, ethics and design. This paper explores...... the potentials of speculative thinking in relation to design and social and cultural studies, arguing that both offer valuable insights for creating a speculative space for new emergent criticalities challenging current assumptions of the relations between power and design. It does so by tracing out discussions...... of ‘futurity’ and ‘futuring’ in design as well as social and cultural studies. Firstly, by discussing futurist and speculative approaches in design thinking; secondly by engaging with ideas of scenario thinking and utopianism in current social and cultural studies; and thirdly by showing how the articulation...

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  10. kjac Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kphx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. Optimal operation and forecasting policy for pump storage plants in day-ahead markets

    International Nuclear Information System (INIS)

    Muche, Thomas

    2014-01-01

    Highlights: • We investigate unit commitment deploying stochastic and deterministic approaches. • We consider day-ahead markets, its forecast and weekly price based unit commitment. • Stochastic and deterministic unit commitment are identical for the first planning day. • Unit commitment and bidding policy can be based on the deterministic approach. • Robust forecasting models should be estimated based on the whole planning horizon. - Abstract: Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation

  13. Realizing Controllable Quantum States

    Science.gov (United States)

    Takayanagi, Hideaki; Nitta, Junsaku

    -- 4. Mesoscopic superconductivity with unconventional superconductor or ferromagnet. Ultraefficient microrefrigerators realized with ferromagnet-superconductor junctions / F. Giazotto et al. Anomalous charge transport in triplet superconductor junctions by the synergy effect of the proximity effect and the mid gap Andreev resonant states / Y. Tanaka and S. Kashiwaya. Paramagnetic and glass states in superconductive YBa[symbol]Cu[symbol]O[symbol] ceramics of sub-micron scale grains / H. Deguchi et al. Quantum properties of single-domain triplet superconductors / A. M. Gulian and K. S. Wood. A numerical study of Josephson current in p wave superconducting junctions / Y. Asano et al. Tilted bi-crystal sapphire substrates improve properties of grain boundary YBa[symbol]Cu[symbol]O[symbol] junctions and extend their Josephson response to THZ frequencies / E. Stepantsov et al. Circuit theory analysis of AB-plane tunnel junctions of unconventional superconductor Bi[symbol]Sr[symbol]Ca[symbol]Cu[symbol]O[symbol] / I. Shigeta et al. Transport properties of normal metal/anisotropic superconductor junctions in the eutectic system Sr[symbol]RuO[symbol]Ru / M. Kawamura et al. Macroscopic quantum tunneling in d-wave superconductor Josephson / S. Kawabata et al. Quasiparticle states of high-T[symbol] oxides observed by a Zeeman magnetic field response / S. Kashiwaya et al. Experimentally realizable devices for controlling the motion of magnetic flux quanta in anisotropic superconductors: vortex lenses, vortex diodes and vortex pumps / S. Savel'ev and F. Nori. Stability of vortex-antivortex "molecules" in mesoscopic superconducting triangles / V. R. Misko et al. Superconducting network with magnetic decoration - Hofstadter butterfly in spatially modulated magnetic field / Y. Iye et al. Observation of paramagnetic supercurrent in mesoscopic superconducting rings and disks using multiple-small-tunnel-junction method / A. Kanda et al. Guidance of vortices in high

  14. Evaluating FOMC forecast ranges: an interval data approach

    OpenAIRE

    Henning Fischer; Marta García-Bárzana; Peter Tillmann; Peter Winker

    2012-01-01

    The Federal Open Market Committee (FOMC) of the U.S. Federal Reserve publishes the range of members' forecasts for key macroeconomic variables, but not the distribution of forecasts within this range. To evaluate these projections, previous papers compare the midpoint of the ranges with the realized outcome. This paper proposes a new approach to forecast evaluation that takes account of the interval nature of projections. It is shown that using the conventional Mincer-Zarnowitz approach to ev...

  15. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  16. Statistical methods for forecasting

    CERN Document Server

    Abraham, Bovas

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...

  17. Improving the effectiveness of real-time flood forecasting through Predictive Uncertainty estimation: the multi-temporal approach

    Science.gov (United States)

    Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Todini, Ezio

    2015-04-01

    The negative effects of severe flood events are usually contrasted through structural measures that, however, do not fully eliminate flood risk. Non-structural measures, such as real-time flood forecasting and warning, are also required. Accurate stage/discharge future predictions with appropriate forecast lead-time are sought by decision-makers for implementing strategies to mitigate the adverse effects of floods. Traditionally, flood forecasting has been approached by using rainfall-runoff and/or flood routing modelling. Indeed, both types of forecasts, cannot be considered perfectly representing future outcomes because of lacking of a complete knowledge of involved processes (Todini, 2004). Nonetheless, although aware that model forecasts are not perfectly representing future outcomes, decision makers are de facto implicitly assuming the forecast of water level/discharge/volume, etc. as "deterministic" and coinciding with what is going to occur. Recently the concept of Predictive Uncertainty (PU) was introduced in hydrology (Krzysztofowicz, 1999), and several uncertainty processors were developed (Todini, 2008). PU is defined as the probability of occurrence of the future realization of a predictand (water level/discharge/volume) conditional on: i) prior observations and knowledge, ii) the available information obtained on the future value, typically provided by one or more forecast models. Unfortunately, PU has been frequently interpreted as a measure of lack of accuracy rather than the appropriate tool allowing to take the most appropriate decisions, given a model or several models' forecasts. With the aim to shed light on the benefits for appropriately using PU, a multi-temporal approach based on the MCP approach (Todini, 2008; Coccia and Todini, 2011) is here applied to stage forecasts at sites along the Upper Tiber River. Specifically, the STAge Forecasting-Rating Curve Model Muskingum-based (STAFOM-RCM) (Barbetta et al., 2014) along with the Rating

  18. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  19. Solid low-level waste forecasting guide

    International Nuclear Information System (INIS)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford's experience within the last six years. Hanford's forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford's annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford's forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data

  20. Realistic Realizations Of Threshold Circuits

    Science.gov (United States)

    Razavi, Hassan M.

    1987-08-01

    Threshold logic, in which each input is weighted, has many theoretical advantages over the standard gate realization, such as reducing the number of gates, interconnections, and power dissipation. However, because of the difficult synthesis procedure and complicated circuit implementation, their use in the design of digital systems is almost nonexistant. In this study, three methods of NMOS realizations are discussed, and their advantages and shortcomings are explored. Also, the possibility of using the methods to realize multi-valued logic is examined.

  1. A methodology for Electric Power Load Forecasting

    Directory of Open Access Journals (Sweden)

    Eisa Almeshaiei

    2011-06-01

    Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

  2. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  3. Forecasting reliability of transformer populations

    NARCIS (Netherlands)

    Schijndel, van A.; Wetzer, J.; Wouters, P.A.A.F.

    2007-01-01

    The expected replacement wave in the current power grid faces asset managers with challenging questions. Setting up a replacement strategy and planning calls for a forecast of the long term component reliability. For transformers the future failure probability can be predicted based on the ongoing

  4. Global-warming forecasting models

    International Nuclear Information System (INIS)

    Moeller, K.P.

    1992-01-01

    In spite of an annual man-made quantity of about 20 billion tons, carbon dioxide has remained a trace gas in the atmosphere (350 ppm at present). The reliability of model calculations which forecast temperatures is dicussed in view of the world-wide increase in carbon dioxides. Computer simulations reveal a general, serious threat to the future of mankind. (DG) [de

  5. Forecasting fluid milk and cheese demands for the next decade.

    Science.gov (United States)

    Schmit, T M; Kaiser, H M

    2006-12-01

    Predictions of future market demands and farm prices for dairy products are important determinants in developing marketing strategies and farm-production planning decisions. The objective of this report was to use current aggregate forecast data, combined with existing econometric models of demand and supply, to forecast retail demands for fluid milk and cheese and the supply and price of farm milk over the next decade. In doing so, we can investigate whether projections of population and consumer food-spending patterns will extend or alter current consumption trends and examine the implications of future generic advertising strategies for dairy products. To conduct the forecast simulations and appropriately allocate the farm milk supply to various uses, we used a partial equilibrium model of the US domestic dairy sector that segmented the industry into retail, wholesale, and farm markets. Model simulation results indicated that declines in retail per capita demand would persist but at a reduced rate from years past and that retail per capita demand for cheese would continue to grow and strengthen over the next decade. These predictions rely on expected changes in the size of populations of various ages, races, and ethnicities and on existing patterns of spending on food at home and away from home. The combined effect of these forecasted changes in demand levels was reflected in annualized growth in the total farm-milk supply that was similar to growth realized during the past few years. Although we expect nominal farm milk prices to increase over the next decade, we expect real prices (relative to assumed growth in feed costs) to remain relatively stable and show no increase until the end of the forecast period. Supplemental industry model simulations also suggested that net losses in producer revenues would result if only nominal levels of generic advertising spending were maintained in forthcoming years. In fact, if real generic advertising expenditures are

  6. DEVELOPMENT OF THE PROBABLY-GEOGRAPHICAL FORECAST METHOD FOR DANGEROUS WEATHER PHENOMENA

    Directory of Open Access Journals (Sweden)

    Elena S. Popova

    2015-12-01

    Full Text Available This paper presents a scheme method of probably-geographical forecast for dangerous weather phenomena. Discuss two general realization stages of this method. Emphasize that developing method is response to actual questions of modern weather forecast and it’s appropriate phenomena: forecast is carried out for specific point in space and appropriate moment of time.

