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

Forecasting Interest Rates and Inflation

DEFF Research Database (Denmark)

Chun, Albert Lee

the best overall for short horizon forecasts of short to medium term yields and inflation. Econometric models with shrinkage perform the best over longer horizons and maturities. Aggregating over a larger set of analysts improves inflation surveys while generally degrading interest rates surveys. We...

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

Interval Forecast for Smooth Transition Autoregressive Model ...

African Journals Online (AJOL)

In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...

Forecasting space weather: Can new econometric methods improve accuracy?

Science.gov (United States)

Reikard, Gordon

2011-06-01

Space weather forecasts are currently used in areas ranging from navigation and communication to electric power system operations. The relevant forecast horizons can range from as little as 24 h to several days. This paper analyzes the predictability of two major space weather measures using new time series methods, many of them derived from econometrics. The data sets are the A p geomagnetic index and the solar radio flux at 10.7 cm. The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques. While combined models are complex, they can be programmed using modern statistical software. The data frequency is daily, and forecasting experiments are run over horizons ranging from 1 to 7 days. Two major conclusions stand out. First, the frequency domain method forecasts the A p index more accurately than any time domain model, including both regressions and neural networks. This finding is very robust, and holds for all forecast horizons. Combining the frequency domain method with other techniques yields a further small improvement in accuracy. Second, the neural network forecasts the solar flux more accurately than any other method, although at short horizons (2 days or less) the regression and net yield similar results. The neural net does best when it includes measures of the long-term component in the data.

Forecasting electricity market pricing using artificial neural networks

International Nuclear Information System (INIS)

Pao, Hsiao-Tien

2007-01-01

Electricity price forecasting is extremely important for all market players, in particular for generating companies: in the short term, they must set up bids for the spot market; in the medium term, they have to define contract policies; and in the long term, they must define their expansion plans. For forecasting long-term electricity market pricing, in order to avoid excessive round-off and prediction errors, this paper proposes a new artificial neural network (ANN) with single output node structure by using direct forecasting approach. The potentials of ANNs are investigated by employing a rolling cross validation scheme. Out of sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are a more robust multi-step ahead forecasting method than autoregressive error models. Moreover, ANN predictions are quite accurate even when the length of the forecast horizon is relatively short or long

41 CFR 101-39.106 - Unlimited exemptions.

Science.gov (United States)

2010-07-01

...-INTERAGENCY FLEET MANAGEMENT SYSTEMS 39.1-Establishment, Modification, and Discontinuance of Interagency Fleet Management Systems § 101-39.106 Unlimited exemptions. Unlimited exemptions from inclusion in the fleet... below. Unlimited exemptions do not preclude agencies from requesting fleet management services, if...

Solar Particle Radiation Storms Forecasting and Analysis within the Framework of the `HESPERIA' HORIZON 2020 Project

Science.gov (United States)

Posner, A.; Malandraki, O.; Nunez, M.; Heber, B.; Labrenz, J.; Kühl, P.; Milas, N.; Tsiropoula, G.; Pavlos, E.

2017-12-01

Two prediction tools that have been developed in the framework of HESPERIA based upon the proven concepts UMASEP and REleASE. Near-relativistic (NR) electrons traveling faster than ions (30 MeV protons have 0.25c) are used to forecast the arrival of protons of Solar Energetic Particle (SEP) events with real-time measurements of NR electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. REleASE (Relativistic Electron Alert System for Exploration, Posner, 2007) uses this effect to predict the proton flux by utilizing actual electron fluxes and their most recent increases. Through HESPERIA, a clone of REleASE was built in open source programming language. The same forecasting principle was adapted to real-time data from ACE/EPAM. It is shown that HESPERIA REleASE forecasting works with any NR electron flux measurements. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing Ground Level Enhancement (GLE) events. Within HESPERIA, a predictor of >500 SEP proton events near earth (geostationary orbit) has been developed. In order to predict these events, UMASEP (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux near earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then UMASEP issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called HESPERIA UMASEP-500, correlates X-ray flux with differential proton fluxes by GOES, and with fluxes collected by neutron monitor stations around the world. When the correlation estimation and flare surpasses thresholds, a >500 MeV SEP forecast is issued. These findings suggest that a synthesis of the various approaches may improve over the status quo. Both forecasting tools are

Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

Science.gov (United States)

Zaron, Edward D.; Fitzpatrick, Patrick J.; Cross, Scott L.; Harding, John M.; Bub, Frank L.; Wiggert, Jerry D.; Ko, Dong S.; Lau, Yee; Woodard, Katharine; Mooers, Christopher N. K.

2015-12-01

In response to the Deepwater Horizon (DwH) oil spill event in 2010, the Naval Oceanographic Office deployed a nowcast-forecast system covering the Gulf of Mexico and adjacent Caribbean Sea that was designated Americas Seas, or AMSEAS, which is documented in this manuscript. The DwH disaster provided a challenge to the application of available ocean-forecast capabilities, and also generated a historically large observational dataset. AMSEAS was evaluated by four complementary efforts, each with somewhat different aims and approaches: a university research consortium within an Integrated Ocean Observing System (IOOS) testbed; a petroleum industry consortium, the Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project (GOMEX-PPP); a British Petroleum (BP) funded project at the Northern Gulf Institute in response to the oil spill; and the Navy itself. Validation metrics are presented in these different projects for water temperature and salinity profiles, sea surface wind, sea surface temperature, sea surface height, and volume transport, for different forecast time scales. The validation found certain geographic and time biases/errors, and small but systematic improvements relative to earlier regional and global modeling efforts. On the basis of these positive AMSEAS validation studies, an oil spill transport simulation was conducted using archived AMSEAS nowcasts to examine transport into the estuaries east of the Mississippi River. This effort captured the influences of Hurricane Alex and a non-tropical cyclone off the Louisiana coast, both of which pushed oil into the western Mississippi Sound, illustrating the importance of the atmospheric influence on oil spills such as DwH.

AN EVALUATION OF POINT AND DENSITY FORECASTS FOR SELECTED EU FARM GATE MILK PRICES

Directory of Open Access Journals (Sweden)

Dennis Bergmann

2018-01-01

Full Text Available Fundamental changes to the common agricultural policy (CAP have led to greater market orientation which in turn has resulted in sharply increased variability of EU farm gate milk prices and thus farmers’ income. In this market environment reliable forecasts of farm gate milk prices are extremely important as farmers can make improved decisions with regards to cash flow management and budget preparation. In addition these forecasts may be used in setting fixed priced contracts between dairy farmers and processors thus providing certainty and reducing risk. In this study both point and density forecasts from various time series models for farm gate milk prices in Germany, Ireland and for an average EU price series are evaluated using a rolling window framework. Additionally forecasts of the individual models are combined using different combination schemes. The results of the out of sample evaluation show that ARIMA type models perform well on short forecast horizons (1 to 3 month while the structural time series approach performs well on longer forecast horizons (12 month. Finally combining individual forecasts of different models significantly improves the forecast performance for all forecast horizons.

Forecasting daily political opinion polls using the fractionally cointegrated VAR model

DEFF Research Database (Denmark)

Nielsen, Morten Ørregaard; Shibaev, Sergei S.

We examine forecasting performance of the recent fractionally cointegrated vector autoregressive (FCVAR) model. We use daily polling data of political support in the United Kingdom for 2010-2015 and compare with popular competing models at several forecast horizons. Our findings show that the four...... trend from the model follows the vote share of the UKIP very closely, and we thus interpret it as a measure of Euro-skepticism in public opinion rather than an indicator of the more traditional left-right political spectrum. In terms of prediction of vote shares in the election, forecasts generated...... variants of the FCVAR model considered are generally ranked as the top four models in terms of forecast accuracy, and the FCVAR model significantly outperforms both univariate fractional models and the standard cointegrated VAR (CVAR) model at all forecast horizons. The relative forecast improvement...

47 CFR 73.1710 - Unlimited time.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 4 2010-10-01 2010-10-01 false Unlimited time. 73.1710 Section 73.1710 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Rules Applicable to All Broadcast Stations § 73.1710 Unlimited time. Operation is permitted 24 hours a...

Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data

Science.gov (United States)

Fantazzini, Dean

2014-01-01

We propose the use of Google online search data for nowcasting and forecasting the number of food stamps recipients. We perform a large out-of-sample forecasting exercise with almost 3000 competing models with forecast horizons up to 2 years ahead, and we show that models including Google search data statistically outperform the competing models at all considered horizons. These results hold also with several robustness checks, considering alternative keywords, a falsification test, different out-of-samples, directional accuracy and forecasts at the state-level. PMID:25369315

Precipitable water vapour forecasting: a tool for optimizing IR observations at Roque de los Muchachos Observatory.

Science.gov (United States)

Pérez-Jordán, G.; Castro-Almazán, J. A.; Muñoz-Tuñón, C.

2018-04-01

We validate the Weather Research and Forecasting (WRF) model for precipitable water vapour (PWV) forecasting as a fully operational tool for optimizing astronomical infrared (IR) observations at Roque de los Muchachos Observatory (ORM). For the model validation we used GNSS-based (Global Navigation Satellite System) data from the PWV monitor located at the ORM. We have run WRF every 24 h for near two months, with a horizon of 48 hours (hourly forecasts), from 2016 January 11 to 2016 March 4. These runs represent 1296 hourly forecast points. The validation is carried out using different approaches: performance as a function of the forecast range, time horizon accuracy, performance as a function of the PWV value, and performance of the operational WRF time series with 24- and 48-hour horizons. Excellent agreement was found between the model forecasts and observations, with R =0.951 and R =0.904 for the 24- and 48-h forecast time series respectively. The 48-h forecast was further improved by correcting a time lag of 2 h found in the predictions. The final errors, taking into account all the uncertainties involved, are 1.75 mm for the 24-h forecasts and 1.99 mm for 48 h. We found linear trends in both the correlation and RMSE of the residuals (measurements - forecasts) as a function of the forecast range within the horizons analysed (up to 48 h). In summary, the WRF performance is excellent and accurate, thus allowing it to be implemented as an operational tool at the ORM.

Evolutionary Forecast Engines for Solar Meteorology

Science.gov (United States)

Coimbra, C. F.

2012-12-01

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

Isolated Horizon, Killing Horizon and Event Horizon

OpenAIRE

Date, G.

2001-01-01

We consider space-times which in addition to admitting an isolated horizon also admit Killing horizons with or without an event horizon. We show that an isolated horizon is a Killing horizon provided either (1) it admits a stationary neighbourhood or (2) it admits a neighbourhood with two independent, commuting Killing vectors. A Killing horizon is always an isolated horizon. For the case when an event horizon is definable, all conceivable relative locations of isolated horizon and event hori...

Filters or Holt Winters Technique to Improve the SPF Forecasts for USA Inflation Rate?

Directory of Open Access Journals (Sweden)

Mihaela Bratu (Simionescu

2013-02-01

Full Text Available In this study, transformations of SPF inflation forecasts were made in order to get moreaccurate predictions. The filters application and Holt Winters technique were chosen as possiblestrategies of improving the predictions accuracy. The quarterly inflation rate forecasts (1975 Q1-2012Q3 of USAmade by SPF were transformed using an exponential smoothing technique-HoltWinters-and these new predictions are better than the initial ones for all forecasting horizons of 4quarters. Some filters were applied to SPF forecasts (Hodrick-Prescott,Band-Pass and Christiano-Fitzegerald filters, but Holt Winters method was superior.Full sample asymmetric (Christiano-Fitzegerald and Band-Pass filtersmoothed values are more accurate than the SPF expectations onlyfor some forecast horizons.

A New Approach to Forecasting Exchange Rates

OpenAIRE

Kenneth W Clements; Yihui Lan

2006-01-01

Building on purchasing power parity theory, this paper proposes a new approach to forecasting exchange rates using the Big Mac data from The Economist magazine. Our approach is attractive in three aspects. Firstly, it uses easily-available Big Mac prices as input. These prices avoid several serious problems associated with broad price indexes, such as the CPI, that are used in conventional PPP studies. Secondly, this approach provides real-time exchange-rate forecasts at any forecast horizon....

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

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.

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....

Forecasting Value-at-Risk Under Temporal and Portfolio Aggregation

NARCIS (Netherlands)

H.J.W.G. Kole (Erik); T.D. Markwat (Thijs); A. Opschoor (Anne); D.J.C. van Dijk (Dick)

2016-01-01

textabstractWe examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of ten trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly or

41 CFR 109-39.106 - Unlimited exemptions.

Science.gov (United States)

2010-07-01

..., AND MOTOR VEHICLES 39-INTERAGENCY FLEET MANAGEMENT SYSTEMS 39.1-Establishment, Modification, and Discontinuance of Interagency Fleet Management Systems § 109-39.106 Unlimited exemptions. The Director, Office of... determination that an unlimited exemption from inclusion of a motor vehicle in a fleet management system is...