  7. Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

    Directory of Open Access Journals (Sweden)

    Yi Liang

    2016-11-01

    Full Text Available The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy and further promote the sustained, healthy and rapid development of the national economy. Under the goal of low-carbon economy, medium and long term electricity demand forecasting will have very important practical significance. In this paper, a new hybrid electricity demand model framework is characterized as follows: firstly, integration of grey relation degree (GRD with induced ordered weighted harmonic averaging operator (IOWHA to propose a new weight determination method of hybrid forecasting model on basis of forecasting accuracy as induced variables is presented; secondly, utilization of the proposed weight determination method to construct the optimal hybrid forecasting model based on extreme learning machine (ELM forecasting model and multiple regression (MR model; thirdly, three scenarios in line with the level of realization of various carbon emission targets and dynamic simulation of effect of low-carbon economy on future electricity demand are discussed. The resulting findings show that, the proposed model outperformed and concentrated some monomial forecasting models, especially in boosting the overall instability dramatically. In addition, the development of a low-carbon economy will increase the demand for electricity, and have an impact on the adjustment of the electricity demand structure.

  8. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  9. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  10. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

    The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamenta......The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged...... fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or singlevalued forecasts, the research interest in probabilistic energy...

  11. EU pharmaceutical expenditure forecast.

    Science.gov (United States)

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

    2014-01-01

    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). 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. 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 (-€5,589 million), and, far behind them

  12. Forecasting risks of natural gas consumption in Slovenia

    Energy Technology Data Exchange (ETDEWEB)

    Potocnik, Primoz; Govekar, Edvard; Grabec, Igor [Laboratory of Synergetics, Ljubljana (Slovenia). Faculty of Mechanical Engineering; Thaler, Marko; Poredos, Alojz [Laboratory for Refrigeration, Ljubljana (Slovenia). Faculty of Mechanical Engineering

    2007-08-15

    Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems' cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company. (author)

  13. Forecasting risks of natural gas consumption in Slovenia

    International Nuclear Information System (INIS)

    Potocnik, Primoz; Thaler, Marko; Govekar, Edvard; Grabec, Igor; Poredos, Alojz

    2007-01-01

    Efficient operation of modern energy distribution systems often requires forecasting future energy demand. This paper proposes a strategy to estimate forecasting risk. The objective of the proposed method is to improve knowledge about expected forecasting risk and to estimate the expected cash flow in advance, based on the risk model. The strategy combines an energy demand forecasting model, an economic incentive model and a risk model. Basic guidelines are given for the construction of a forecasting model that combines past energy consumption data, weather data and weather forecast. The forecasting model is required to estimate expected forecasting errors that are the basis for forecasting risk estimation. The risk estimation strategy also requires an economic incentive model that describes the influence of forecasting accuracy on the energy distribution systems' cash flow. The economic model defines the critical forecasting error levels that most strongly influence cash flow. Based on the forecasting model and the economic model, the development of a risk model is proposed. The risk model is associated with critical forecasting error levels in the context of various influential parameters such as seasonal data, month, day of the week and temperature. The risk model is applicable to estimating the daily forecasting risk based on the influential parameters. The proposed approach is illustrated by a case study of a Slovenian natural gas distribution company

  14. Physical Realizations of Quantum Computing

    CERN Document Server

    Kanemitsu, Shigeru; Salomaa, Martti; Takagi, Shin; Are the DiVincenzo Criteria Fulfilled in 2004 ?

    2006-01-01

    The contributors of this volume are working at the forefront of various realizations of quantum computers. They survey the recent developments in each realization, in the context of the DiVincenzo criteria, including nuclear magnetic resonance, Josephson junctions, quantum dots, and trapped ions. There are also some theoretical contributions which have relevance in the physical realizations of a quantum computer. This book fills the gap between elementary introductions to the subject and highly specialized research papers to allow beginning graduate students to understand the cutting-edge of r

  15. Concerning the justiciability of demand forecasts

    International Nuclear Information System (INIS)

    Nierhaus, M.

    1977-01-01

    This subject plays at present in particular a role in the course of judicial examinations of immediately enforceable orders for the partial construction licences of nuclear power plants. The author distinguishes beween three kinds of forecast decisions: 1. Appraising forecast decisions with standards of judgment taken mainly from the fields of the art, culture, morality, religion are, according to the author, only legally verifyable to a limited extent. 2. With regard to forecast decisions not arguable, e.g. where the future behaviour of persons is concerned, the same should be applied basically. 3. In contrast to this, the following is applicable for programmatic, proceedingslike, or creative forecast decisions, in particular in economics: 'An administrative estimation privilege in a prognostic sense with the consequence that the court has to accept the forecast decision which lies within the forecast margins and which cannot be disproved, and that the court may not replace this forecast decision by its own probability judgment. In these cases, administration has the right to create its own forecast standards.' Judicial control in these cases was limited to certain substantive and procedural mistakes made by the administration in the course of forecast decision finding. (orig./HP) [de

  16. Concerning the justiciability of demand forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Nierhaus, M [Koeln Univ. (Germany, F.R.)

    1977-01-01

    This subject plays at present in particular a role in the course of judicial examinations of immediately enforceable orders for the partial construction licences of nuclear power plants. The author distinguishes beween three kinds of forecast decisions: 1. Appraising forecast decisions with standards of judgment taken mainly from the fields of the art, culture, morality, religion are, according to the author, only legally verifyable to a limited extent. 2. With regard to forecast decisions not arguable, e.g. where the future behaviour of persons is concerned, the same should be applied basically. 3. In contrast to this, the following is applicable for programmatic, proceedingslike, or creative forecast decisions, in particular in economics: 'An administrative estimation privilege in a prognostic sense with the consequence that the court has to accept the forecast decision which lies within the forecast margins and which cannot be disproved, and that the court may not replace this forecast decision by its own probability judgment. In these cases, administration has the right to create its own forecast standards.' Judicial control in these cases was limited to certain substantive and procedural mistakes made by the administration in the course of forecast decision finding.

  17. Proposal and realization advertising campaign

    OpenAIRE

    RYCHLÁ, Marie

    2008-01-01

    The Bachelor Paper contains proposal and realization advertising campaign, including make charge for cost amount. The advertising campaign is made for chosen product of firm. Advertising campaign is planning by the medium of broadsheet and advertising on the Internet.

  18. Mercury emissions from municipal solid waste combustors. An assessment of the current situation in the United States and forecast of future emissions

    Energy Technology Data Exchange (ETDEWEB)

    None

    1993-05-01

    This report examines emissions of mercury (Hg) from municipal solid waste (MSW) combustion in the United States (US). It is projected that total annual nationwide MSW combustor emissions of mercury could decrease from about 97 tonnes (1989 baseline uncontrolled emissions) to less than about 4 tonnes in the year 2000. This represents approximately a 95 percent reduction in the amount of mercury emitted from combusted MSW compared to the 1989 mercury emissions baseline. The likelihood that routinely achievable mercury emissions removal efficiencies of about 80 percent or more can be assured; it is estimated that MSW combustors in the US could prove to be a comparatively minor source of mercury emissions after about 1995. This forecast assumes that diligent measures to control mercury emissions, such as via use of supplemental control technologies (e.g., carbon adsorption), are generally employed at that time. However, no present consensus was found that such emissions control measures can be implemented industry-wide in the US within this time frame. Although the availability of technology is apparently not a limiting factor, practical implementation of necessary control technology may be limited by administrative constraints and other considerations (e.g., planning, budgeting, regulatory compliance requirements, etc.). These projections assume that: (a) about 80 percent mercury emissions reduction control efficiency is achieved with air pollution control equipment likely to be employed by that time; (b) most cylinder-shaped mercury-zinc (CSMZ) batteries used in hospital applications can be prevented from being disposed into the MSW stream or are replaced with alternative batteries that do not contain mercury; and (c) either the amount of mercury used in fluorescent lamps is decreased to an industry-wide average of about 27 milligrams of mercury per lamp or extensive diversion from the MSW stream of fluorescent lamps that contain mercury is accomplished.

  19. Extravehicular Activity (EVA) Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2010-01-01

    Beginning in Fiscal Year (FY) 2011, Extravehicular activity (EVA) technology development became a technology foundational domain under a new program Enabling Technology Development and Demonstration. The goal of the EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA technology life and limited availability of the EMUs will become a critical issue eventually. The current Extravehicular Mobility Unit (EMU) has vastly served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability could be an option for the future mission applications building off of the technology development over the last several years. Besides ISS, potential mission applications include EVAs for

  20. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  1. Cracks in the crystal ball : What happens to firms’ foreign exchange rate exposure when forecasters don’t agree about the future

    NARCIS (Netherlands)

    A. Muller (Aline); J. Poncelet (Julien); W.F.C. Verschoor (Willem); R.C.J. Zwinkels (Remco)

    2013-01-01

    textabstractThe central issue of this paper is whether stock prices are exposed to total exchange rate movements – as traditionally measured – or to revisions in expected future exchange rate movements and unanticipated currency shocks, and by how much of each. Based on a sample of 1675 U.S. firms

  2. The development rainfall forecasting using kalman filter

    Science.gov (United States)

    Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

    2018-04-01

    Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

  3. Forecast Of International Security Threat Of Russia In 2017

    Directory of Open Access Journals (Sweden)

    A. O. Bezrukov

    2017-01-01

    Full Text Available The article analyzes the threats to international security of Russia in 2017. It presents the analysis of the twelve situations, the development of which could have a significant effect on the interests of Russia in the field of international security. There is the most probable scenario for every situation and a list of conditions of its occurrence. The objective of the forecast is reduction of uncertainty of the future and the promotion of reasonable hypotheses about its likely scenarios. The forecast task is to help decision-makers, mentally put yourself in a situation in which realized one of the scenarios for the future and to encourage them to calculate their possible actions. In the preparation of the forecast two scenario analysis tools were used: the allocation of two key variables, the ratio of which determines the spectrum of the analyzed scenarios, and the key events method, which consists of several stages and allows to evaluate the prospect of implementing the scenario observed in real time. Authors conclude that the USA with the new president will be forced to choose between maintaining global posture and keeping order at home, and the EU will be absorbed by internal issues. In 2017 for Russia is important to keep the positive dynamics in the Transatlantic and Grand Eurasia regions, and in the Middle East. For this purpose it is necessary to ignore the provocations – mainly in Europe. The source of a new crisis may be NATO members discouraged by lack of attention to them by the USA or allies of Russia.

  4. The Information Content of Treasury Bond Options Concerning Future Volatility and Price Jumps

    DEFF Research Database (Denmark)

    Busch, Thomas; Christensen, Bent Jesper; Nielsen, Morten Ørregaard

    We study the relation between realized and implied volatility in the bond market. Realizedvolatility is constructed from high-frequency (5-minute) returns on 30 year Treasury bond futures.Implied volatility is backed out from prices of associated bond options. Recent nonparametric statisticaltech......We study the relation between realized and implied volatility in the bond market. Realizedvolatility is constructed from high-frequency (5-minute) returns on 30 year Treasury bond futures.Implied volatility is backed out from prices of associated bond options. Recent nonparametric...... components. We also introduce a new vector HAR (VecHAR) modelfor the resulting simultaneous system, controlling for possible endogeneity of implied volatility inthe forecasting equations. We show that implied volatility is a biased and inefficient forecast in thebond market. However, implied volatility does...

  5. Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

    Science.gov (United States)

    Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

    2016-01-01

    Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

  6. Forecasting in Complex Systems

    Science.gov (United States)

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

    2014-12-01

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

  7. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  8. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  9. Sales Forecasting for Fashion Retailing Service Industry: A Review

    Directory of Open Access Journals (Sweden)

    Na Liu

    2013-01-01

    Full Text Available Sales forecasting is crucial for many retail operations. It is especially critical for the fashion retailing service industry in which product demand is very volatile and product’s life cycle is short. This paper conducts a comprehensive literature review and selects a set of papers in the literature on fashion retail sales forecasting. The advantages and the drawbacks of different kinds of analytical methods for fashion retail sales forecasting are examined. The evolution of the respective forecasting methods over the past 15 years is revealed. Issues related to real-world applications of the fashion retail sales forecasting models and important future research directions are discussed.

  10. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  11. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  12. “Swimming Ducks Forecast the Coming of Spring”—The predictability of aggregate insider trading on future market returns in the Chinese market

    Directory of Open Access Journals (Sweden)

    Chafen Zhu

    2014-09-01

    Full Text Available This study systematically examines the ability of aggregate insider trading to predict future market returns in the Chinese A-share market. After controlling for the contrarian investment strategy, aggregate executive (large shareholder trading conducted over the past six months can predict 66% (72.7% of market returns twelve months in advance. Aggregate insider trading predicts future market returns very accurately and is stronger for insiders who have a greater information advantage (e.g., executives and controlling shareholders. Corporate governance also affects the predictability of insider trading. The predictability of executive trading is weakest in central state-owned companies, probably because the “quasi-official” status of the executives in those companies effectively curbs their incentives to benefit from insider trading. The predictive power of large shareholder trading in private-owned companies is higher than that in state-owned companies, probably due to their stronger profit motivation and higher involvement in business operations. This study complements the literature by examining an emerging market and investigating how the institutional context and corporate governance affect insider trading.

  13. Forecasting the future reimbursement system of Korean National Health Insurance: a contemplation focusing on global budget and Neo-KDRG-based payment systems.

    Science.gov (United States)

    Kim, Yang-Kyun

    2012-05-01

    With the adoption of national health insurance in 1977, Korea has been utilizing fee-for-service payment with contract-based healthcare reimbursement system in 2000. Under the system, fee-for-service reimbursement has been accused of augmenting national healthcare expenditure by excessively increasing service volume. The researcher examined in this paper two major alternatives including diagnosis related group-based payment and global budget to contemplate the future of reimbursement system of Korean national health insurance. Various literature and preceding studies on pilot project and actual implementation of Neo-KDRG were reviewed. As a result, DRG-based payment was effective for healthcare cost control but low in administrative efficiency. Global budget may be adequate for cost control and improving the quality of healthcare and administrative efficiency. However, many healthcare providers disagree that excess care arising from fee-for-service payment alone has led to financial deterioration of national health insurance and healthcare institutions should take responsibility with global budget payment as an appropriate solution. Dissimilar payment systems may be applied to different types of institutions to reflect their unique attributes, and this process can be achieved step-by-step. Developing public sphere among the stakeholders and striving for consensus shall be kept as collateral to attain the desirable reimbursement system in the future.

  14. “Swimming Ducks Forecast the Coming of Spring”—The predictability of aggregate insider trading on future market returns in the Chinese market

    Institute of Scientific and Technical Information of China (English)

    Chafen; Zhu; Li; Wang; Tengfei; Yang

    2014-01-01

    This study systematically examines the ability of aggregate insider trading to predict future market returns in the Chinese A-share market. After controlling for the contrarian investment strategy, aggregate executive(large shareholder)trading conducted over the past six months can predict 66%(72.7%) of market returns twelve months in advance. Aggregate insider trading predicts future market returns very accurately and is stronger for insiders who have a greater information advantage(e.g., executives and controlling shareholders).Corporate governance also affects the predictability of insider trading. The predictability of executive trading is weakest in central state-owned companies,probably because the "quasi-official" status of the executives in those companies effectively curbs their incentives to benefit from insider trading.The predictive power of large shareholder trading in private-owned companies is higher than that in state-owned companies, probably due to their stronger profit motivation and higher involvement in business operations. This study complements the literature by examining an emerging market and investigating how the institutional context and corporate governance affect insider trading.

  15. The Realized Hierarchical Archimedean Copula in Risk Modelling

    Directory of Open Access Journals (Sweden)

    Ostap Okhrin

    2017-06-01

    Full Text Available This paper introduces the concept of the realized hierarchical Archimedean copula (rHAC. The proposed approach inherits the ability of the copula to capture the dependencies among financial time series, and combines it with additional information contained in high-frequency data. The considered model does not suffer from the curse of dimensionality, and is able to accurately predict high-dimensional distributions. This flexibility is obtained by using a hierarchical structure in the copula. The time variability of the model is provided by daily forecasts of the realized correlation matrix, which is used to estimate the structure and the parameters of the rHAC. Extensive simulation studies show the validity of the estimator based on this realized correlation matrix, and its performance, in comparison to the benchmark models. The application of the estimator to one-day-ahead Value at Risk (VaR prediction using high-frequency data exhibits good forecasting properties for a multivariate portfolio.

  16. Multiple Realizability and Biological Laws

    NARCIS (Netherlands)

    Raerinne, Jani P.; Eronen, Markus I.

    2012-01-01

    We critically analyze Alexander Rosenberg's argument based on the multiple realizability of biological properties that there are no biological laws. The argument is intuitive and suggestive. Nevertheless, a closer analysis reveals that the argument rests on dubious assumptions about the nature of

  17. Realizations of the canonical representation

    Indian Academy of Sciences (India)

    Traditionally, the canonical representation is realized on the Hilbert space ... Fix a decomposition R2n = Rn × Rn ..... to an orthonormal basis {ψ1,ψ2,. ..... [7] Vemuri M K, A non-commutative Sobolev inequality and its application to spectral.

  18. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  19. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  20. Can energy forecasts be improved?

    International Nuclear Information System (INIS)

    Rech, O.; Alban, P.

    2000-01-01

    Within the present day context of energy, characterized by the gap between short term trends and long term risks, forecasting takes on particular interest. We based our study on the evaluation of the results of some of these long term (2020) and very long term (2050) forecasts. This article looks at the overall demand for energy, whereas the evolution of each primary energy will be handled in a future article. We are restricting our analysis to a global level despite the inherent limitations of such a choice. Our approach mainly concentrates on the dynamics of the phenomena. Thus, we have noticed a simultaneous slowing down since the 1960's of the demography, economy and energy. The revenue and energy consumption per capita do not elude this tendency. At the same time, energy production leads a steep downward tendency. All in all, the forecasts have a tendency to conflict more or less with these changes. In the majority of the scenarios the anticipated rhythms of economic change and energy consumption would indicate a sudden and abrupt inverse of current dynamics. We have noticed that the single use of the average annual rate of change is insufficient to clearly present the long term tendencies that follow curved and not linear paths. Diagnostic errors made in past analyses are likely to affect the models for forecasting, for which the inferred dynamics have not been fully apprehended

  1. An Optimization of Inventory Demand Forecasting in University Healthcare Centre

    Science.gov (United States)

    Bon, A. T.; Ng, T. K.