Probabilistic Forecasting for On-line Operation of Urban Drainage Systems

DEFF Research Database (Denmark)

Löwe, Roland

This thesis deals with the generation of probabilistic forecasts in urban hydrology. In particular, we focus on the case of runoff forecasting for real-time control (RTC) on horizons of up to two hours. For the generation of probabilistic on-line runoff forecasts, we apply the stochastic grey...... and forecasts have on on-line runoff forecast quality. Finally, we implement the stochastic grey-box model approach in a real-world real-time control (RTC) setup and study how RTC can benefit from a dynamic quantification of runoff forecast uncertainty....

Verification of short lead time forecast models: applied to Kp and Dst forecasting

Science.gov (United States)

Wintoft, Peter; Wik, Magnus

2016-04-01

In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

Multi-site solar power forecasting using gradient boosted regression trees

DEFF Research Database (Denmark)

Persson, Caroline Stougård; Bacher, Peder; Shiga, Takahiro

2017-01-01

The challenges to optimally utilize weather dependent renewable energy sources call for powerful tools for forecasting. This paper presents a non-parametric machine learning approach used for multi-site prediction of solar power generation on a forecast horizon of one to six hours. Historical pow...

MOTIVATIONAL LEXICON IN ANTHONY ROBBINS’ UNLIMITED POWER

Directory of Open Access Journals (Sweden)

Nur Faidatun Naimah

2016-12-01

Full Text Available In the language learning process, motivation, one of psychological factors, has a great role in endorsing students to be a successful learner. Based on the issues, the choice of words that can influence the students to do the best is practically required by the teachers. So that, teacher as a motivator has a power to influence the students to take action for achieving their excellent learning, using what Anthony Robbins suggest on his book; Unlimited Power. The writer formulated the aims of this study as follow; (1 to identify the motivational lexicons in Unlimited Power from the psychological perspective, and (2 to describe how motivational lexicons in Unlimited Power take apart in the pedagogical field. This research used qualitative research to find out the data. The data analysis technique that researcher used is content analysis since they were texts in Unlimited Power. Researcher found three motivational lexicons used by Anthony Robbins in his book Unlimited Power; think, challenge, and remember. Think used as a tool to lead his readers to come to their memory, re-identify some main points, and consider about the certain thing. Challenge used to pump readers’ emotion, gave a test, and invited them to take action. Remember used as a tool to bring back a piece of information he provided before and try to keep it in readers’ mind. Anthony’s motivational lexicons in Unlimited Power also can use in the pedagogical field. Teacher can use them in the teaching-learning process as it determines the effectiveness of rewards for what students do and apparently influential factor for learning process.

Motivational Lexicon in Anthony Robbins’ Unlimited Power

Directory of Open Access Journals (Sweden)

Nur Faidatun Naimah

2016-12-01

Full Text Available In the language learning process, motivation, one of psychological factors, has a great role in endorsing students to be a successful learner. Based on the issues, the choice of words that can influence the students to do the best is practically required by the teachers. So that, teacher as a motivator has a power to influence the students to take action for achieving their excellent learning, using what Anthony Robbins suggest on his book; Unlimited Power. The writer formulated the aims of this study as follow; (1 to identify the motivational lexicons in Unlimited Power from the psychological perspective, and (2 to describe how motivational lexicons in Unlimited Power take apart in the pedagogical field. This research used qualitative research to find out the data. The data analysis technique that researcher used is content analysis since they were texts in Unlimited Power. Researcher found three motivational lexicons used by Anthony Robbins in his book Unlimited Power; think, challenge, and remember. Think used as a tool to lead his readers to come to their memory, re-identify some main points, and consider about the certain thing. Challenge used to pump readers’ emotion, gave a test, and invited them to take action. Remember used as a tool to bring back a piece of information he provided before and try to keep it in readers’ mind. Anthony’s motivational lexicons in Unlimited Power also can use in the pedagogical field. Teacher can use them in the teaching-learning process as it determines the effectiveness of rewards for what students do and apparently influential factor for learning process.

Valuing hydrological forecasts for a pumped storage assisted hydro facility

Science.gov (United States)

Zhao, Guangzhi; Davison, Matt

2009-07-01

SummaryThis paper estimates the value of a perfectly accurate short-term hydrological forecast to the operator of a hydro electricity generating facility which can sell its power at time varying but predictable prices. The expected value of a less accurate forecast will be smaller. We assume a simple random model for water inflows and that the costs of operating the facility, including water charges, will be the same whether or not its operator has inflow forecasts. Thus, the improvement in value from better hydrological prediction results from the increased ability of the forecast using facility to sell its power at high prices. The value of the forecast is therefore the difference between the sales of a facility operated over some time horizon with a perfect forecast, and the sales of a similar facility operated over the same time horizon with similar water inflows which, though governed by the same random model, cannot be forecast. This paper shows that the value of the forecast is an increasing function of the inflow process variance and quantifies how much the value of this perfect forecast increases with the variance of the water inflow process. Because the lifetime of hydroelectric facilities is long, the small increase observed here can lead to an increase in the profitability of hydropower investments.

Using Quantile Regression to Extend an Existing Wind Power Forecasting System with Probabilistic Forecasts

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg; Madsen, Henrik; Nielsen, Torben Skov

2006-01-01

speed (due to the non-linearity of the power curve) and the forecast horizon. With respect to the predictability of the actual meteorological situation a number of explanatory variables are considered, some inspired by the literature. The article contains an overview of related work within the field...

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Science.gov (United States)

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Leveraging stochastic differential equations for probabilistic forecasting of wind power using a dynamic power curve

DEFF Research Database (Denmark)

Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg

2017-01-01

Short-term (hours to days) probabilistic forecasts of wind power generation provide useful information about the associated uncertainty of these forecasts. Standard probabilistic forecasts are usually issued on a per-horizon-basis, meaning that they lack information about the development of the u...

Out-of-sample Forecasting Performance of Won/Dollar Exchange Rate Return Volatility Model

Directory of Open Access Journals (Sweden)

Hojin Lee

2009-06-01

Full Text Available We compare the out-of-sample forecasting performance of volatility models using daily exchange rate for the KRW/USD during the period from 1992 to 2008. For various forecasting horizons, historical volatility models with a long memory tend to make more accurate forecasts. Especially, we carefully observe the difference between the EWMA and the GARCH(1,1 model. Our empirical finding that the GARCH model puts too much weight on recent observations relative to those in the past is consistent with prior evidence showing that asset market volatility has a long memory, such as Ding and Granger (1996. The forecasting model with the lowest MSFE and VaR forecast error among the models we consider is the EWMA model in which the forecast volatility for the coming period is a weighted average of recent squared return with exponentially declining weights. In terms of forecast accuracy, it clearly dominates the widely accepted GARCH and rolling window GARCH models. We also present a multiple comparison of the out-of-sample forecasting performance of volatility using the stationary bootstrap of Politis and Romano (1994. We find that the White's reality check for the GARCH(1,1 expanding window model and the FIGARCH(1,1 expanding window model clearly reject the null hypothesis and there exists a better model than the two benchmark models. On the other hand, when the EWMA model is the benchmark, the White's for all forecasting horizons are very high, which indicates the null hypothesis may not be rejected. The Hansen's report the same results. The GARCH(1,1 expanding window model and the FIGARCH(1,1 expanding window model are dominated by the best competing model in most of the forecasting horizons. In contrast, the RiskMetrics model seems to be the most preferred. We also consider combining the forecasts generated by averaging the six raw forecasts and a trimmed set of forecasts which calculate the mean of the four forecasts after disregarding the highest and

41 CFR 109-38.204-1 - Unlimited exemptions.

Science.gov (United States)

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Unlimited exemptions... Regulations System (Continued) DEPARTMENT OF ENERGY PROPERTY MANAGEMENT REGULATIONS AVIATION, TRANSPORTATION... § 109-38.204-1 Unlimited exemptions. (a)-(f) [Reserved] (g) The Director, Office of Administrative...

TradeWind Deliverable 2.2: Forecast error of aggregated wind power

DEFF Research Database (Denmark)

Giebel, Gregor; Sørensen, Poul Ejnar; Holttinen, Hannele

2007-01-01

Estimates of forecast error of aggregated production for time horizons of intraday and dayahead markets in future will be produced. This will be done by reference to published studies of forecasting for wind generation, and from internal knowledge of WP2 participants. Modelling of wind power fluctuations...

A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data

DEFF Research Database (Denmark)

Alessandrini, S.; Sperati, S.; Pinson, Pierre

2013-01-01

together with a single forecast power value for each future time horizon. A comparison between two different ensemble forecasting models, ECMWF EPS (Ensemble Prediction System in use at the European Centre for Medium-Range Weather Forecasts) and COSMO-LEPS (Limited-area Ensemble Prediction System developed...... ahead forecast horizon. A statistical calibration of the ensemble wind speed members based on the use of past wind speed measurements is explained. The two models are compared using common verification indices and diagrams. The higher horizontal resolution model (COSMO-LEPS) shows slightly better...

48 CFR 27.404-1 - Unlimited rights data.

Science.gov (United States)

2010-10-01

... data constitute minor modifications to data that are limited rights data or restricted computer... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Unlimited rights data. 27... CONTRACTING REQUIREMENTS PATENTS, DATA, AND COPYRIGHTS Rights in Data and Copyrights 27.404-1 Unlimited rights...

Statistical and Machine Learning forecasting methods: Concerns and ways forward

Science.gov (United States)

Makridakis, Spyros; Assimakopoulos, Vassilios

2018-01-01

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

Statistical and Machine Learning forecasting methods: Concerns and ways forward.

Science.gov (United States)

Makridakis, Spyros; Spiliotis, Evangelos; Assimakopoulos, Vassilios

2018-01-01

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.

Using ensemble forecasting for wind power

Energy Technology Data Exchange (ETDEWEB)

Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

2003-07-01

Short-term prediction of wind power has a long tradition in Denmark. It is an essential tool for the operators to keep the grid from becoming unstable in a region like Jutland, where more than 27% of the electricity consumption comes from wind power. This means that the minimum load is already lower than the maximum production from wind energy alone. Danish utilities have therefore used short-term prediction of wind energy since the mid-90ies. However, the accuracy is still far from being sufficient in the eyes of the utilities (used to have load forecasts accurate to within 5% on a one-week horizon). The Ensemble project tries to alleviate the dependency of the forecast quality on one model by using multiple models, and also will investigate the possibilities of using the model spread of multiple models or of dedicated ensemble runs for a prediction of the uncertainty of the forecast. Usually, short-term forecasting works (especially for the horizon beyond 6 hours) by gathering input from a Numerical Weather Prediction (NWP) model. This input data is used together with online data in statistical models (this is the case eg in Zephyr/WPPT) to yield the output of the wind farms or of a whole region for the next 48 hours (only limited by the NWP model horizon). For the accuracy of the final production forecast, the accuracy of the NWP prediction is paramount. While many efforts are underway to increase the accuracy of the NWP forecasts themselves (which ultimately are limited by the amount of computing power available, the lack of a tight observational network on the Atlantic and limited physics modelling), another approach is to use ensembles of different models or different model runs. This can be either an ensemble of different models output for the same area, using different data assimilation schemes and different model physics, or a dedicated ensemble run by a large institution, where the same model is run with slight variations in initial conditions and

Essays on forecasting stationary and nonstationary economic time series

Science.gov (United States)

Bachmeier, Lance Joseph

This dissertation consists of three essays. Chapter II considers the question of whether M2 growth can be used to forecast inflation at horizons of up to ten years. A vector error correction (VEC) model serves as our benchmark model. We find that M2 growth does have marginal predictive content for inflation at horizons of more than two years, but only when allowing for cointegration and when the cointegrating rank and vector are specified a priori. When estimating the cointegration vector or failing to impose cointegration, there is no longer evidence of causality running from M2 growth to inflation at any forecast horizon. Finally, we present evidence that M2 needs to be redefined, as forecasts of the VEC model using data on M2 observed after 1993 are worse than the forecasts of an autoregressive model of inflation. Chapter III reconsiders the evidence for a "rockets and feathers" effect in gasoline markets. We estimate an error correction model of gasoline prices using daily data for the period 1985--1998 and fail to find any evidence of asymmetry. We show that previous work suffered from two problems. First, nonstationarity in some of the regressors was ignored, leading to invalid inference. Second, the weekly data used in previous work leads to a temporal aggregation problem, and thus biased estimates of impulse response functions. Chapter IV tests for a forecasting relationship between the volume of litigation and macroeconomic variables. We analyze annual data for the period 1960--2000 on the number of cases filed, real GDP, real consumption expenditures, inflation, unemployment, and interest rates. Bivariate Granger causality tests show that several of the macroeconomic variables can be used to forecast the volume of litigation, but show no evidence that the volume of litigation can be used to forecast any of the macroeconomic variables. The analysis is then extended to bivariate and multivariate regression models, and we find similar evidence to that of the

New Technology Trends in Education: Seven Years of Forecasts and Convergence

Science.gov (United States)

Martin, Sergio; Diaz, Gabriel; Sancristobal, Elio; Gil, Rosario; Castro, Manuel; Peire, Juan

2011-01-01

Each year since 2004, a new Horizon Report has been released. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the mid-term (the next 2 years) and the long term (the next 4 years). This paper analyzes the evolution of technology trends…

Forecasting short-term wind farm production in complex terrain. Volume 1

International Nuclear Information System (INIS)

LeBlanc, M.

2005-01-01

Wind energy forecasting adds financial value to wind farms and may soon become a regulatory requirement. A robust information technology system is essential for addressing industry demands. Various forecasting methodologies for short-term wind production in complex terrain were presented. Numerical weather predictions were discussed with reference to supervisory control and data acquisition (SCADA) system site measurements. Forecasting methods using wind speed, direction, temperature and pressure, as well as issues concerning statistical modelling were presented. Model output statistics and neural networks were reviewed, as well as significant components of error. Results from a Garrad Hassan forecaster with a European wind farm were presented, including wind speed evaluation, and forecast horizon for T + 1 hours, T + 12 hours, and T + 36 hours. It was suggested that buy prices often reflect the cost of under-prediction, and that forecasting has more potential where the spread is greatest. Accurate T + 19 hours to T + 31 hours could enable participation in the day-ahead market, which is less volatile and prices are usually better. Estimates of possible profits per annum through the use of GH forecaster power predictions were presented, calculated over and above spilling power to the grid. It was concluded that accurate forecasts combined with certainty evaluation enables the optimization of wind energy in the market, and is applicable to a wide range of weather regimes and terrain types. It was suggested that site feedback is essential for good forecasts at short horizons, and that the value of forecasting is dependent on the market. refs., tabs., figs

Online short-term heat load forecasting for single family houses

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2013-01-01

. Every hour the hourly heat load for each house the following two days is forecasted. The forecast models are adaptive linear time-series models and the climate inputs used are: ambient temperature, global radiation, and wind speed. A computationally efficient recursive least squares scheme is used......This paper presents a method for forecasting the load for heating in a single-family house. Both space and hot tap water heating are forecasted. The forecasting model is built using data from sixteen houses in Sønderborg, Denmark, combined with local climate measurements and weather forecasts...... variations in the heat load signal (predominant only for some houses), peaks presumably from showers, shifts in resident behavior, and uncertainty of the weather forecasts for longer horizons, especially for the solar radiation....

Analysts’ forecast error: A robust prediction model and its short term trading profitability

NARCIS (Netherlands)

Boudt, K.M.R.; de Goei, P.; Thewissen, J.; van Campenhout, G.

2015-01-01

This paper contributes to the empirical evidence on the investment horizon salient to trading based on predicting the error in analysts' earnings forecasts. An econometric framework is proposed that accommodates the stylized fact of extreme values in the forecast error series. We find that between

A Simple Hybrid Model for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Suseelatha Annamareddi

2013-01-01

Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

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)

The Use of Ambient Humidity Conditions to Improve Influenza Forecast

Science.gov (United States)

Shaman, J. L.; Kandula, S.; Yang, W.; Karspeck, A. R.

2017-12-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast and provide further evidence that humidity modulates rates of influenza transmission.

Multifractality and value-at-risk forecasting of exchange rates

Science.gov (United States)

Batten, Jonathan A.; Kinateder, Harald; Wagner, Niklas

2014-05-01

This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.

Comparison of two new short-term wind-power forecasting systems

Energy Technology Data Exchange (ETDEWEB)

Ramirez-Rosado, Ignacio J. [Department of Electrical Engineering, University of Zaragoza, Zaragoza (Spain); Fernandez-Jimenez, L. Alfredo [Department of Electrical Engineering, University of La Rioja, Logrono (Spain); Monteiro, Claudio; Sousa, Joao; Bessa, Ricardo [FEUP, Fac. Engenharia Univ. Porto (Portugal)]|[INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

2009-07-15

This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction model; and electric power-generation registers from the SCADA system of the wind farm. Both systems are described in detail and the forecasting results compared, revealing great similarities, although the proposed structures of the two systems are different. The forecast horizon for both systems is 72 h, allowing the use of the forecasted values in electric market operations, as diary and intra-diary power generation bid offers, and in wind-farm maintenance planning. (author)

A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts

Directory of Open Access Journals (Sweden)

Hossein Hassani

2015-08-01

Full Text Available This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS test, referred to as the KS Predictive Accuracy (KSPA test. The KSPA test is able to serve two distinct purposes. Initially, the test seeks to determine whether there exists a statistically significant difference between the distribution of forecast errors, and secondly it exploits the principles of stochastic dominance to determine whether the forecasts with the lower error also reports a stochastically smaller error than forecasts from a competing model, and thereby enables distinguishing between the predictive accuracy of forecasts. We perform a simulation study for the size and power of the proposed test and report the results for different noise distributions, sample sizes and forecasting horizons. The simulation results indicate that the KSPA test is correctly sized, and robust in the face of varying forecasting horizons and sample sizes along with significant accuracy gains reported especially in the case of small sample sizes. Real world applications are also considered to illustrate the applicability of the proposed KSPA test in practice.

Assessment of a new seasonal to inter-annual operational Great Lakes water supply, water levels, and connecting channel flow forecasting system

Science.gov (United States)

Gronewold, A.; Fry, L. M.; Hunter, T.; Pei, L.; Smith, J.; Lucier, H.; Mueller, R.

2017-12-01

The U.S. Army Corps of Engineers (USACE) has recently operationalized a suite of ensemble forecasts of Net Basin Supply (NBS), water levels, and connecting channel flows that was developed through a collaboration among USACE, NOAA's Great Lakes Environmental Research Laboratory, Ontario Power Generation (OPG), New York Power Authority (NYPA), and the Niagara River Control Center (NRCC). These forecasts are meant to provide reliable projections of potential extremes in daily discharge in the Niagara and St. Lawrence Rivers over a long time horizon (5 years). The suite of forecasts includes eight configurations that vary by (a) NBS model configuration, (b) meteorological forcings, and (c) incorporation of seasonal climate projections through the use of weighting. Forecasts are updated on a weekly basis, and represent the first operational forecasts of Great Lakes water levels and flows that span daily to inter-annual horizons and employ realistic regulation logic and lake-to-lake routing. We will present results from a hindcast assessment conducted during the transition from research to operation, as well as early indications of success rates determined through operational verification of forecasts. Assessment will include an exploration of the relative skill of various forecast configurations at different time horizons and the potential for application to hydropower decision making and Great Lakes water management.

Advancing solar energy forecasting through the underlying physics

Science.gov (United States)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Online short-term solar power forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2009-01-01

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen......-minute observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques....... Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours...

Skill forecasting from ensemble predictions of wind power

DEFF Research Database (Denmark)

Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

2009-01-01

Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

The use of ambient humidity conditions to improve influenza forecast.

Science.gov (United States)

Shaman, Jeffrey; Kandula, Sasikiran; Yang, Wan; Karspeck, Alicia

2017-11-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

Unlimited energy, restricted carbohydrate diet improves lipid parameters in obese children.

Science.gov (United States)

Dunlap, Brian S; Bailes, James R

2008-03-01

Childhood obesity is a leading health concern. We have previously demonstrated the effectiveness of a restricted-carbohydrate, unlimited energy diet for weight reduction in elementary school-aged children. To our knowledge, there are no studies that have looked at the effect of this diet on lipid profiles in elementary school-aged children. Therefore, the objective of this pilot study was to examine the effect of a restricted-carbohydrate, unlimited protein, unlimited energy diet on lipid profiles in obese children 6 to 12 years of age. Overweight children (body mass index >97%) referred to our obesity clinic were treated with a restricted-carbohydrate (unlimited protein, and unlimited energy diet. Weight, height, body mass index, and fasting lipid profiles were obtained at baseline and at 10 weeks on each patient. Twenty-seven patients were enrolled in our study, with a total of 18 patients returning for our 10 week follow-up (67%). The study group included 10 males and 8 females, with an age range of 6 to 12 years. Both total serum cholesterol and triglyceride levels showed a significant reduction; 24.2 (P = 0.018) and 56.9 (P = 0.015) mg/dL, respectively. We have demonstrated a significant decrease in total cholesterol and triglycerides in elementary school-aged children after 10 weeks of a restricted-carbohydrate, unlimited protein, and unlimited energy diet. We suggest that this diet may decrease cardiovascular risk factors in obese children. Long-term studies will be needed to substantiate these data.

On the directional accuracy of survey forecasts: the case of gold and silver

DEFF Research Database (Denmark)

Fritsche, U.; Pierdzioch, C.; Rulke, J. C.

2013-01-01

We use a nonparametric market-timing test to study the directional accuracy of survey forecasts of the prices of gold and silver. We find that forecasters have market-timing ability with respect to the direction of change of the price of silver at various forecast horizons. In contrast, forecasters...... have no market-timing ability with respect to the direction of change in the gold price. Combining forecasts of both metal prices to set up a multivariate market-timing test yields no evidence of joint predictability of the directions of change of the prices of gold and silver....

Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

DEFF Research Database (Denmark)

Dahl, Christian M.; Croonenbroeck, Carsten

2014-01-01

We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium......-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...... accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology....

Day-ahead wind speed forecasting using f-ARIMA models

International Nuclear Information System (INIS)

Kavasseri, Rajesh G.; Seetharaman, Krithika

2009-01-01

With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed/power forecasts. Accurate wind speed forecasts are necessary to schedule dispatchable generation and tariffs in the day-ahead electricity market. This paper examines the use of fractional-ARIMA or f-ARIMA models to model, and forecast wind speeds on the day-ahead (24 h) and two-day-ahead (48 h) horizons. The models are applied to wind speed records obtained from four potential wind generation sites in North Dakota. The forecasted wind speeds are used in conjunction with the power curve of an operational (NEG MICON, 750 kW) turbine to obtain corresponding forecasts of wind power production. The forecast errors in wind speed/power are analyzed and compared with the persistence model. Results indicate that significant improvements in forecasting accuracy are obtained with the proposed models compared to the persistence method. (author)

The use of ambient humidity conditions to improve influenza forecast.

Directory of Open Access Journals (Sweden)

Jeffrey Shaman

2017-11-01

Full Text Available Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

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)

Short-term Wind Forecasting to Support Virtual Power Player Operation

OpenAIRE

Ramos, Sérgio; Soares, João; Pinto, Tiago; Vale, Zita

2013-01-01

This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed ...

Rough Precipitation Forecasts based on Analogue Method: an Operational System

Science.gov (United States)

Raffa, Mario; Mercogliano, Paola; Lacressonnière, Gwendoline; Guillaume, Bruno; Deandreis, Céline; Castanier, Pierre

2017-04-01

In the framework of the Climate KIC partnership, has been funded the project Wat-Ener-Cast (WEC), coordinated by ARIA Technologies, having the goal to adapt, through tailored weather-related forecast, the water and energy operations to the increased weather fluctuation and to climate change. The WEC products allow providing high quality forecast suited in risk and opportunities assessment dashboard for water and energy operational decisions and addressing the needs of sewage/water distribution operators, energy transport & distribution system operators, energy manager and wind energy producers. A common "energy water" web platform, able to interface with newest smart water-energy IT network have been developed. The main benefit by sharing resources through the "WEC platform" is the possibility to optimize the cost and the procedures of safety and maintenance team, in case of alerts and, finally to reduce overflows. Among the different services implemented on the WEC platform, ARIA have developed a product having the goal to support sewage/water distribution operators, based on a gradual forecast information system ( at 48hrs/24hrs/12hrs horizons) of heavy precipitation. For each fixed deadline different type of operation are implemented: 1) 48hour horizon, organisation of "on call team", 2) 24 hour horizon, update and confirm the "on call team", 3) 12 hour horizon, secure human resources and equipment (emptying storage basins, pipes manipulations …). More specifically CMCC have provided a statistical downscaling method in order to provide a "rough" daily local precipitation at 24 hours, especially when high precipitation values are expected. This statistical technique consists of an adaptation of analogue method based on ECMWF data (analysis and forecast at 24 hours). One of the most advantages of this technique concerns a lower computational burden and budget compared to running a Numerical Weather Prediction (NWP) model, also if, of course it provides only this

Deep Random based Key Exchange protocol resisting unlimited MITM

OpenAIRE

de Valroger, Thibault

2018-01-01

We present a protocol enabling two legitimate partners sharing an initial secret to mutually authenticate and to exchange an encryption session key. The opponent is an active Man In The Middle (MITM) with unlimited computation and storage capacities. The resistance to unlimited MITM is obtained through the combined use of Deep Random secrecy, formerly introduced and proved as unconditionally secure against passive opponent for key exchange, and universal hashing techniques. We prove the resis...