    2017-01-01

    Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

  2. Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Haoran Zhao

    2018-03-01

    Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

  3. Challenges in realizing ultraflat materials surfaces

    Directory of Open Access Journals (Sweden)

    Takashi Yatsui

    2013-12-01

    Full Text Available Ultraflat surface substrates are required to achieve an optimal performance of future optical, electronic, or optoelectronic devices for various applications, because such surfaces reduce the scattering loss of photons, electrons, or both at the surfaces and interfaces. In this paper, we review recent progress toward the realization of ultraflat materials surfaces. First, we review the development of surface-flattening techniques. Second, we briefly review the dressed photon–phonon (DPP, a nanometric quasiparticle that describes the coupled state of a photon, an electron, and a multimode-coherent phonon. Then, we review several recent developments based on DPP-photochemical etching and desorption processes, which have resulted in angstrom-scale flat surfaces. To confirm that the superior flatness of these surfaces that originated from the DPP process, we also review a simplified mathematical model that describes the scale-dependent effects of optical near-fields. Finally, we present the future outlook for these technologies.

  4. PRAGMATIC TRANSFER IN REQUEST REALIZATIONS

    Directory of Open Access Journals (Sweden)

    Indawan Syahri

    2007-01-01

    Full Text Available This study investigates the pragmatic transfer in English request realizations made by EFL learners, i.e. the proficient learners. The subjects were students of an English Study Program who obtained TOEFL-like scores of at least 450. The data were collected by means of DCT-questionnaires and Role-plays. The results show that the subjects realize requests in the form of external modifications more frequently. Most of them embed their requests with supportive moves dominantly. They enfold the acts with the moves before, after or in both positions. Of the three positions, they mostly insert the moves initial position, i.e., through inductive patterns. This is due to pragmatic transfer.

  5. Forecast communication through the newspaper Part 1: Framing the forecaster

    Science.gov (United States)

    Harris, Andrew J. L.

    2015-04-01

    This review is split into two parts both of which address issues of forecast communication of an environmental disaster through the newspaper during a period of crisis. The first part explores the process by which information passes from the scientist or forecaster, through the media filter, to the public. As part of this filter preference, omission, selection of data, source, quote and story, as well as placement of the same information within an individual piece or within the newspaper itself, can serve to distort the message. The result is the introduction of bias and slant—that is, the message becomes distorted so as to favor one side of the argument against another as it passes through the filter. Bias can be used to support spin or agenda setting, so that a particular emphasis becomes placed on the story which exerts an influence on the reader's judgment. The net result of the filter components is either a negative (contrary) or positive (supportive) frame. Tabloidization of the news has also resulted in the use of strong, evocative, exaggerated words, headlines and images to support a frame. I illustrate these various elements of the media filter using coverage of the air space closure due to the April 2010 eruption of Eyjafjallajökull (Iceland). Using the British press coverage of this event it is not difficult to find examples of all media filter elements, application of which resulted in bias against the forecast and forecaster. These actors then became named and blamed. Within this logic, it becomes only too easy for forecasters and scientists to be framed in a negative way through blame culture. The result is that forecast is framed in such a way so as to cause the forecaster to be blamed for all losses associated with the loss-causing event. Within the social amplification of risk framework (SARF), this can amplify a negative impression of the risk, the event and the response. However, actions can be taken to avoid such an outcome. These actions

  6. Trend analysis of mortality rates and causes of death in children under 5 years old in Beijing, China from 1992 to 2015 and forecast of mortality into the future: an entire population-based epidemiological study.

    Science.gov (United States)

    Cao, Han; Wang, Jing; Li, Yichen; Li, Dongyang; Guo, Jin; Hu, Yifei; Meng, Kai; He, Dian; Liu, Bin; Liu, Zheng; Qi, Han; Zhang, Ling

    2017-09-18

    To analyse trends in mortality and causes of death among children aged under 5 years in Beijing, China between 1992 and 2015 and to forecast under-5 mortality rates (U5MRs) for the period 2016-2020. An entire population-based epidemiological study was conducted. Data collection was based on the Child Death Reporting Card of the Beijing Under-5 Mortality Rate Surveillance Network. Trends in mortality and leading causes of death were analysed using the χ 2 test and SPSS 19.0 software. An autoregressive integrated moving average (ARIMA) model was fitted to forecast U5MRs between 2016 and 2020 using the EViews 8.0 software. Mortality in neonates, infants and children aged under 5 years decreased by 84.06%, 80.04% and 80.17% from 1992 to 2015, respectively. However, the U5MR increased by 7.20% from 2013 to 2015. Birth asphyxia, congenital heart disease, preterm/low birth weight and other congenital abnormalities comprised the top five causes of death. The greatest, most rapid reduction was that of pneumonia by 92.26%, with an annual average rate of reduction of 10.53%. The distribution of causes of death differed among children of different ages. Accidental asphyxia and sepsis were among the top five causes of death in children aged 28 days to 1 year and accident was among the top five causes in children aged 1-4 years. The U5MRs in Beijing are projected to be 2.88‰, 2.87‰, 2.90‰, 2.97‰ and 3.09‰ for the period 2016-2020, based on the predictive model. Beijing has made considerable progress in reducing U5MRs from 1992 to 2015. However, U5MRs could show a slight upward trend from 2016 to 2020. Future considerations for child healthcare include the management of birth asphyxia, congenital heart disease, preterm/low birth weight and other congenital abnormalities. Specific preventative measures should be implemented for children of various age groups. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All

  7. Forecasting Canadian nuclear power station construction costs

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions. (author)

  8. Forecasting market developments

    International Nuclear Information System (INIS)

    Weller, T.

    1997-01-01

    Traditional planning in essence consists of linear extrapolation of established facts and experience. This approach was good enough until recently, when progress would be relatively foreseeable within a stable system. The situation has been changing with developments and modifications in the global economic sector proceeding at accelerated pace, so that conventional planning methods become hopelessly inadequate. The past is of low significance to emerging markets; planners today have to keep abreast with and take into account the possible and emerging influencing factors. Experience is a factor to be replaced by intelligent analysis and conclusion within the framework of system networks. Modern scenario modelling methods are based on this approach: They are able to simulate and forecast a whole range of ''possible futures'', derived from perceivable trends. The article illustrates the novel planning methodology by assessing the future of the renewable energy sources, applying a computerized planning method (vision design) which is based on intelligent comparative analysis of all relevant trends. (Orig./RHM) [de

  9. Online forecasting of electrical load for distributed management of plug-in electric vehicles

    OpenAIRE

    Basu , Kaustav; Ovalle , Andres; Guo , Baoling; Hably , Ahmad; Bacha , Seddik; Hajar , Khaled

    2016-01-01

    International audience; The paper aims at making online forecast of electrical load at the MV-LV transformer level. Optimal management of the Plug-in Electric Vehicles (PEV) charging requires the forecast of the electrical load for future hours. The forecasting module needs to be online (i.e update and make forecast for the future hours, every hour). The inputs to the predictor are historical electrical and weather data. Various data driven machine learning algorithms are compared to derive t...

  10. Nambe Pueblo Water Budget and Forecasting model.

    Energy Technology Data Exchange (ETDEWEB)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  11. Satellite based Ocean Forecasting, the SOFT project

    Science.gov (United States)

    Stemmann, L.; Tintoré, J.; Moneris, S.

    2003-04-01

    The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

  12. High-frequency volatility combine forecast evaluations: An empirical study for DAX

    Directory of Open Access Journals (Sweden)

    Wen Cheong Chin

    2017-01-01

    Full Text Available This study aims to examine the benefits of combining realized volatility, higher power variation volatility and nearest neighbour truncation volatility in the forecasts of financial stock market of DAX. A structural break heavy-tailed heterogeneous autoregressive model under the heterogeneous market hypothesis specification is employed to capture the stylized facts of high-frequency empirical data. Using selected averaging forecast methods, the forecast weights are assigned based on the simple average, simple median, least squares and mean square error. The empirical results indicated that the combination of forecasts in general shown superiority under four evaluation criteria regardless which proxy is set as the actual volatility. As a conclusion, we summarized that the forecast performance is influenced by three factors namely the types of volatility proxy, forecast methods (individual or averaging forecast and lastly the type of actual forecast value used in the evaluation criteria.

  13. Forecasting in the presence of expectations

    Science.gov (United States)

    Allen, R.; Zivin, J. G.; Shrader, J.

    2016-05-01

    Physical processes routinely influence economic outcomes, and actions by economic agents can, in turn, influence physical processes. This feedback creates challenges for forecasting and inference, creating the potential for complementarity between models from different academic disciplines. Using the example of prediction of water availability during a drought, we illustrate the potential biases in forecasts that only take part of a coupled system into account. In particular, we show that forecasts can alter the feedbacks between supply and demand, leading to inaccurate prediction about future states of the system. Although the example is specific to drought, the problem of feedback between expectations and forecast quality is not isolated to the particular model-it is relevant to areas as diverse as population assessments for conservation, balancing the electrical grid, and setting macroeconomic policy.

  14. Forecasting for the Small Retail Business: Operational Recommendations

    OpenAIRE

    J. Holton Wilson; Robert H. Miller

    1998-01-01

    Often small business owners/managers feel they have inadequate time for formal forecasting and/or that they lack the expertise to do so. Since forecasting is an important decision-aiding tool, managers in small retail establishments can benefit by implementing a simple forecasting process. Doing so will enable them to better anticipate the firms future level of sales and lead to more successful operations. We suggest the use of relatively simple quantitative methods that have proven to work w...