Formulation for less master production schedule instability under rolling horizon

OpenAIRE

Herrera , Carlos; Thomas , André

2009-01-01

International audience; In Manufacturing Planning and Control Systems, the Master Production Schedule (MPS) makes a link between tactical and operational levels, taking into account information provided by end items, demand forecast as well as Sales and Operations Planning (S&OP) suggestions. Therefore, MPS plays an important role to maintain an adequate customers service level and an efficient production system. In a rolling planning horizon, MPS is periodically computed over whole operation...

Forecasting non-stationary diarrhea, acute respiratory infection, and malaria time-series in Niono, Mali.

Science.gov (United States)

Medina, Daniel C; Findley, Sally E; Guindo, Boubacar; Doumbia, Seydou

2007-11-21

Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods. In this longitudinal retrospective (01/1996-06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%. The multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions

Probabilistic forecasting for extreme NO2 pollution episodes

International Nuclear Information System (INIS)

Aznarte, José L.

2017-01-01

In this study, we investigate the convenience of quantile regression to predict extreme concentrations of NO 2 . Contrarily to the usual point-forecasting, where a single value is forecast for each horizon, probabilistic forecasting through quantile regression allows for the prediction of the full probability distribution, which in turn allows to build models specifically fit for the tails of this distribution. Using data from the city of Madrid, including NO 2 concentrations as well as meteorological measures, we build models that predict extreme NO 2 concentrations, outperforming point-forecasting alternatives, and we prove that the predictions are accurate, reliable and sharp. Besides, we study the relative importance of the independent variables involved, and show how the important variables for the median quantile are different than those important for the upper quantiles. Furthermore, we present a method to compute the probability of exceedance of thresholds, which is a simple and comprehensible manner to present probabilistic forecasts maximizing their usefulness. - Highlights: • A new probabilistic forecasting system is presented to predict NO 2 concentrations. • While predicting the full distribution, it also outperforms other point-forecasting models. • Forecasts show good properties and peak concentrations are properly predicted. • It forecasts the probability of exceedance of thresholds, key to decision makers. • Relative forecasting importance of the variables is obtained as a by-product.

An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

Directory of Open Access Journals (Sweden)

F. Anctil

2009-11-01

Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

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

Submesoscale dispersion in the vicinity of the Deepwater Horizon spill

OpenAIRE

Poje, Andrew C.; Özgökmen, Tamay M.; Lipphardt, Bruce L.; Haus, Brian K.; Ryan, Edward H.; Haza, Angelique C.; Jacobs, Gregg A.; Reniers, A. J. H. M.; Olascoaga, Maria Josefina; Novelli, Guillaume; Griffa, Annalisa; Beron-Vera, Francisco J.; Chen, Shuyi S.; Coelho, Emanuel; Hogan, Patrick J.

2014-01-01

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity fi...

Initial results with time series forecasting of TJ-II heliac waveforms

International Nuclear Information System (INIS)

Farias, G.; Dormido-Canto, S.; Vega, J.; Díaz, N.

2015-01-01

This article discusses about how to apply forecasting techniques to predict future samples of plasma signals during a discharge. One application of the forecasting could be to detect in real time anomalous behaviors in fusion waveforms. The work describes the implementation of three prediction techniques; two of them based on machine learning methods such as artificial neural networks and support vector machines for regression. The results have shown that depending on the temporal horizon, the predictions match the real samples in most cases with an error less than 5%, even more the forecasting of five samples ahead can reach accuracy over 90% in most signals analyzed.

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.

Unlimited - nuclear liabilities in the Federal Republic of Germany

International Nuclear Information System (INIS)

Arendt, W.

1986-01-01

Unlimited nuclear liabilities as in force in the Federal Republic of Germany go beyond the international rules of the Paris liability agreement. The unlimited liability mainly roots in the positive operational experiences and safety balance of the 20 nuclear power plants which meanwhile are in operation in the Federal Republic of Germany. Nuclear liabilities must not be confounded with scepticism as to the utilization of nuclear power. Extraordinary requirements of that kind should rather be reflecting responsibility and clear ideas and notions of the advantages and risks of nuclear energy. (HSCH) [de

Evaluating Extensions to Coherent Mortality Forecasting Models

Directory of Open Access Journals (Sweden)

Syazreen Shair

2017-03-01

Full Text Available Coherent models were developed recently to forecast the mortality of two or more sub-populations simultaneously and to ensure long-term non-divergent mortality forecasts of sub-populations. This paper evaluates the forecast accuracy of two recently-published coherent mortality models, the Poisson common factor and the product-ratio functional models. These models are compared to each other and the corresponding independent models, as well as the original Lee–Carter model. All models are applied to age-gender-specific mortality data for Australia and Malaysia and age-gender-ethnicity-specific data for Malaysia. The out-of-sample forecast error of log death rates, male-to-female death rate ratios and life expectancy at birth from each model are compared and examined across groups. The results show that, in terms of overall accuracy, the forecasts of both coherent models are consistently more accurate than those of the independent models for Australia and for Malaysia, but the relative performance differs by forecast horizon. Although the product-ratio functional model outperforms the Poisson common factor model for Australia, the Poisson common factor is more accurate for Malaysia. For the ethnic groups application, ethnic-coherence gives better results than gender-coherence. The results provide evidence that coherent models are preferable to independent models for forecasting sub-populations’ mortality.

Fishing Facts Unlimited. Enterprise: Man & Technology.

Science.gov (United States)

Southern Illinois Univ., Carbondale. Dept. of Technical and Industrial Education.

Fishing Facts Unlimited, a student conducted enterprise in Technical and Industrial Education at Southern Illinois University, Carbondale has been a very successful operation, both financially and in providing a community service. The service provided by the enterprise was the production and sales of a 48-page fishing guide to Southern Illinois.…

UNLIMITED I, On the corporate training revolution

Directory of Open Access Journals (Sweden)

Leandro Adolfo Viltard

2017-09-01

Full Text Available The unlimited is a borderless territory where the whole world is inmerse. In this study, it is shown that the unlimited is present in education and, specifically, in the corporate educational arena. Helped by technology and automation, disruptive leaders are challenging the way things are done, the way we think and, in addtion, what we are. After performing a documentation analysis, conclusions are that big problems –as education- need cheap and scaled technology; leadership and organizations must evolve to less human intervention; education and training need a rethought; Eduaction-2-Employment (E2E is key for unemployment; and that new educational structures, delivery methods, pedagogical approaches and advanced Learning Management Systems (LMS are observed proposing huge transformations in the corporate educational arena. This is a qualitative investigation with a not experimental and transversal research design.

From probabilistic forecasts to statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2009-01-01

on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting.

Science.gov (United States)

Corzo, Gerald; Solomatine, Dimitri

2007-05-01

Natural phenomena are multistationary and are composed of a number of interacting processes, so one single model handling all processes often suffers from inaccuracies. A solution is to partition data in relation to such processes using the available domain knowledge or expert judgment, to train separate models for each of the processes, and to merge them in a modular model (committee). In this paper a problem of water flow forecast in watershed hydrology is considered where the flow process can be presented as consisting of two subprocesses -- base flow and excess flow, so that these two processes can be separated. Several approaches to data separation techniques are studied. Two case studies with different forecast horizons are considered. Parameters of the algorithms responsible for data partitioning are optimized using genetic algorithms and global pattern search. It was found that modularization of ANN models using domain knowledge makes models more accurate, if compared with a global model trained on the whole data set, especially when forecast horizon (and hence the complexity of the modelled processes) is increased.

Skill forecasting from different wind power ensemble prediction methods

International Nuclear Information System (INIS)

Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

2007-01-01

This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

Time orientation, planning horizons and responsibility into the future

International Nuclear Information System (INIS)

Svenson, O.; Nilsson, G.

1988-01-01

Subjects of four categories (social science students, engineering students, retired people and nuclear waste experts) were asked about past events, planning, risks and future time with emphasis on energy related issues and in particular questions concerning spent nuclear waste. Among, the results reported it was found that events in the past were located more or less correctly and that events further back systematically too close to the present. Today's responsibility into the future was judged to cover 3 to 6 generations ahead and an adequate planning horizon for a local community to be on the average 11 to 14 years. Adequate planning horizons for the handling of spent nuclear fuel were judged to be from 100 to 500 years. The responsibility for effects of today's decisions was judged to be from about 100 to 300 years into the future for environmental pollution and from about 50 to 600 years for nuclear waste. However, non-negliqable proportions of the subjects choose a more moral standpoint and gave answers indicating that responsibility had to be unlimited. Some sex differences were found and an interaction with age offered as a hypothesis to be investigated in the future. Interrelations between clusters of questions revealed some links from past time and planning to judgements of environmental and nuclear power related risks. (orig.)

Parametric decadal climate forecast recalibration (DeFoReSt 1.0

Directory of Open Access Journals (Sweden)

A. Pasternack

2018-01-01

Full Text Available Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt, a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS. Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

Science.gov (United States)

Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

2018-01-01

Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

THE ACCURACY AND BIAS EVALUATION OF THE USA UNEMPLOYMENT RATE FORECASTS. METHODS TO IMPROVE THE FORECASTS ACCURACY

Directory of Open Access Journals (Sweden)

MIHAELA BRATU (SIMIONESCU

2012-12-01

Full Text Available In this study some alternative forecasts for the unemployment rate of USA made by four institutions (International Monetary Fund (IMF, Organization for Economic Co-operation and Development (OECD, Congressional Budget Office (CBO and Blue Chips (BC are evaluated regarding the accuracy and the biasness. The most accurate predictions on the forecasting horizon 201-2011 were provided by IMF, followed by OECD, CBO and BC.. These results were gotten using U1 Theil’s statistic and a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the institutions regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The IMF, OECD and CBO predictions are unbiased. The combined forecasts of institutions’ predictions are a suitable strategy to improve the forecasts accuracy of IMF and OECD forecasts when all combination schemes are used, but INV one is the best. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique are a good strategy of improving only the BC expectations. The proposed strategies to improve the accuracy do not solve the problem of biasness. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decisional process.

Operational Efficiency Forecasting Model of an Existing Underground Mine Using Grey System Theory and Stochastic Diffusion Processes

Directory of Open Access Journals (Sweden)

Svetlana Strbac Savic

2015-01-01

Full Text Available Forecasting the operational efficiency of an existing underground mine plays an important role in strategic planning of production. Degree of Operating Leverage (DOL is used to express the operational efficiency of production. The forecasting model should be able to involve common time horizon, taking the characteristics of the input variables that directly affect the value of DOL. Changes in the magnitude of any input variable change the value of DOL. To establish the relationship describing the way of changing we applied multivariable grey modeling. Established time sequence multivariable response formula is also used to forecast the future values of operating leverage. Operational efficiency of production is often associated with diverse sources of uncertainties. Incorporation of these uncertainties into multivariable forecasting model enables mining company to survive in today’s competitive environment. Simulation of mean reversion process and geometric Brownian motion is used to describe the stochastic diffusion nature of metal price, as a key element of revenues, and production costs, respectively. By simulating a forecasting model, we imitate its action in order to measure its response to different inputs. The final result of simulation process is the expected value of DOL for every year of defined time horizon.

The spatial relation between the event horizon and trapping horizon

International Nuclear Information System (INIS)

Nielsen, Alex B

2010-01-01

The relation between event horizons and trapping horizons is investigated in a number of different situations with emphasis on their role in thermodynamics. A notion of constant change is introduced that in certain situations allows the location of the event horizon to be found locally. When the black hole is accreting matter the difference in area between the two different horizons can be many orders of magnitude larger than the Planck area. When the black hole is evaporating, the difference is small on the Planck scale. A model is introduced that shows how trapping horizons can be expected to appear outside the event horizon before the black hole starts to evaporate. Finally, a modified definition is introduced to invariantly define the location of the trapping horizon under a conformal transformation. In this case the trapping horizon is not always a marginally outer trapped surface.

Estimation of the uncertainty in wind power forecasting

International Nuclear Information System (INIS)

Pinson, P.

2006-03-01

WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level

Short time ahead wind power production forecast

International Nuclear Information System (INIS)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-01-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)

Short time ahead wind power production forecast

Science.gov (United States)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-09-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

Spatial bias and uncertainty in numerical weather predictions for urban runoff forecasts with long time horizons

DEFF Research Database (Denmark)

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

2017-01-01

Numerical Weather Predictions (NWP) can be used to forecast urban runoff with long lead times. However, NWP exhibit large spatial uncertainties and using forecasted precipitation directly above the catchment might therefore not be an ideal approach in an online setup. We use the Danish...... Meteorological Institute’s NWP ensemble and investigate a large spatial neighborhood around the catchment over a two-year period. When compared against in-sewer observations, runoff forecasts forced with precipitation from north-east of the catchment are most skillful. This highlights spatial biases...

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

Science.gov (United States)

Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

Forecasting monthly peak demand of electricity in India—A critique

International Nuclear Information System (INIS)

Rallapalli, Srinivasa Rao; Ghosh, Sajal

2012-01-01

The nature of electricity differs from that of other commodities since electricity is a non-storable good and there have been significant seasonal and diurnal variations of demand. Under such condition, precise forecasting of demand for electricity should be an integral part of the planning process as this enables the policy makers to provide directions on cost-effective investment and on scheduling the operation of the existing and new power plants so that the supply of electricity can be made adequate enough to meet the future demand and its variations. Official load forecasting in India done by Central Electricity Authority (CEA) is often criticized for being overestimated due to inferior techniques used for forecasting. This paper tries to evaluate monthly peak demand forecasting performance predicted by CEA using trend method and compare it with those predicted by Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) model. It has been found that MSARIMA model outperforms CEA forecasts both in-sample static and out-of-sample dynamic forecast horizons in all five regional grids in India. For better load management and grid discipline, this study suggests employing sophisticated techniques like MSARIMA for peak load forecasting in India. - Highlights: ► This paper evaluates monthly peak demand forecasting performance by CEA. ► Compares CEA forecasts it with those predicted by MSARIMA model. ► MSARIMA model outperforms CEA forecasts in all five regional grids in India. ► Opportunity exists to improve the performance of CEA forecasts.

Near horizon structure of extremal vanishing horizon black holes

Directory of Open Access Journals (Sweden)

S. Sadeghian

2015-11-01

Full Text Available We study the near horizon structure of Extremal Vanishing Horizon (EVH black holes, extremal black holes with vanishing horizon area with a vanishing one-cycle on the horizon. We construct the most general near horizon EVH and near-EVH ansatz for the metric and other fields, like dilaton and gauge fields which may be present in the theory. We prove that (1 the near horizon EVH geometry for generic gravity theory in generic dimension has a three dimensional maximally symmetric subspace; (2 if the matter fields of the theory satisfy strong energy condition either this 3d part is AdS3, or the solution is a direct product of a locally 3d flat space and a d−3 dimensional part; (3 these results extend to the near horizon geometry of near-EVH black holes, for which the AdS3 part is replaced with BTZ geometry. We present some specific near horizon EVH geometries in 3, 4 and 5 dimensions for which there is a classification. We also briefly discuss implications of these generic results for generic (gauged supergravity theories and also for the thermodynamics of near-EVH black holes and the EVH/CFT proposal.

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

Short term solar radiation forecasting: Island versus continental sites

International Nuclear Information System (INIS)

Boland, John; David, Mathieu; Lauret, Philippe

2016-01-01

Due its intermittency, the large-scale integration of solar energy into electricity grids is an issue and more specifically in an insular context. Thus, forecasting the output of solar energy is a key feature to efficiently manage the supply-demand balance. In this paper, three short term forecasting procedures are applied to island locations in order to see how they perform in situations that are potentially more volatile than continental locations. Two continental locations, one coastal and one inland are chosen for comparison. At the two time scales studied, ten minute and hourly, the island locations prove to be more difficult to forecast, as shown by larger forecast errors. It is found that the three methods, one purely statistical combining Fourier series plus linear ARMA models, one combining clear sky index models plus neural net models, and a third using a clear sky index plus ARMA, give similar forecasting results. It is also suggested that there is great potential of merging modelling approaches on different horizons. - Highlights: • Solar energy forecasting is more difficult for insular than continental sites. • Fourier series plus linear ARMA models are one forecasting method tested. • Clear sky index models plus neural net models are also tested. • Clear sky index models plus linear ARMA is also an option. • All three approaches have similar skill.

Floating oil-covered debris from Deepwater Horizon: identification and application

International Nuclear Information System (INIS)

Carmichael, Catherine A; Lemkau, Karin L; Nelson, Robert K; Reddy, Christopher M; Arey, J Samuel; Graham, William M; Linn, Laura J

2012-01-01

The discovery of oiled and non-oiled honeycomb material in the Gulf of Mexico surface waters and along coastal beaches shortly after the explosion of Deepwater Horizon sparked debate about its origin and the oil covering it. We show that the unknown pieces of oiled and non-oiled honeycomb material collected in the Gulf of Mexico were pieces of the riser pipe buoyancy module of Deepwater Horizon. Biomarker ratios confirmed that the oil had originated from the Macondo oil well and had undergone significant weathering. Using the National Oceanic and Atmospheric Administration’s records of the oil spill trajectory at the sea surface, we show that the honeycomb material preceded the front edge of the uncertainty of the oil slick trajectory by several kilometers. We conclude that the observation of debris fields deriving from damaged marine materials may be incorporated into emergency response efforts and forecasting of coastal impacts during future offshore oil spills, and ground truthing predicative models. (letter)

Application of the North American Multi-Model Ensemble to seasonal water supply forecasting in the Great Lakes basin through the use of the Great Lakes Seasonal Climate Forecast Tool

Science.gov (United States)

Gronewold, A.; Apps, D.; Fry, L. M.; Bolinger, R.

2017-12-01

The U.S. Army Corps of Engineers (USACE) contribution to the internationally coordinated 6-month forecast of Great Lakes water levels relies on several water supply models, including a regression model relating a coming month's water supply to past water supplies, previous months' precipitation and temperature, and forecasted precipitation and temperature. Probabilistic forecasts of precipitation and temperature depicted in the Climate Prediction Center's seasonal outlook maps are considered to be standard for use in operational forecasting for seasonal time horizons, and have provided the basis for computing a coming month's precipitation and temperature for use in the USACE water supply regression models. The CPC outlook maps are a useful forecast product offering insight into interpretation of climate models through the prognostic discussion and graphical forecasts. However, recent evolution of USACE forecast procedures to accommodate automated data transfer and manipulation offers a new opportunity for direct incorporation of ensemble climate forecast data into probabilistic outlooks of water supply using existing models that have previously been implemented in a deterministic fashion. We will present results from a study investigating the potential for applying data from the North American Multi-Model Ensemble to operational water supply forecasts. The use of NMME forecasts is facilitated by a new, publicly available, Great Lakes Seasonal Climate Forecast Tool that provides operational forecasts of monthly average temperatures and monthly total precipitation summarized for each lake basin.

Three theorems on near horizon extremal vanishing horizon geometries

Directory of Open Access Journals (Sweden)

S. Sadeghian

2016-02-01

Full Text Available EVH black holes are Extremal black holes with Vanishing Horizon area, where vanishing of horizon area is a result of having a vanishing one-cycle on the horizon. We prove three theorems regarding near horizon geometry of EVH black hole solutions to generic Einstein gravity theories in diverse dimensions. These generic gravity theories are Einstein–Maxwell-dilaton-Λ theories, and gauged or ungauged supergravity theories with U(1 Maxwell fields. Our three theorems are: (1 The near horizon geometry of any EVH black hole has a three dimensional maximally symmetric subspace. (2 If the energy momentum tensor of the theory satisfies strong energy condition either this 3d part is an AdS3, or the solution is a direct product of a locally 3d flat space and a d−3 dimensional part. (3 These results extend to the near horizon geometry of near-EVH black holes, for which the AdS3 part is replaced with BTZ geometry.

Improving the Forecasting Accuracy of Crude Oil Prices

Directory of Open Access Journals (Sweden)

Xuluo Yin

2018-02-01

Full Text Available Currently, oil is the key element of energy sustainability, and its prices and economy have a strong mutual influence. Modeling a good method to accurately predict oil prices over long future horizons is challenging and of great interest to investors and policymakers. This paper forecasts oil prices using many predictor variables with a new time-varying weight combination approach. In doing so, we first use five single-variable time-varying parameter models to predict crude oil prices separately. Second, every special model is assigned a time-varying weight by the new combination approach. Finally, the forecasting results of oil prices are calculated. The results show that the paper’s method is robust and performs well compared to random walk.

A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

Science.gov (United States)

Liu, P.

2013-12-01

Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

Energy demand forecasting method based on international statistical data

International Nuclear Information System (INIS)

Glanc, Z.; Kerner, A.

1997-01-01

Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs

Energy demand forecasting method based on international statistical data

Energy Technology Data Exchange (ETDEWEB)

Glanc, Z; Kerner, A [Energy Information Centre, Warsaw (Poland)

1997-09-01

Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs.

Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework

NARCIS (Netherlands)

Basu, S.

2017-01-01

Accurate simulation and forecasting of over-the-horizon propagation events are essential for various civilian and defense applications. We demonstrate the prowess of a newly proposed coupled mesoscale modeling and ray tracing framework in reproducing such an event. Wherever possible, routinely

An overview of wind power forecast types and their use in large-scale integration of wind power

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Henrik Aalborg; Nielsen, Torben Skov [ENFOR A/S, Horslholm (Denmark); Madsen, Henrik [Technical Univ. of Denmark, Lyngby (Denmark). Informatics and Mathematical Modelling

2011-07-01

Wind power forecast characteristics are described and it is shown how analyses of actual decision problems can be used to derive the forecast characteristics important in a given situation. Generally, characteristics related to resolution in space and time, together with the required maximal forecast horizon are easily identified. However, identification of forecast characteristics required for optimal decision support requires a more thorough investigation, which is illustrated by examples. Generally, quantile forecasts of the future wind power production are required, but the transformation of a quantile forecast into an actual decisions is highly dependent on the precise formulation of the decision problem. Furthermore, when consequences of neighbouring time steps interact, quantile forecasts are not sufficient. It is argued that a general solution in such cases is to base the decision on reliable scenarios of the future wind power production. (orig.)

Verification of Space Weather Forecasts using Terrestrial Weather Approaches

Science.gov (United States)

Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

2015-12-01

MOSWOC forecasters view verification results in near real-time; plans to objectively assess flare forecasts under the EU Horizon 2020 FLARECAST project; and summarise ISES efforts to achieve consensus on verification.

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

Directory of Open Access Journals (Sweden)

J. Hosek

2011-02-01

Full Text Available The northeast coast of North America is frequently hit by severe ice storms. These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply a combination of a numerical weather prediction model and an ice accretion algorithm to simulate a forecast of this event.

The main goals of this study are to compare the simulated meteorological variables to observations, and to assess the ability of the model to accurately predict the ice accretion load for different forecast horizons. The duration and timing of the freezing rain event that occurred between the night of 4 March and the morning of 6 March was simulated well in all model runs. The total precipitation amounts in the model, however, differed by up to a factor of two from the observations. The accuracy of the model air temperature strongly depended on the forecast horizon, but it was acceptable for all simulation runs. The simulated accretion loads were also compared to the design values for power delivery structures in the region. The results indicated that the simulated values exceeded design criteria in the areas of reported damage and power outages.

Two quantitative forecasting methods for macroeconomic indicators in Czech Republic

Directory of Open Access Journals (Sweden)

Mihaela BRATU (SIMIONESCU

2012-03-01

Full Text Available Econometric modelling and exponential smoothing techniques are two quantitative forecasting methods with good results in practice, but the objective of the research was to find out which of the two techniques are better for short run predictions. Therefore, for inflation, unemployment and interest rate in Czech Republic some accuracy indicators were calculated for the predictions based on these methods. Short run forecasts on a horizon of 3 months were made for December 2011-February 2012, the econometric models being updated. For Czech Republic, the exponential smoothing techniques provided more accurate forecasts than the econometric models (VAR(2 models, ARMA procedure and models with lagged variables. One explication for the better performance of smoothing techniques would be that in the chosen countries the short run predictions more influenced by the recent evolution of the indicators.

Unlimited ion acceleration by radiation pressure.

Science.gov (United States)

Bulanov, S V; Echkina, E Yu; Esirkepov, T Zh; Inovenkov, I N; Kando, M; Pegoraro, F; Korn, G

2010-04-02

The energy of ions accelerated by an intense electromagnetic wave in the radiation pressure dominated regime can be greatly enhanced due to a transverse expansion of a thin target. The expansion decreases the number of accelerated ions in the irradiated region resulting in an increase in the ion energy and in the ion longitudinal velocity. In the relativistic limit, the ions become phase locked with respect to the electromagnetic wave resulting in unlimited ion energy gain.