  15. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  16. Models of Investor Forecasting Behavior — Experimental Evidence

    Directory of Open Access Journals (Sweden)

    Federico Bonetto

    2017-12-01

    Full Text Available Different forecasting behaviors affect investors’ trading decisions and lead to qualitatively different asset price trajectories. It has been shown in the literature that the weights that investors place on observed asset price changes when forecasting future price changes, and the nature of their confidence when price changes are forecast, determine whether price bubbles, price crashes, and unpredictable price cycles occur. In this paper, we report the results of behavioral experiments involving multiple investors who participated in a market for a virtual asset. Our goal is to study investors’ forecast formation. We conducted three experimental sessions with different participants in each session. We fit different models of forecast formation to the observed data. There is strong evidence that the investors forecast future prices by extrapolating past price changes, even when they know the fundamental value of the asset exactly and the extrapolated forecasts differ significantly from the fundamental value. The rational expectations hypothesis seems inconsistent with the observed forecasts. The forecasting models of all participants that best fit the observed forecasting data were of the type that cause price bubbles and cycles in dynamical systems models, and price bubbles and cycles ended up occurring in all three sessions.

  17. Design and realization of simulators

    International Nuclear Information System (INIS)

    Mathey, C.

    1984-01-01

    The two main categories of simulators are training simulators of which aim is the education of the nuclear power plant operators, and the study simulators. The French park of simulators is reviewed, as also their field of utilization. One deals with the simulator design: general description, calculation tools, middleware, and programming, mathematical models and numerical methods. Then, the instructor post of the EDF's simulators are more particularly described. The realization of a simulator includes two main stages: the development of the material and, the development of the software [fr

  18. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

    This article deals with the problems of forecasting models. First part of the article is dedicated to definition of the relevant areas (vertical and horizontal pillar of definition) and then the forecasting model itself is defined; as article presents theoretical background for further primary research, this definition is crucial. Finally the position of forecasting models within the management system is identified. The paper is a part of the outputs of FEM CULS grant no. 1312/11/3121.

  19. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  20. Net load forecasting for high renewable energy penetration grids

    International Nuclear Information System (INIS)

    Kaur, Amanpreet; Nonnenmacher, Lukas; Coimbra, Carlos F.M.

    2016-01-01

    We discuss methods for net load forecasting and their significance for operation and management of power grids with high renewable energy penetration. Net load forecasting is an enabling technology for the integration of microgrid fleets with the macrogrid. Net load represents the load that is traded between the grids (microgrid and utility grid). It is important for resource allocation and electricity market participation at the point of common coupling between the interconnected grids. We compare two inherently different approaches: additive and integrated net load forecast models. The proposed methodologies are validated on a microgrid with 33% annual renewable energy (solar) penetration. A heuristics based solar forecasting technique is proposed, achieving skill of 24.20%. The integrated solar and load forecasting model outperforms the additive model by 10.69% and the uncertainty range for the additive model is larger than the integrated model by 2.2%. Thus, for grid applications an integrated forecast model is recommended. We find that the net load forecast errors and the solar forecasting errors are cointegrated with a common stochastic drift. This is useful for future planning and modeling because the solar energy time-series allows to infer important features of the net load time-series, such as expected variability and uncertainty. - Highlights: • Net load forecasting methods for grids with renewable energy generation are discussed. • Integrated solar and load forecasting outperforms the additive model by 10.69%. • Net load forecasting reduces the uncertainty between the interconnected grids.

  1. Too Many, Too Few, or Just Right? Making Sense Of Conflicting RN Supply and Demand Forecasts.

    Science.gov (United States)

    Spetz, Joanne

    2015-01-01

    Forecasts of future supply and demand of health professionals are tools to guide policy, not a final statement about how the world will be in the future. Recent forecasts of RN supply and demand vary widely and are incredibly confusing for nurse leaders, nurse educators, and policymakers. To effectively incorporate forecasts into policy and planning, one must understand the structure of the forecasts and underlying assumptions. One should treat all forecasts cautiously, and use them as guides to policy rather than definitive future outcomes.

  2. Forecasting economic aspects of future wireless services

    DEFF Research Database (Denmark)

    Falch, Morten; Henten, Anders; Saugstrup, Dan

    services be shaped like the Internet today with a large number of independent information providers offering their services directly to the customers? This deliverable will analyse economic models for delivery of ‘3G and beyond’ wireless Internet services, and assess the types of services that will drive...... the market and the business models to be applied. The analysis will take current market trends as point of departure with focus on vanguard markets with respect to 3G services....

  3. Nuclear wastes future: results and forecasting

    International Nuclear Information System (INIS)

    2001-01-01

    Since many years, the CEA is greatly involved in the research programs on the long-dated management of radioactive wastes. This document presents the CEA development in the following domains: the spent fuel processing, the high separation process, the environmental behavior of wastes packages, the glass performance and the apatites behavior in the new matrix. (A.L.B.)

  4. A global flash flood forecasting system

    Science.gov (United States)

    Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

    2016-04-01

    The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

  5. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  6. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  7. Fast, Flexible, and Digital: Forecasts for Occupational and Workplace Education.

    Science.gov (United States)

    Ausburn, Lynna J.

    2002-01-01

    Three Delphi panels of occupational educators (n=16, 9, 12) forecast scenarios for the future of workplace education, which were compared with results of a literature review. Results indicated increasing alignment of practitioners' forecasts for dramatically transformed workplace education with major trends identified in the literature. (Contains…

  8. Biorefineries. Prerequisite for the realization of a future bioeconomy

    Energy Technology Data Exchange (ETDEWEB)

    Wagemann, K. [DECHEMA e.V., Frankfurt am Main (Germany)

    2012-07-01

    The current discussion on how to establish a bioeconomy aims in particular at a significant increase of the share of renewable raw materials in the feedstock pool for the production of chemicals and materials; this share currently is around 12%. Such products can be intermediate chemicals, presently already produced from petroleum. Other chemicals, which can be components of new value chains, are also being discussed. In addition materials like biopolymers are already used directly in consumer goods. These considerations imply a higher demand on renewable raw materials especially from plants. Biorefineries will play an important role in meeting this demand. The German Government has decided to draw up a roadmap being established by a group of independent experts from industry and academia. This roadmap describes in a systematic way status and perspectives of the different biorefinery concepts. It takes economic and ecological aspects into considerations and analyses the R and D demand. The following definition is taken as a basis for the analysis: 'A biorefinery is characterised by having a dedicated, integrative overall approach, using biomass as a versatile raw material source for the sustainable production of a spectrum of different intermediates and marketable products (chemicals, materials, bioenergy and food/feed co-products) by using the biomass components as complete as possible.' The analysis considers the following promising concepts: - Sugar biorefinery and Starch biorefinery; - Plant oil biorefinery including Algae lipid biorefinery; - Lignocellulose (Cellulose/Hemicellulose/Lignin) biorefinery including Green (green fibre/green juice) biorefinery; - Synthesis gas biorefinery; - Biogas biorefinery. The roadmap analyses the strengths, weaknesses, opportunities and threats of the different concepts. For several specific examples preliminary economical and ecological assessment were carried out. The lecture will also give examples how these concepts are presently implemented either top down being integrated in existing plants using renewable raw materials as feedstock or top down as standalone plants mostly on a pilot or demonstration scale. (orig.)

  9. Realizing a Clean Energy Future: Highlights of NREL Analysis (Brochure)

    Energy Technology Data Exchange (ETDEWEB)

    2013-12-01

    Profound energy system transformation is underway. In Hawaiian mythology, Maui set out to lasso the sun in order to capture its energy. He succeeded. That may have been the most dramatic leap forward in clean energy systems that the world has known. Until now. Today, another profound transformation is underway. A combination of forces is taking us from a carbon-centric, inefficient energy system to one that draws from diverse energy sources - including the sun. NREL analysis is helping guide energy systems policy and investment decisions through this transformation. This brochure highlights NREL analysis accomplishments in the context of four thematic storylines.

  10. Realization of a Desired Future: Innovation in Education

    Science.gov (United States)

    Findikoglu, Fuat; Ilhan, Dilek

    2016-01-01

    Today and tomorrow, the world needs individuals who can manipulate critical and creative thinking skills to solve problems as a team. With technology, the way knowledge is obtained, constructed and communicated have completely transformed and altered. When it comes to education, it is a matter of question whether education is capable of creating…

  11. Sub-Seasonal Climate Forecast Rodeo

    Science.gov (United States)

    Webb, R. S.; Nowak, K.; Cifelli, R.; Brekke, L. D.

    2017-12-01

    The Bureau of Reclamation, as the largest water wholesaler and the second largest producer of hydropower in the United States, benefits from skillful forecasts of future water availability. Researchers, water managers from local, regional, and federal agencies, and groups such as the Western States Water Council agree that improved precipitation and temperature forecast information at the sub-seasonal to seasonal (S2S) timescale is an area with significant potential benefit to water management. In response, and recognizing NOAA's leadership in forecasting, Reclamation has partnered with NOAA to develop and implement a real-time S2S forecasting competition. For a year, solvers are submitting forecasts of temperature and precipitation for weeks 3&4 and 5&6 every two weeks on a 1x1 degree grid for the 17 western state domain where Reclamation operates. The competition began on April 18, 2017 and the final real-time forecast is due April 3, 2018. Forecasts are evaluated once observational data become available using spatial anomaly correlation. Scores are posted on a competition leaderboard hosted by the National Integrated Drought Information System (NIDIS). The leaderboard can be accessed at: https://www.drought.gov/drought/sub-seasonal-climate-forecast-rodeo. To be eligible for cash prizes - which total $800,000 - solvers must outperform two benchmark forecasts during the real-time competition as well as in a required 11-year hind-cast. To receive a prize, competitors must grant a non-exclusive license to practice their forecast technique and make it available as open source software. At approximately one quarter complete, there are teams outperforming the benchmarks in three of the four competition categories. With prestige and monetary incentives on the line, it is hoped that the competition will spur innovation of improved S2S forecasts through novel approaches, enhancements to established models, or otherwise. Additionally, the competition aims to raise

  12. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  13. Dreams, Perception, and Creative Realization.