75 FR 41762 - Safety Zone; Annual Kennewick, WA, Columbia Unlimited Hydroplane Races, Kennewick, WA

Science.gov (United States)

2010-07-19

...-AA00 Safety Zone; Annual Kennewick, WA, Columbia Unlimited Hydroplane Races, Kennewick, WA AGENCY..., Columbia Unlimited Hydroplane Races'' also known as the Tri-City Water Follies Hydroplane Races. The safety... power and responsibilities between the Federal Government and Indian tribes. Energy Effects We have...

Prospective analysis of the flows of certain rare earths in Europe at the 2020 horizon.

Science.gov (United States)

Rollat, Alain; Guyonnet, Dominique; Planchon, Mariane; Tuduri, Johann

2016-03-01

This paper proposes a forecast of certain rare earth flows in Europe at the 2020 horizon, based on an analysis of trends influencing various actors of the rare earth industry along the value chain. While 2020 is indicated as the forecast horizon, the analysis should be considered as more representative of the next decade. The rare earths considered here are used in applications that are important for a low-carbon energy transition and/or have a significant recycling potential: NdFeB magnets (Pr, Nd, Dy), NiMH batteries (Pr, Nd) and fluorescent lamp phosphors (Eu, Tb, Y). An analysis of major trends affecting the rare earth industry in Europe along the value chain (including extraction, separation, fabrication, manufacture, use and recycling), helps to build a scenario for a material flow analysis of these rare earths in Europe. The scenario assumes in particular that during the next decade, there exists a rare earth mine in production in Europe (with Norra Kärr in Sweden as a most likely candidate) and also that recycling is in line with targets proposed in recent European legislation. Results are presented in the form of Sankey diagrams which help visualize the various flows for the three applications. For example, calculations forecast flows from extraction to separation of Pr, Nd and Dy for magnet applications in Europe, on the order of 310 tons, 980 tons and 80 tons rare earth metal resp., while recycled flows are 35 tons, 110 tons and 30 tons resp. Calculations illustrate how the relative contribution of recycling to supply strongly depends on the situation with respect to demand. Considering the balance between supply and demand, it is not anticipated any significant shortage of rare earth supply in Europe at the 2020 horizon, barring any new geopolitical crisis involving China. For some heavy rare earths, supply will in fact largely outweigh demand, as for example Europium due to the phasing out of fluorescent lights by LEDs. Copyright © 2016 Elsevier Ltd

Forecasting air quality time series using deep learning.

Science.gov (United States)

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

Multi-parametric variational data assimilation for hydrological forecasting

Science.gov (United States)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

Coupling meteorological and hydrological models for flood forecasting

Directory of Open Access Journals (Sweden)

Bartholmes

2005-01-01

Full Text Available This paper deals with the problem of analysing the coupling of meteorological meso-scale quantitative precipitation forecasts with distributed rainfall-runoff models to extend the forecasting horizon. Traditionally, semi-distributed rainfall-runoff models have been used for real time flood forecasting. More recently, increased computer capabilities allow the utilisation of distributed hydrological models with mesh sizes from tenths of metres to a few kilometres. On the other hand, meteorological models, providing the quantitative precipitation forecast, tend to produce average values on meshes ranging from slightly less than 10 to 200 kilometres. Therefore, to improve the quality of flood forecasts, the effects of coupling the meteorological and the hydrological models at different scales were analysed. A distributed hydrological model (TOPKAPI was developed and calibrated using a 1x1 km mesh for the case of the river Po closed at Ponte Spessa (catchment area c. 37000 km2. The model was then coupled with several other European meteorological models ranging from the Limited Area Models (provided by DMI and DWD with resolutions from 0.0625° * 0.0625°, to the ECMWF ensemble predictions with a resolution of 1.85° * 1.85°. Interesting results, describing the coupled model behaviour, are available for a meteorological extreme event in Northern Italy (Nov. 1994. The results demonstrate the poor reliability of the quantitative precipitation forecasts produced by meteorological models presently available; this is not resolved using the Ensemble Forecasting technique, when compared with results obtainable with measured rainfall.

Short-term forecasting model for aggregated regional hydropower generation

International Nuclear Information System (INIS)

Monteiro, Claudio; Ramirez-Rosado, Ignacio J.; Fernandez-Jimenez, L. Alfredo

2014-01-01

Highlights: • Original short-term forecasting model for the hourly hydropower generation. • The use of NWP forecasts allows horizons of several days. • New variable to represent the capacity level for generating hydroelectric energy. • The proposed model significantly outperforms the persistence model. - Abstract: This paper presents an original short-term forecasting model of the hourly electric power production for aggregated regional hydropower generation. The inputs of the model are previously recorded values of the aggregated hourly production of hydropower plants and hourly water precipitation forecasts using Numerical Weather Prediction tools, as well as other hourly data (load demand and wind generation). This model is composed of three modules: the first one gives the prediction of the “monthly” hourly power production of the hydropower plants; the second module gives the prediction of hourly power deviation values, which are added to that obtained by the first module to achieve the final forecast of the hourly hydropower generation; the third module allows a periodic adjustment of the prediction of the first module to improve its BIAS error. The model has been applied successfully to the real-life case study of the short-term forecasting of the aggregated hydropower generation in Spain and Portugal (Iberian Peninsula Power System), achieving satisfactory results for the next-day forecasts. The model can be valuable for agents involved in electricity markets and useful for power system operations

Wind Resource Assessment and Forecast Planning with Neural Networks

Directory of Open Access Journals (Sweden)

Nicolus K. Rotich

2014-06-01

Full Text Available In this paper we built three types of artificial neural networks, namely: Feed forward networks, Elman networks and Cascade forward networks, for forecasting wind speeds and directions. A similar network topology was used for all the forecast horizons, regardless of the model type. All the models were then trained with real data of collected wind speeds and directions over a period of two years in the municipal of Puumala, Finland. Up to 70th percentile of the data was used for training, validation and testing, while 71–85th percentile was presented to the trained models for validation. The model outputs were then compared to the last 15% of the original data, by measuring the statistical errors between them. The feed forward networks returned the lowest errors for wind speeds. Cascade forward networks gave the lowest errors for wind directions; Elman networks returned the lowest errors when used for short term forecasting.

Analysis and forecasting of nonresidential electricity consumption in Romania

Energy Technology Data Exchange (ETDEWEB)

Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio [Dipartimento di Ingegneria Aerospaziale e Meccanica, Seconda Universita degli Studi di Napoli, Via Roma 29, 81031 Aversa (CE) (Italy); Minea, Alina A. [Faculty of Materials Science and Engineering, Technical University Gh. Asachi from Iasi, Bd. D. Mangeron, No. 59, Iasi (Romania)

2010-11-15

Electricity consumption forecast has fundamental importance in the energy planning of a country. In this paper, we present an analysis and two forecast models for nonresidential electricity consumption in Romania. A first part of the paper is dedicated to the estimation of GDP and price elasticities of consumption. Nonresidential short run GDP and price elasticities are found to be approximately 0.136 and -0.0752, respectively, whereas long run GDP and price elasticities are equal to 0.496 and -0.274 respectively. The second part of the study is dedicated to the forecasting of nonresidential electricity consumption up to year 2020. A Holt-Winters exponential smoothing method and a trigonometric grey model with rolling mechanism (TGMRM) are employed for the consumption prediction. The two models lead to similar results, with an average deviation less than 5%. This deviation is to be considered acceptable in relation to the time horizon considered in the present study. (author)

Analysis and forecasting of nonresidential electricity consumption in Romania

International Nuclear Information System (INIS)

Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio; Minea, Alina A.

2010-01-01

Electricity consumption forecast has fundamental importance in the energy planning of a country. In this paper, we present an analysis and two forecast models for nonresidential electricity consumption in Romania. A first part of the paper is dedicated to the estimation of GDP and price elasticities of consumption. Nonresidential short run GDP and price elasticities are found to be approximately 0.136 and -0.0752, respectively, whereas long run GDP and price elasticities are equal to 0.496 and -0.274 respectively. The second part of the study is dedicated to the forecasting of nonresidential electricity consumption up to year 2020. A Holt-Winters exponential smoothing method and a trigonometric grey model with rolling mechanism (TGMRM) are employed for the consumption prediction. The two models lead to similar results, with an average deviation less than 5%. This deviation is to be considered acceptable in relation to the time horizon considered in the present study. (author)

Forecasting of Radiation Belts: Results From the PROGRESS Project.

Science.gov (United States)

Balikhin, M. A.; Arber, T. D.; Ganushkina, N. Y.; Walker, S. N.

2017-12-01

Forecasting of Radiation Belts: Results from the PROGRESS Project. The overall goal of the PROGRESS project, funded in frame of EU Horizon2020 programme, is to combine first principles based models with the systems science methodologies to achieve reliable forecasts of the geo-space particle radiation environment.The PROGRESS incorporates three themes : The propagation of the solar wind to L1, Forecast of geomagnetic indices, and forecast of fluxes of energetic electrons within the magnetosphere. One of the important aspects of the PROGRESS project is the development of statistical wave models for magnetospheric waves that affect the dynamics of energetic electrons such as lower band chorus, hiss and equatorial noise. The error reduction ratio (ERR) concept has been used to optimise the set of solar wind and geomagnetic parameters for organisation of statistical wave models for these emissions. The resulting sets of parameters and statistical wave models will be presented and discussed. However the ERR analysis also indicates that the combination of solar wind and geomagnetic parameters accounts for only part of the variance of the emissions under investigation (lower band chorus, hiss and equatorial noise). In addition, advances in the forecast of fluxes of energetic electrons, exploiting empirical models and the first principles IMPTAM model achieved by the PROGRESS project is presented.

Towards the intrahour forecasting of direct normal irradiance using sky-imaging data.

Science.gov (United States)

Nou, Julien; Chauvin, Rémi; Eynard, Julien; Thil, Stéphane; Grieu, Stéphane

2018-04-01

Increasing power plant efficiency through improved operation is key in the development of Concentrating Solar Power (CSP) technologies. To this end, one of the most challenging topics remains accurately forecasting the solar resource at a short-term horizon. Indeed, in CSP plants, production is directly impacted by both the availability and variability of the solar resource and, more specifically, by Direct Normal Irradiance (DNI). The present paper deals with a new approach to the intrahour forecasting (the forecast horizon [Formula: see text] is up to [Formula: see text] ahead) of DNI, taking advantage of the fact that this quantity can be split into two terms, i.e. clear-sky DNI and the clear sky index. Clear-sky DNI is forecasted from DNI measurements, using an empirical model (Ineichen and Perez, 2002) combined with a persistence of atmospheric turbidity. Moreover, in the framework of the CSPIMP (Concentrating Solar Power plant efficiency IMProvement) research project, PROMES-CNRS has developed a sky imager able to provide High Dynamic Range (HDR) images. So, regarding the clear-sky index, it is forecasted from sky-imaging data, using an Adaptive Network-based Fuzzy Inference System (ANFIS). A hybrid algorithm that takes inspiration from the classification algorithm proposed by Ghonima et al. (2012) when clear-sky anisotropy is known and from the hybrid thresholding algorithm proposed by Li et al. (2011) in the opposite case has been developed to the detection of clouds. Performance is evaluated via a comparative study in which persistence models - either a persistence of DNI or a persistence of the clear-sky index - are included. Preliminary results highlight that the proposed approach has the potential to outperform these models (both persistence models achieve similar performance) in terms of forecasting accuracy: over the test data used, RMSE (the Root Mean Square Error) is reduced of about [Formula: see text], with [Formula: see text], and [Formula: see

Topology of Event Horizon

OpenAIRE

Siino, Masaru

1997-01-01

The topologies of event horizons are investigated. Considering the existence of the endpoint of the event horizon, it cannot be differentiable. Then there are the new possibilities of the topology of the event horizon though they are excluded in smooth event horizons. The relation between the topology of the event horizon and the endpoint of it is revealed. A torus event horizon is caused by two-dimensional endpoints. One-dimensional endpoints provide the coalescence of spherical event horizo...

Horizon measures

KAUST Repository

Zhang, Eugene

2016-11-28

In this paper we seek to answer the following question: where do contour lines and visible contour lines (silhouette) tend to occur in a 3D surface. Our study leads to two novel shape descriptors, the horizon measure and the visible horizon measure, which we apply to the visualization of 3D shapes including archeological artifacts. In addition to introducing the shape descriptors, we also provide a closed-form formula for the horizon measure based on classical spherical geometry. To compute the visible horizon measure, which depends on the exact computation of the surface visibility function, we instead of provide an image-based approach which can process a model with high complexity within a few minutes.

Unlimited Relativistic Shock Surfing Acceleration

International Nuclear Information System (INIS)

Ucer, D.; Shapiro, V. D.