    Science.gov (United States)

    Glaskin, Katie

    2015-10-01

    This article draws on the ethnography of Aboriginal Australia to argue that perceptual openness, extending from waking life into dreaming experience, provides an important cognitive framework for the apprehension of dreamt experience in these contexts. I argue that this perceptual openness is analogous to the "openness to experience" described as a personality trait that had been linked with dream recall frequency (among other things). An implication of identifying perceptual openness at a cultural rather than at an individual level is two-fold. It provides an example of the ways in which cultural differences affect perception, indicative of cognitive diversity; and, given the relationship between dreams and creativity suggested anecdotally and through research, a cultural orientation toward perceptual openness is also likely to have implications for the realization of creativity that occurs through dreams. Such creativity though cannot be separated from the relational context in which such dreamt material is elaborated and understood. Copyright © 2015 Cognitive Science Society, Inc.

  14. Greening the Future

    Science.gov (United States)

    Williamson, Norma Velia

    2011-01-01

    Because educators vicariously touch the future through their students, the author believes that they sometimes have the uncanny ability to see the future. One common future forecast is the phenomenal growth of green jobs in the emerging green economy, leading to the creation of the "Reach of the Sun" Solar Energy Academy at La Mirada…

  15. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  16. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

    Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

  17. On density forecast evaluation

    NARCIS (Netherlands)

    Diks, C.

    2008-01-01

    Traditionally, probability integral transforms (PITs) have been popular means for evaluating density forecasts. For an ideal density forecast, the PITs should be uniformly distributed on the unit interval and independent. However, this is only a necessary condition, and not a sufficient one, as

  18. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  19. Data Driven Broiler Weight Forecasting using Dynamic Neural Network Models

    DEFF Research Database (Denmark)

    Johansen, Simon Vestergaard; Bendtsen, Jan Dimon; Riisgaard-Jensen, Martin

    2017-01-01

    In this article, the dynamic influence of environmental broiler house conditions and broiler growth is investigated. Dynamic neural network forecasting models have been trained on farm-scale broiler batch production data from 12 batches from the same house. The model forecasts future broiler weight...... and uses environmental conditions such as heating, ventilation, and temperature along with broiler behavior such as feed and water consumption. Training data and forecasting data is analyzed to explain when the model might fail at generalizing. We present ensemble broiler weight forecasts to day 7, 14, 21...

  20. 7 CFR 1710.206 - Approval requirements for load forecasts prepared pursuant to approved load forecast work plans.

    Science.gov (United States)

    2010-01-01

    ... financial ratings, and participation in reliability council, power pool, regional transmission group, power... analysis and modeling of the borrower's electric system loads as provided for in the load forecast work plan. (5) A narrative discussing the borrower's past, existing, and forecast of future electric system...

  1. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

    We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

  2. Real-time data processing and inflow forecasting

    International Nuclear Information System (INIS)

    Olason, T.; Lafreniere, M.

    1998-01-01

    One of the key inputs into the short-term scheduling of hydroelectric generation is inflow forecasting which is needed for natural or unregulated inflows into various lakes, reservoirs and river sections. The forecast time step and time horizon are determined by the time step and the scheduling horizon. Acres International Ltd. has developed the Vista Decision Support System (DSS) in which the time step is one hour and the scheduling can be done up to two weeks into the future. This paper presents the basis of the operational flow-forecasting module of the Vista DSS software and its application to flow forecasting for 16 basins within Nova Scotia Power's hydroelectric system. Among the tasks performed by the software are collection and treatment of data (in real time) regarding meteorological forecasts, reviews and monitoring of hydro-meteorological data, updating of the state variables in the module, and the review and adjustment of sub-watershed forecasts

  3. Influenza forecasting with Google Flu Trends.

    Science.gov (United States)

    Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E

    2013-01-01

    We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by

  4. Spatiotemporal drought forecasting using nonlinear models

    Science.gov (United States)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  5. Using imperfect advance demand information in forecasting

    NARCIS (Netherlands)

    Tan, T.

    2008-01-01

    In this paper, we consider the demand-forecasting problem of a make-to-stock system operating in a business-to-business environment where some customers provide information on their future orders, which are subject to changes in time, hence constituting imperfect advance demand information (ADI).

  6. MACROECONOMIC FORECASTING USING BAYESIAN VECTOR AUTOREGRESSIVE APPROACH

    Directory of Open Access Journals (Sweden)

    D. Tutberidze

    2017-04-01

    Full Text Available There are many arguments that can be advanced to support the forecasting activities of business entities. The underlying argument in favor of forecasting is that managerial decisions are significantly dependent on proper evaluation of future trends as market conditions are constantly changing and require a detailed analysis of future dynamics. The article discusses the importance of using reasonable macro-econometric tool by suggesting the idea of conditional forecasting through a Vector Autoregressive (VAR modeling framework. Under this framework, a macroeconomic model for Georgian economy is constructed with the few variables believed to be shaping business environment. Based on the model, forecasts of macroeconomic variables are produced, and three types of scenarios are analyzed - a baseline and two alternative ones. The results of the study provide confirmatory evidence that suggested methodology is adequately addressing the research phenomenon and can be used widely by business entities in responding their strategic and operational planning challenges. Given this set-up, it is shown empirically that Bayesian Vector Autoregressive approach provides reasonable forecasts for the variables of interest.

  7. A Realization Approach for Residual Expressions

    DEFF Research Database (Denmark)

    Skovmose Kallesøe, Carsten; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal

    2006-01-01

    This paper is concerned with state space realization of inherent redundant information in subsystems, which are identified by structural analysis (SA) approach. The identified subsystems are assumed to involve algebraic variables, representing unknown signals. The proposed realization method...

  8. Realization of an integral using anticommuting variables

    International Nuclear Information System (INIS)

    Valuev, B.N.

    1979-01-01

    It is shown that the integral defined by Berezin over anticommuting variables may be realized as a trace on the Clifford algebra. In fact, this realization makes precise the definition of the integral

  9. Realizing the potential of nuclear energy

    International Nuclear Information System (INIS)

    Walske, C.

    1982-01-01

    The future of nuclear power, just as the future of America, can be viewed with optimism. There is hope in America's record of overcoming obstacles, but growth is essential for that hope to be realized. Despite the downturn in energy demand made possible by conservation, we will need a 35% growth in total energy for new workers and production. Electricity generated by nuclear or coal can make US production more cost-competitive, and it can power mass-transit systems, electric heat pumps, and communications and information systems. Changes in electricity and gross national product (GNP) have been more closely in step since 1973 than have total energy and GNP. The nuclear power units now under construction will add 80,000 megawatts to the 56,000 now on line. It is important to note that, while utilities are cancelling plans for nuclear plants, they aren't ordering new coal plants, which shows the impact of the high cost of money. Interest rates must come down and public-relations efforts to sell electricity must improve to change the situation. Although capital shortages are real, waste disposal is a problem of perception that was politically induced because the government failed to provide a demonstration of safety as the French are doing. Streamlined regulatory and insurance procedures can help to justify optimism in the nuclear option. 4 figures

  10. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  11. Primitive recursive realizability and basic propositional logic

    NARCIS (Netherlands)

    Plisko, Valery

    2007-01-01

    Two notions of primitive recursive realizability for arithmetic sentences are considered. The first one is strictly primitive recursive realizability introduced by Z. Damnjanovic in 1994. We prove that intuitionistic predicate logic is not sound with this kind of realizability. Namely there

  12. Adaptively smoothed seismicity earthquake forecasts for Italy

    Directory of Open Access Journals (Sweden)

    Yan Y. Kagan

    2010-11-01

    Full Text Available We present a model for estimation of the probabilities of future earthquakes of magnitudes m ≥ 4.95 in Italy. This model is a modified version of that proposed for California, USA, by Helmstetter et al. [2007] and Werner et al. [2010a], and it approximates seismicity using a spatially heterogeneous, temporally homogeneous Poisson point process. The temporal, spatial and magnitude dimensions are entirely decoupled. Magnitudes are independently and identically distributed according to a tapered Gutenberg-Richter magnitude distribution. We have estimated the spatial distribution of future seismicity by smoothing the locations of past earthquakes listed in two Italian catalogs: a short instrumental catalog, and a longer instrumental and historic catalog. The bandwidth of the adaptive spatial kernel is estimated by optimizing the predictive power of the kernel estimate of the spatial earthquake density in retrospective forecasts. When available and reliable, we used small earthquakes of m ≥ 2.95 to reveal active fault structures and 29 probable future epicenters. By calibrating the model with these two catalogs of different durations to create two forecasts, we intend to quantify the loss (or gain of predictability incurred when only a short, but recent, data record is available. Both forecasts were scaled to five and ten years, and have been submitted to the Italian prospective forecasting experiment of the global Collaboratory for the Study of Earthquake Predictability (CSEP. An earlier forecast from the model was submitted by Helmstetter et al. [2007] to the Regional Earthquake Likelihood Model (RELM experiment in California, and with more than half of the five-year experimental period over, the forecast has performed better than the others.

  13. Forecasting Long-Run Electricity Prices

    International Nuclear Information System (INIS)

    Hamm, Gregory; Borison, Adam

    2006-01-01

    Estimation of long-run electricity prices is extremely important but it is also very difficult because of the many uncertainties that will determine future prices, and because of the lack of sufficient historical and forwards data. The difficulty is compounded when forecasters ignore part of the available information or unnecessarily limit their thinking about the future. The authors present a practical approach that addresses these problems. (author)

  14. Artificial Intelligence as a Business Forecasting and Error Handling Tool

    OpenAIRE

    Md. Tabrez Quasim; Rupak Chattopadhyay

    2015-01-01

     Any business enterprise must rely a lot on how well it can predict the future happenings. To cope up with the modern global customer demand, technological challenges, market competitions etc., any organization is compelled to foresee the future having maximum impact and least chances of errors. The traditional forecasting approaches have some limitations. That is why the business world is adopting the modern Artificial Intelligence based forecasting techniques. This paper has tried to presen...

  15. Effective Heuristics for Capacitated Production Planning with Multiperiod Production and Demand with Forecast Band Refinement

    OpenAIRE

    Philip Kaminsky; Jayashankar M. Swaminathan

    2004-01-01

    In this paper we extend forecast band evolution and capacitated production modelling to the multiperiod demand case. In this model, forecasts of discrete demand for any period are modelled as bands and defined by lower and upper bounds on demand, such that future forecasts lie within the current band. We develop heuristics that utilize knowledge of demand forecast evolution to make production decisions in capacitated production planning environments. In our computational study we explore the ...

  16. Application of Quantitative Models, MNLR and ANN in Short Term Forecasting of Ship Data

    OpenAIRE

    P.Oliver Jayaprakash; K. Gunasekaran

    2011-01-01

    Forecasting has been the trouble-free way for the port authorities to derive the future expected values of service time of Bulk cargo ships handled at ports of South India. The short term forecasting could be an effective tool for estimating the resource requirements of recurring ships of similar tonnage and Cargo. Forecasting the arrival data related to port based ship operations customarily done using the standard algorithms and assumptions. The regular forecasting methods were decompositio...

  17. About the National Forecast Chart

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. The National Forecast Charts

  18. Marine Point Forecasts

    Science.gov (United States)

    will link to the zone forecast and then allow further zooming to the point of interest whereas on the Honolulu, HI Chicago, IL Northern Indiana, IN Lake Charles, LA New Orleans, LA Boston, MA Caribou, ME

  19. Socioeconomic Forecasting : [Technical Summary

    Science.gov (United States)

    2012-01-01

    Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

  20. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  1. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

    McManamon, A. [Bonneville Power Administration, Portland, OR (United States)

    2007-07-01

    The Columbia River Power System operates with consideration for flood control, endangered species, navigation, irrigation, water supply, recreation, other fish and wildlife concerns and power production. The Bonneville Power Association (BPA) located in Portland, Oregon is responsible for 35-40 per cent of the power consumed within the region. This presentation discussed inflow power concerns at BPA. The presentation illustrated elevational relief of projects; annual and daily variability; the hydrologic cycle; national river service weather forecasting service (NRSWFS); components of NRSWFS; and hydrologic forecast locations. Project operations and inventory were included along with a comparison of the 71-year average unregulated flow with regulated flow at the Dalles. Consistency between short-term and long-term forecasts and long-term streamflow forecasts were also illustrated in graphical format. The presentation also discussed the issue of reducing model and parameter uncertainty; reducing initial conditions uncertainty; snow updating; and reducing meteorological uncertainty. tabs., figs.

  2. CCAA seasonal forecasting

    International Development Research Centre (IDRC) Digital Library (Canada)

    Integrating meteorological and indigenous knowledge-based seasonal climate forecasts in ..... Explanation is based on spiritual and social values. Taught by .... that provided medicine and food became the subject of strict rules and practices ...

  3. Forecast Icing Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Forecast Icing Product (FIP) is an automatically-generated index suitable for depicting areas of potentially hazardous airframe icing. The FIP algorithm uses...

  4. Classical realizability in the CPS target language

    DEFF Research Database (Denmark)

    Frey, Jonas

    2016-01-01

    Motivated by considerations about Krivine's classical realizability, we introduce a term calculus for an intuitionistic logic with record types, which we call the CPS target language. We give a reformulation of the constructions of classical realizability in this language, using the categorical...... techniques of realizability triposes and toposes. We argue that the presentation of classical realizability in the CPS target language simplifies calculations in realizability toposes, in particular it admits a nice presentation of conjunction as intersection type which is inspired by Girard's ludics....

  5. Explicit field realizations of W algebras

    International Nuclear Information System (INIS)

    Wei Shaowen; Liu Yuxiao; Ren Jirong; Zhang Lijie

    2009-01-01

    The fact that certain nonlinear W 2,s algebras can be linearized by the inclusion of a spin-1 current can provide a simple way to realize W 2,s algebras from linear W 1,2,s algebras. In this paper, we first construct the explicit field realizations of linear W 1,2,s algebras with double scalar and double spinor, respectively. Then, after a change of basis, the realizations of W 2,s algebras are presented. The results show that all these realizations are Romans-type realizations.

  6. Explicit field realizations of W algebras

    OpenAIRE

    Wei, Shao-Wen; Liu, Yu-Xiao; Zhang, Li-Jie; Ren, Ji-Rong

    2009-01-01

    The fact that certain non-linear $W_{2,s}$ algebras can be linearized by the inclusion of a spin-1 current can provide a simple way to realize $W_{2,s}$ algebras from linear $W_{1,2,s}$ algebras. In this paper, we first construct the explicit field realizations of linear $W_{1,2,s}$ algebras with double-scalar and double-spinor, respectively. Then, after a change of basis, the realizations of $W_{2,s}$ algebras are presented. The results show that all these realizations are Romans-type realiz...

  7. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

    2003-01-01

    Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

  8. Conditional probabilistic population forecasting

    OpenAIRE

    Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

    2003-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

  9. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

    2004-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

  10. EU pharmaceutical expenditure forecast

    OpenAIRE

    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’ ph...

  11. Leverage effect, economic policy uncertainty and realized volatility with regime switching

    Science.gov (United States)

    Duan, Yinying; Chen, Wang; Zeng, Qing; Liu, Zhicao

    2018-03-01

    In this study, we first investigate the impacts of leverage effect and economic policy uncertainty (EPU) on future volatility in the framework of regime switching. Out-of-sample results show that the HAR-RV including the leverage effect and economic policy uncertainty with regimes can achieve higher forecast accuracy than RV-type and GARCH-class models. Our robustness results further imply that these factors in the framework of regime switching can substantially improve the HAR-RV's forecast performance.

  12. Organic photovoltaics concepts and realization

    CERN Document Server

    Dyakonov, Vladimir; Parisi, Jürgen; Sariciftci, Niyazi

    2003-01-01

    Achieving efficient solar energy conversion at both large scale and low cost is among the most important technological challenges for the near future. The present volume describes and explains the fundamentals of organic/plastic solar cells in a manner accessible to both researchers and students. It provides a comprehensive analysis of the operational principles underlying several types of solar cells that have absorber layers based on polymer materials and small molecules. It addresses competing approaches, such as polymer solar cells and dye-sensitized cells, while considering the thermodynamic principles within the context of these schemes. Organic Photovoltaics also analyzes in detail the charge-transfer processes in the bulk-heterojunction devices corresponding to the relevant mechanism of carrier generation. Emphasized throughout is the concept of interpenetrating polymer-fullerene networks, due to their high potential for improving power efficiency.

  13. FORECASTING OF PERFORMANCE EVALUATION OF NEW VEHICLES

    Directory of Open Access Journals (Sweden)

    O. S. Krasheninin

    2016-12-01

    Full Text Available Purpose. The research work focuses on forecasting of performance evaluation of the tractive and non-tractive vehicles that will satisfy and meet the needs and requirements of the railway industry, which is constantly evolving. Methodology. Analysis of the technical condition of the existing fleet of rolling stock (tractive and non-tractive of Ukrainian Railways shows a substantial reduction that occurs in connection with its moral and physical wear and tear, as well as insufficient and limited purchase of new units of the tractive and non-tractive rolling stock in the desired quantity. In this situation there is a necessity of search of the methods for determination of rolling stock technical characteristics. One of such urgent and effective measures is to conduct forecasting of the defining characteristics of the vehicles based on the processes of their reproduction in conditions of limited resources using a continuous exponential function. The function of the growth rate of the projected figure degree for the vehicle determines the logistic characteristic that with unlimited resources has the form of an exponent, and with low ones – that of a line. Findings. The data obtained according to the proposed method allowed determining the expected (future value, that is the ratio of load to volume of the body for non-tractive rolling stock (gondola cars and weight-to-power for tractive rolling stock, the degree of forecast reliability and the standard forecast error, which show high prediction accuracy for the completed procedure. As a result, this will allow estimating the required characteristics of vehicles in the forecast year with high accuracy. Originality. The concept of forecasting the characteristics of the vehicles for decision-making on the evaluation of their prospects was proposed. Practical value. The forecasting methodology will reliably determine the technical parameters of tractive and non-tractive rolling stock, which will meet

  14. Iterative near-term ecological forecasting: Needs, opportunities, and challenges.

    Science.gov (United States)

    Dietze, Michael C; Fox, Andrew; Beck-Johnson, Lindsay M; Betancourt, Julio L; Hooten, Mevin B; Jarnevich, Catherine S; Keitt, Timothy H; Kenney, Melissa A; Laney, Christine M; Larsen, Laurel G; Loescher, Henry W; Lunch, Claire K; Pijanowski, Bryan C; Randerson, James T; Read, Emily K; Tredennick, Andrew T; Vargas, Rodrigo; Weathers, Kathleen C; White, Ethan P

    2018-02-13

    Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

  15. Coal production forecast and low carbon policies in China

    International Nuclear Information System (INIS)

    Wang Jianzhou; Dong Yao; Wu Jie; Mu Ren; Jiang He

    2011-01-01

    With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production. - Highlights: → Improved forecasting models make full use of the advantages of individual model. → Proposed models create commendable improvements for current research. → Proposed models do not make complicated decisions about the explicit form. → We forecast coal production of China from 2011 to 2015. → We suggest some policies for reducing carbon emissions.