2001-01-01

Nonrelativistic shock surfing acceleration at quasiperpendicular shocks is usually considered to be a preacceleration mechanism for slow pickup ions to initiate diffusive shock acceleration. In shock surfing, the particle accelerates along the shock front under the action of the convective electric field of the plasma flow. However, the particle also gains kinetic energy normal to the shock and eventually escapes downstream. We consider the case when ions are accelerated to relativistic velocities. In this case, the ions are likely to be trapped for infinitely long times, because the energy of bounce oscillations tends to decrease during acceleration. This suggests the possibility of unlimited acceleration by shock surfing

Early warnings of extreme winds using the ECMWF Extreme Forecast Index

DEFF Research Database (Denmark)

Petroliagis, Thomas I.; Pinson, Pierre

2014-01-01

The European FP7 SafeWind Project aims at developing research towards a European vision of wind power forecasting, which requires advanced meteorological support concerning extreme wind events. This study is focused mainly on early warnings of extreme winds in the early medium-range. Three synoptic...... regimes. Overall, it becomes clear that the first indications of an extreme wind event might come from the ECMWF deterministic and/or probabilistic components capturing very intense weather systems (possible windstorms) in the medium term. For early warnings, all available EPS Extreme Forecast Index (EFI......) formulations were used, by linking daily maximum wind speeds to EFI values for different forecast horizons. From all possible EFI schemes deployed for issuing early warnings, the highest skill was found for the Gust Factor formulation (EFI-10FGI). Using EFI-10FGI, the corresponding 99% threshold could provide...

Predicting Earth orientation changes from global forecasts of atmosphere-hydrosphere dynamics

Science.gov (United States)

Dobslaw, Henryk; Dill, Robert

2018-02-01

Effective Angular Momentum (EAM) functions obtained from global numerical simulations of atmosphere, ocean, and land surface dynamics are routinely processed by the Earth System Modelling group at Deutsches GeoForschungsZentrum. EAM functions are available since January 1976 with up to 3 h temporal resolution. Additionally, 6 days-long EAM forecasts are routinely published every day. Based on hindcast experiments with 305 individual predictions distributed over 15 months, we demonstrate that EAM forecasts improve the prediction accuracy of the Earth Orientation Parameters at all forecast horizons between 1 and 6 days. At day 6, prediction accuracy improves down to 1.76 mas for the terrestrial pole offset, and 2.6 mas for Δ UT1, which correspond to an accuracy increase of about 41% over predictions published in Bulletin A by the International Earth Rotation and Reference System Service.

Forecasting value added of agricultural sub-sectors during fourth five-year development plan in iran

International Nuclear Information System (INIS)

Nassabian, S.

2009-01-01

This article focuses on forecasting the values added of agricultural sub-sectors, including agronomy, fishing, forestry, animal husbandry and agricultural services, using the Artificial Neural Networks (ANN) model. It compares the resulting figures with the target estimates throughout the plan within the years 1384-1388 (2005-2009). It turns out that the forecasted values added in the sub-sectors of agronomy and agricultural services are higher and slower than the estimated values added required due to the plan, respectively. Also the high conformity of the estimated and forecasted value added on the horizon of the fourth five-year plan, while the other sub-sectors both the values are close to each other. The results indicate that the capability of ANN method for forecasting variables is more suitable than the other methods. (author)

Investment horizon heterogeneity and wavelet: Overview and further research directions

Science.gov (United States)

Chakrabarty, Anindya; De, Anupam; Gunasekaran, Angappa; Dubey, Rameshwar

2015-07-01

Wavelet based multi-scale analysis of financial time series has attracted much attention, lately, from both the academia and practitioners from all around the world. The unceasing metamorphosis of the discipline of finance from its humble beginning as applied economics to the more sophisticated depiction as applied physics and applied psychology has revolutionized the way we perceive the market and its complexities. One such complexity is the presence of heterogeneous horizon agents in the market. In this context, we have performed a generous review of different aspects of horizon heterogeneity that has been successfully elucidated through the synergy between wavelet theory and finance. The evolution of wavelet has been succinctly delineated to bestow necessary information to the readers who are new to this field. The migration of wavelet into finance and its subsequent branching into different sub-divisions have been sketched. The pertinent literature on the impact of horizon heterogeneity on risk, asset pricing and inter-dependencies of the financial time series are explored. The significant contributions are collated and classified in accordance to their purpose and approach so that potential researcher and practitioners, interested in this subject, can be benefited. Future research possibilities in the direction of "agency cost mitigation" and "synergy between econophysics and behavioral finance in stock market forecasting" are also suggested in the paper.

Time-series-based hybrid mathematical modelling method adapted to forecast automotive and medical waste generation: Case study of Lithuania.

Science.gov (United States)

Karpušenkaitė, Aistė; Ruzgas, Tomas; Denafas, Gintaras

2018-05-01

The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used 'pure' time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%-4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models' abilities to forecast short- and mid-term forecasts were tested using prediction horizon.

Wind Power accuracy and forecast. D3.1. Assumptions on accuracy of wind power to be considered at short and long term horizons

Energy Technology Data Exchange (ETDEWEB)

Morthorst, P.E.; Coulondre, J.M.; Schroeder, S.T.; Meibom, P.

2010-07-15

The main objective of the Optimate project (An Open Platform to Test Integration in new MArkeT designs of massive intermittent Energy sources dispersed in several regional power markets) is to develop a new tool for testing these new market designs with large introduction of variable renewable energy sources. In Optimate a novel network/system/market modelling approach is being developed, generating an open simulation platform able to exhibit the comparative benefits of several market design options. This report constitutes delivery 3.1 on the assumptions on accuracy of wind power to be considered at short and long term horizons. The report handles the issues of state-of-the-art prediction, how predictions for wind power enter into the Optimate model and a simple and a more advanced methodology of how to generate trajectories of prediction errors to be used in Optimate. The main conclusion is that undoubtedly, the advanced approach is to be preferred to the simple one seen from a theoretical viewpoint. However, the advanced approach was developed to the Wilmar-model with the purpose of describing the integration of large-scale wind power in Europe. As the main purpose of the Optimate model is not to test the integration of wind power, but to test new market designs assuming a strong growth in wind power production, a more simplified approach for describing wind power forecasts should be sufficient. Thus a further development of the simple approach is suggested, eventually including correlations between geographical areas. In this report the general methodologies for generating trajectories for wind power forecasts are outlined. However, the methods are not yet implemented. In the next phase of Optimate, the clusters will be defined and the needed data collected. Following this phase actual results will be generated to be used in Optimate. (LN)

Wind power forecasting accuracy and uncertainty in Finland

Energy Technology Data Exchange (ETDEWEB)

Holttinen, H.; Miettinen, J.; Sillanpaeae, S.

2013-04-15

forecasts for short horizons like the following hour, more advanced combining techniques than simple average, such as Kalmar filtering or recursive least squares provided better results. Two different uncertainty quantification methods, based on empirical cumulative density function and kernel densities, were analysed for 3 sites. Aggregation of wind power production will not only decrease relative prediction errors, but also decreases the variation and uncertainty of prediction errors. (orig.)

Parity horizons in shape dynamics

International Nuclear Information System (INIS)

Herczeg, Gabriel

2016-01-01

I introduce the notion of a parity horizon, and show that many simple solutions of shape dynamics possess them. I show that the event horizons of the known asymptotically flat black hole solutions of shape dynamics are parity horizons and that this notion of parity implies that these horizons possess a notion of CPT invariance that can in some cases be extended to the solution as a whole. I present three new solutions of shape dynamics with parity horizons and find that not only do event horizons become parity horizons in shape dynamics, but observer-dependent horizons and Cauchy horizons do as well. The fact that Cauchy horizons become (singular) parity horizons suggests a general chronology protection mechanism in shape dynamics that prevents the formation of closed timelike curves. (paper)

Why do couples discontinue unlimited free IVF treatments?

Science.gov (United States)

Lande, Yechezkel; Seidman, Daniel S; Maman, Ettie; Baum, Micha; Hourvitz, Ariel

2015-03-01

Worldwide, IVF is often discontinued before a live birth is achieved due to high costs. Even when partial financial coverage is provided, often medical providers advise treatment discontinuation. In Israel, unlimited IVF is offered free of charge for a couples' first two children. Our objective was to assess the reasons couples discontinue IVF treatments before achieving two children in a completely unlimited cost-free environment. This cohort study included all primary infertile women, reason they ceased treatments. Of the 134 couples included, only 46 ceased IVF treatments without achieving two children, after performing an average of 6.2 IVF cycles to achieve their first birth. The reasons given were: lost hope of success (13), psychological burden (18), divorce (6), medical staff recommendation (5), bureaucratic difficulties (3) and general medical condition (1). The main reasons for "drop out" in our cost-free environment were as follows: psychological burden and lost hope of success. Due to high availability of treatments, medical staff recommendation was a less significant factor in our study.

Probabilistic Forecasting of the Wave Energy Flux

DEFF Research Database (Denmark)

Pinson, Pierre; Reikard, G.; Bidlot, J.-R.

2012-01-01

Wave energy will certainly have a significant role to play in the deployment of renewable energy generation capacities. As with wind and solar, probabilistic forecasts of wave power over horizons of a few hours to a few days are required for power system operation as well as trading in electricit......% and 70% in terms of Continuous Rank Probability Score (CRPS), depending upon the test case and the lead time. It is finally shown that the log-Normal assumption can be seen as acceptable, even though it may be refined in the future....

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

Directory of Open Access Journals (Sweden)

S. W. D. Turner

2017-09-01

Full Text Available Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

The Determinants of Sell-side Analysts’ Forecast Accuracy and Media Exposure

Directory of Open Access Journals (Sweden)

Samira Amadu Sorogho

2017-09-01

Full Text Available This study examines contributing factors to the differential forecasting abilities of sell-side analysts and the relation between the sentiments of these analysts and their media exposure. In particular, I investigate whether the level of optimism expressed in sell-side analysts’ reports of fifteen constituents of primarily the S&P 500 Oil and Gas Industry1, enhance the media appearance of these analysts. Using a number of variables estimated from the I/B/E/S Detail history database, 15,455 analyst reports collected from Thompson Reuters Investext and analyst media appearances obtained from Dow Jones Factiva from 1999 to 2014, I run a multiple linear regression to determine the effect of independent variables on dependent variables.  I find that an analyst’s forecast accuracy (as measured by the errors inherent in his forecasts is negatively associated with the analyst’s level of media exposure, experience, brokerage size, the number of times he revises his forecasts in a year and the number of companies followed by the analyst, and positively associated with the analyst’s level of optimism expressed in his reports, forecast horizon and the size of the company he follows.

Load Forecasting in Electric Utility Integrated Resource Planning

Energy Technology Data Exchange (ETDEWEB)

Carvallo, Juan Pablo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Larsen, Peter H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sanstad, Alan H [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goldman, Charles A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2017-07-19

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.

Operational water management of Rijnland water system and pilot of ensemble forecasting system for flood control

Science.gov (United States)

van der Zwan, Rene

2013-04-01

The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water

Against all odds -- Probabilistic forecasts and decision making

Science.gov (United States)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

International Nuclear Information System (INIS)

Trapero, Juan R.; Kourentzes, Nikolaos; Martin, A.

2015-01-01

Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1–24 h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 h ahead. - Highlights: • Solar irradiation forecasts at short-term are required to operate solar power plants. • This paper assesses the Dynamic Harmonic Regression to forecast solar irradiation. • Models are evaluated using hourly GHI and DNI data collected in Spain. • The results show that forecasting accuracy is improved by using the model proposed

Methodology and forecast products for the optimal offering of ancillary services from wind in a market environment

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Pinson, Pierre

. This enables the estimation of return levels below which the extreme wind power forecast error events occur only at a specified rate, e.g. once a month or once every year. The techniques allows extrapolation beyond the available data period. In the study data from 1.5 years is used. It consists of hourly wind...... power production in the two regions of Denmark (DK1 and DK2) and corresponding wind power forecasts. The wind power forecasts are generated using the software WPPT and are based on the outcome of three numerical weather prediction models. They cover horizons from 1 to 42 hours ahead in time...

Forecasting daily patient volumes in the emergency department.