  16. Coal production forecast and low carbon policies in China

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jianzhou [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Dong Yao, E-mail: dongyao20051987@yahoo.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Wu Jie; Mu Ren; Jiang He [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China)

    2011-10-15

    With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production. - Highlights: > Improved forecasting models make full use of the advantages of individual model. > Proposed models create commendable improvements for current research. > Proposed models do not make complicated decisions about the explicit form. > We forecast coal production of China from 2011 to 2015. > We suggest some policies for reducing carbon emissions.

  17. Device for forecasting reactor power-up routes

    International Nuclear Information System (INIS)

    Fukuzaki, Takaharu.

    1980-01-01

    Purpose: To improve the reliability and forecasting accuracy for a device forecasting the change of the state on line in BWR type reactors. Constitution: The present state in a nuclear reactor is estimated in a present state judging section based on measuring signals for thermal power, core flow rate, control rod density and the like from the nuclear reactor, and the estimated results are accumulated in an operation result collecting section. While on the other hand, a forecasting section forecasts the future state in the reactor based on the signals from the forecasting condition setting section. The actual result values from the collecting section and the forecasting results are compared to each other. If they are not equal, new setting signals are outputted from the setting section to perform the forecasting again. These procedures are repeated till the difference between the forecast results and the actual result values is minimized, by which accurate forecasting for the state of the reactor is made possible. (Furukawa, Y.)

  18. Forecasting biodiversity in breeding birds using best practices

    Directory of Open Access Journals (Sweden)

    David J. Harris

    2018-02-01

    Full Text Available Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and “naive” forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the “naive” model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

  19. Forecasting biodiversity in breeding birds using best practices

    Science.gov (United States)

    Taylor, Shawn D.; White, Ethan P.

    2018-01-01

    Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and “naive” forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the “naive” model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods. PMID:29441230

  20. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

    Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  1. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    2003-01-01

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  2. Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

    Science.gov (United States)

    O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

    2015-04-01

    Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

  3. (Some) Computer Futures: Mainframes.

    Science.gov (United States)

    Joseph, Earl C.

    Possible futures for the world of mainframe computers can be forecast through studies identifying forces of change and their impact on current trends. Some new prospects for the future have been generated by advances in information technology; for example, recent United States successes in applied artificial intelligence (AI) have created new…

  4. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

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

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  5. Realizing "value-added" metrology

    Science.gov (United States)

    Bunday, Benjamin; Lipscomb, Pete; Allgair, John; Patel, Dilip; Caldwell, Mark; Solecky, Eric; Archie, Chas; Morningstar, Jennifer; Rice, Bryan J.; Singh, Bhanwar; Cain, Jason; Emami, Iraj; Banke, Bill, Jr.; Herrera, Alfredo; Ukraintsev, Vladamir; Schlessinger, Jerry; Ritchison, Jeff

    2007-03-01

    The conventional premise that metrology is a "non-value-added necessary evil" is a misleading and dangerous assertion, which must be viewed as obsolete thinking. Many metrology applications are key enablers to traditionally labeled "value-added" processing steps in lithography and etch, such that they can be considered integral parts of the processes. Various key trends in modern, state-of-the-art processing such as optical proximity correction (OPC), design for manufacturability (DFM), and advanced process control (APC) are based, at their hearts, on the assumption of fine-tuned metrology, in terms of uncertainty and accuracy. These trends are vehicles where metrology thus has large opportunities to create value through the engineering of tight and targetable process distributions. Such distributions make possible predictability in speed-sorts and in other parameters, which results in high-end product. Additionally, significant reliance has also been placed on defect metrology to predict, improve, and reduce yield variability. The necessary quality metrology is strongly influenced by not only the choice of equipment, but also the quality application of these tools in a production environment. The ultimate value added by metrology is a result of quality tools run by a quality metrology team using quality practices. This paper will explore the relationships among present and future trends and challenges in metrology, including equipment, key applications, and metrology deployment in the manufacturing flow. Of key importance are metrology personnel, with their expertise, practices, and metrics in achieving and maintaining the required level of metrology performance, including where precision, matching, and accuracy fit into these considerations. The value of metrology will be demonstrated to have shifted to "key enabler of large revenues," debunking the out-of-date premise that metrology is "non-value-added." Examples used will be from critical dimension (CD

  6. Athabasca, Cold Lake and the future

    International Nuclear Information System (INIS)

    McFarland, J.D.

    1993-01-01

    It is suggested that Alberta oil sands have the potential to sustain and increase the wealth creation capacity of the Canadian petroleum sector now and well into the next century. Realizing this potential in the present-day competitive and interconnected world crude oil market is a challenge to be addressed in four areas: markets, operations, technology, and stakeholder support. Real price improvement in the world oil market is not expected in the near future, given near-static demand and a continuously increasing worldwide supply potential. Even in such a market, there are specialized niches where Canadian heavy oil should be competitive. These markets are continental and are mainly high- and medium-conversion refineries and upgraders. Demand for Canadian heavy oil is forecast to grow ca 4%/y to over 800,000 bbl/d by 2000. Supply will closely track demand 1995-98 and be slightly below demand before 1995 and after 1998. Improvements in existing operations to lower production costs and increase efficiency are being made at the Cold Lake and Syncrude facilities. The development of technology to improve recovery and lower supply costs will trigger further development, and impressive gains have already been realized as a result from ongoing research. The final condition needed to allow the oil sand sector to realize its potential is informed and supportive stakeholders (investors, customers, governments, and communities), who need to understand the unique attributes and potential awards of the oil sand business. 6 figs

  7. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  8. Forecasting world natural gas supply

    International Nuclear Information System (INIS)

    Al-Fattah, S. M.; Startzman, R. A.

    2000-01-01

    Using the multi-cyclic Hubert approach, a 53 country-specific gas supply model was developed which enables production forecasts for virtually all of the world's gas. Supply models for some organizations such as OPEC, non-OPEC and OECD were also developed and analyzed. Results of the modeling study indicate that the world's supply of natural gas will peak in 2014, followed by an annual decline at the rate of one per cent per year. North American gas production is reported to be currently at its peak with 29 Tcf/yr; Western Europe will reach its peak supply in 2002 with 12 Tcf. According to this forecast the main sources of natural gas supply in the future will be the countries of the former Soviet Union and the Middle East. Between them, they possess about 62 per cent of the world's ultimate recoverable natural gas (4,880 Tcf). It should be noted that these estimates do not include unconventional gas resulting from tight gas reservoirs, coalbed methane, gas shales and gas hydrates. These unconventional sources will undoubtedly play an important role in the gas supply in countries such as the United States and Canada. 18 refs., 2 tabs., 18 figs

  9. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    . The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  10. Wind power forecast

    Energy Technology Data Exchange (ETDEWEB)

    Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

    2012-07-01

    Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

  11. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  12. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  13. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  14. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  15. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  16. Forecasting Spanish natural life expectancy.

    Science.gov (United States)

    Guillen, Montserrat; Vidiella-i-Anguera, Antoni

    2005-10-01

    Knowledge of trends in life expectancy is of major importance for policy planning. It is also a key indicator for assessing future development of life insurance products, substantiality of existing retirement schemes, and long-term care for the elderly. This article examines the feasibility of decomposing age-gender-specific accidental and natural mortality rates. We study this decomposition by using the Lee and Carter model. In particular, we fit the Poisson log-bilinear version of this model proposed by Wilmoth and Brouhns et al. to historical (1975-1998) Spanish mortality rates. In addition, by using the model introduced by Wilmoth and Valkonen we analyze mortality-gender differentials for accidental and natural rates. We present aggregated life expectancy forecasts compared with those constructed using nondecomposed mortality rates.

  17. Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

    Science.gov (United States)

    Storer, Luke N.; Williams, Paul D.; Gill, Philip G.

    2018-03-01

    Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviation-affecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed—ideally in collaboration with the aviation industry—to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future.

  18. Forecasting urban water demand: A meta-regression analysis.

    Science.gov (United States)

    Sebri, Maamar

    2016-12-01

    Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

  19. An Electrical Energy Consumption Monitoring and Forecasting System

    Directory of Open Access Journals (Sweden)

    J. L. Rojas-Renteria

    2016-10-01

    Full Text Available Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.

  20. Scenarios for energy forecasting: papers of the symposium

    International Nuclear Information System (INIS)

    1987-01-01

    Energy planning is important for every developed country and therefore also for South Africa. However, during 1984 it was felt by interested parties that the work in this field should be coordinated through mutual discussion. With this in mind a 'Task Team for Energy Forecasting' was formed with the task to generate acceptable forecasts of the energy set-up in South Africa. Knowledge of the relationship between energy and variables such as the economy and the population is necessary to the Task Team. However, the Task Team also needs some insight into the future paths of such variables if it has to generate energy forecasts. It is the purpose of this symposium to improve this insight through having experts in all relevant fields to set out and develop their possible future scenarios independently of energy forecasting