Science.gov (United States)

Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L

2008-02-01

Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by

Electricity price forecasting in deregulated markets: A review and evaluation

Energy Technology Data Exchange (ETDEWEB)

Aggarwal, Sanjeev Kumar; Saini, Lalit Mohan; Kumar, Ashwani [Department of Electrical Engineering, National Institute of Technology, Kurukshetra, Haryana (India)

2009-01-15

The main methodologies used in electricity price forecasting have been reviewed in this paper. The following price-forecasting techniques have been covered: (i) stochastic time series, (ii) causal models, and (iii) artificial intelligence based models. The quantitative analysis of the work done by various authors has been presented based on (a) time horizon for prediction, (b) input variables, (c) output variables, (d) results, (e) data points used for analysis, (f) preprocessing technique employed, and (g) architecture of the model. The results have been presented in the form of tables for ease of comparison. Classification of various price-influencing factors used by different researchers has been done and put for reference. Application of various models as applied to different electricity markets is also presented for consideration. (author)

Electricity price forecasting in deregulated markets: A review and evaluation

International Nuclear Information System (INIS)

Aggarwal, Sanjeev Kumar; Saini, Lalit Mohan; Kumar, Ashwani

2009-01-01

The main methodologies used in electricity price forecasting have been reviewed in this paper. The following price-forecasting techniques have been covered: (i) stochastic time series, (ii) causal models, and (iii) artificial intelligence based models. The quantitative analysis of the work done by various authors has been presented based on (a) time horizon for prediction, (b) input variables, (c) output variables, (d) results, (e) data points used for analysis, (f) preprocessing technique employed, and (g) architecture of the model. The results have been presented in the form of tables for ease of comparison. Classification of various price-influencing factors used by different researchers has been done and put for reference. Application of various models as applied to different electricity markets is also presented for consideration. (author)

Short-term forecasts of district heating load and outdoor temperature by use of on-line connected computers; Korttidsprognoser foer fjaerrvaermelast och utetemperatur med on-linekopplade datorer

Energy Technology Data Exchange (ETDEWEB)

Malmstroem, B; Ernfors, P; Nilsson, Daniel; Vallgren, H [Chalmers Tekniska Hoegskola, Goeteborg (Sweden). Institutionen foer Energiteknik

1996-10-01

In this report the available methods for forecasting weather and district heating load have been studied. A forecast method based on neural networks has been tested against the more common statistical methods. The accuracy of the weather forecasts from the SMHI (Swedish Meteorological and Hydrological Institute) has been estimated. In connection with these tests, the possibilities of improving the forecasts by using on-line connected computers has been analysed. The most important results from the study are: Energy company staff generally look upon the forecasting of district heating load as a problem of such a magnitude that computer support is needed. At the companies where computer calculated forecasts are in use, their accuracy is regarded as quite satisfactory; The interest in computer produced load forecasts among energy company staff is increasing; At present, a sufficient number of commercial suppliers of weather forecasts as well as load forecasts is available to fulfill the needs of energy companies; Forecasts based on neural networks did not attain any precision improvement in comparison to more traditional statistical methods. There may though be other types of neural networks, not tested in this study, that are possibly capable of improving the forecast precision; Forecasts of outdoor temperature and district heating load can be significantly improved through the use of on-line-connected computers supplied with instantaneous measurements of temperature and load. This study shows that a general reduction of the load prediction errors by approximately 15% is attainable. For short time horizons (less than 5 hours), more extensive load prediction error reductions can be reached. For the 1-hour time horizon, the possible reduction amounts to up to 50%. 21 refs, 4 figs, 7 appendices

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 ...

A Comparison of forecasting Volatility startegies into ARCH Class throughPricing

OpenAIRE

Marzia Freo

2003-01-01

Daily data on the German market index return are used to consider multiple issues in a forecasting comparison of ARCH-type specifications. first, attention is paid to the impact of different sample sizez, different horizons and fitting of historical versus implied data. Secondly, the issue of volatility transmission is addressed by modelling French and Germany market indexes into simultaneous conditionally heteroskedasticity framework. Errors obtained by updating the Black and Scholes formula...

On-line quantile regression in the RKHS (Reproducing Kernel Hilbert Space) for operational probabilistic forecasting of wind power

International Nuclear Information System (INIS)

Gallego-Castillo, Cristobal; Bessa, Ricardo; Cavalcante, Laura; Lopez-Garcia, Oscar

2016-01-01

Wind power probabilistic forecast is being used as input in several decision-making problems, such as stochastic unit commitment, operating reserve setting and electricity market bidding. This work introduces a new on-line quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. Its application to the field of wind power forecasting involves a discussion on the choice of the bias term of the quantile models, and the consideration of the operational framework in order to mimic real conditions. Benchmark against linear and splines quantile regression models was performed for a real case study during a 18 months period. Model parameter selection was based on k-fold crossvalidation. Results showed a noticeable improvement in terms of calibration, a key criterion for the wind power industry. Modest improvements in terms of Continuous Ranked Probability Score (CRPS) were also observed for prediction horizons between 6 and 20 h ahead. - Highlights: • New online quantile regression model based on the Reproducing Kernel Hilbert Space. • First application to operational probabilistic wind power forecasting. • Modest improvements of CRPS for prediction horizons between 6 and 20 h ahead. • Noticeable improvements in terms of Calibration due to online learning.

Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model

Directory of Open Access Journals (Sweden)

Juan Du

2018-05-01

Full Text Available In this paper, we propose a novel forecast method which addresses the difficulty in short-term solar irradiance forecasting that arises due to rapidly evolving environmental factors over short time periods. This involves the forecasting of Global Horizontal Irradiance (GHI that combines prediction sky images with a Radiative Transfer Model (RTM. The prediction images (up to 10 min ahead are produced by a non-local optical flow method, which is used to calculate the cloud motion for each pixel, with consecutive sky images at 1 min intervals. The Direct Normal Irradiance (DNI and the diffuse radiation intensity field under clear sky and overcast conditions obtained from the RTM are then mapped to the sky images. Through combining the cloud locations on the prediction image with the corresponding instance of image-based DNI and diffuse radiation intensity fields, the GHI can be quantitatively forecasted for time horizons of 1–10 min ahead. The solar forecasts are evaluated in terms of root mean square error (RMSE and mean absolute error (MAE in relation to in-situ measurements and compared to the performance of the persistence model. The results of our experiment show that GHI forecasts using the proposed method perform better than the persistence model.

Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty

Directory of Open Access Journals (Sweden)

Zhongwen Li

2016-06-01

Full Text Available Microgrids (MGs are presented as a cornerstone of smart grids. With the potential to integrate intermittent renewable energy sources (RES in a flexible and environmental way, the MG concept has gained even more attention. Due to the randomness of RES, load, and electricity price in MG, the forecast errors of MGs will affect the performance of the power scheduling and the operating cost of an MG. In this paper, a combined stochastic programming and receding horizon control (SPRHC strategy is proposed for microgrid energy management under uncertainty, which combines the advantages of two-stage stochastic programming (SP and receding horizon control (RHC strategy. With an SP strategy, a scheduling plan can be derived that minimizes the risk of uncertainty by involving the uncertainty of MG in the optimization model. With an RHC strategy, the uncertainty within the MG can be further compensated through a feedback mechanism with the lately updated forecast information. In our approach, a proper strategy is also proposed to maintain the SP model as a mixed integer linear constrained quadratic programming (MILCQP problem, which is solvable without resorting to any heuristics algorithms. The results of numerical experiments explicitly demonstrate the superiority of the proposed strategy for both island and grid-connected operating modes of an MG.

A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation

Directory of Open Access Journals (Sweden)

Yuan-Kang Wu

2014-01-01

Full Text Available The increasing use of solar power as a source of electricity has led to increased interest in forecasting its power output over short-time horizons. Short-term forecasts are needed for operational planning, switching sources, programming backup, reserve usage, and peak load matching. However, the output of a photovoltaic (PV system is influenced by irradiation, cloud cover, and other weather conditions. These factors make it difficult to conduct short-term PV output forecasting. In this paper, an experimental database of solar power output, solar irradiance, air, and module temperature data has been utilized. It includes data from the Green Energy Office Building in Malaysia, the Taichung Thermal Plant of Taipower, and National Penghu University. Based on the historical PV power and weather data provided in the experiment, all factors that influence photovoltaic-generated energy are discussed. Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output. They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm. Forecasting results show the high precision and efficiency of this combination model. Therefore, the proposed model is suitable for ensuring the stable operation of a photovoltaic generation system.

The Next Level in Automated Solar Flare Forecasting: the EU FLARECAST Project

Science.gov (United States)

Georgoulis, M. K.; Bloomfield, D.; Piana, M.; Massone, A. M.; Gallagher, P.; Vilmer, N.; Pariat, E.; Buchlin, E.; Baudin, F.; Csillaghy, A.; Soldati, M.; Sathiapal, H.; Jackson, D.; Alingery, P.; Argoudelis, V.; Benvenuto, F.; Campi, C.; Florios, K.; Gontikakis, C.; Guennou, C.; Guerra, J. A.; Kontogiannis, I.; Latorre, V.; Murray, S.; Park, S. H.; Perasso, A.; Sciacchitano, F.; von Stachelski, S.; Torbica, A.; Vischi, D.

2017-12-01

We attempt an informative description of the Flare Likelihood And Region Eruption Forecasting (FLARECAST) project, European Commission's first large-scale investment to explore the limits of reliability and accuracy achieved for the forecasting of major solar flares. We outline the consortium, top-level objectives and first results of the project, highlighting the diversity and fusion of expertise needed to deliver what was promised. The project's final product, featuring an openly accessible, fully modular and free to download flare forecasting facility will be delivered in early 2018. The project's three objectives, namely, science, research-to-operations and dissemination / communication, are also discussed: in terms of science, we encapsulate our close-to-final assessment on how close (or far) are we from a practically exploitable solar flare forecasting. In terms of R2O, we briefly describe the architecture of the FLARECAST infrastructure that includes rigorous validation for each forecasting step. From the three different communication levers of the project we finally focus on lessons learned from the two-way interaction with the community of stakeholders and governmental organizations. The FLARECAST project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 640216.

Impact of onsite solar generation on system load demand forecast

International Nuclear Information System (INIS)

Kaur, Amanpreet; Pedro, Hugo T.C.; Coimbra, Carlos F.M.

2013-01-01

Highlights: • We showed the impact onsite solar generation on system demand load forecast. • Forecast performance degrades by 9% and 3% for 1 h and 15 min forecast horizons. • Error distribution for onsite case is best characterized as t-distribution. • Relation between error, solar penetration and solar variability is characterized. - Abstract: Net energy metering tariffs have encouraged the growth of solar PV in the distribution grid. The additional variability associated with weather-dependent renewable energy creates new challenges for power system operators that must maintain and operate ancillary services to balance the grid. To deal with these issues power operators mostly rely on demand load forecasts. Electric load forecast has been used in power industry for a long time and there are several well established load forecasting models. But the performance of these models for future scenario of high renewable energy penetration is unclear. In this work, the impact of onsite solar power generation on the demand load forecast is analyzed for a community that meets between 10% and 15% of its annual power demand and 3–54% of its daily power demand from a solar power plant. Short-Term Load Forecasts (STLF) using persistence, machine learning and regression-based forecasting models are presented for two cases: (1) high solar penetration and (2) no penetration. Results show that for 1-h and 15-min forecasts the accuracy of the models drops by 9% and 3% with high solar penetration. Statistical analysis of the forecast errors demonstrate that the error distribution is best characterized as a t-distribution for the high penetration scenario. Analysis of the error distribution as a function of daily solar penetration for different levels of variability revealed that the solar power variability drives the forecast error magnitude whereas increasing penetration level has a much smaller contribution. This work concludes that the demand forecast error distribution

Mechanics of apparent horizons

International Nuclear Information System (INIS)

Collins, W.

1992-01-01

An equation for the variation in the surface area of an apparent horizon is derived which has the same form as the thermodynamic relation TdS=dQ. For a stationary vacuum black hole, the expression corresponding to a temperature equals the temperature of the event horizon. Also, if the black hole is perturbed infinitesimally by weak matter and gravitational fields, the area variation of the apparent horizon asymptotically approaches the Hartle-Hawking result for the event horizon. These results support the idea that a local version of black-hole thermodynamics in nonstationary systems can be constructed for apparent horizons

Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

DEFF Research Database (Denmark)

Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

SOLAR PHOTOVOLTAIC OUTPUT POWER FORECASTING USING BACK PROPAGATION NEURAL NETWORK

Directory of Open Access Journals (Sweden)

B. Jency Paulin

2016-01-01

Full Text Available Solar Energy is an important renewable and unlimited source of energy. Solar photovoltaic power forecasting, is an estimation of the expected power production, that help the grid operators to better manage the electric balance between power demand and supply. Neural network is a computational model that can predict new outcomes from past trends. The artificial neural network is used for photovoltaic plant energy forecasting. The output power for solar photovoltaic cell is predicted on hourly basis. In historical dataset collection process, two dataset was collected and used for analysis. The dataset was provided with three independent attributes and one dependent attributes. The implementation of Artificial Neural Network structure is done by Multilayer Perceptron (MLP and training procedure for neural network is done by error Back Propagation (BP. In order to train and test the neural network, the datasets are divided in the ratio 70:30. The accuracy of prediction can be done by using various error measurement criteria and the performance of neural network is to be noted.

Robust Building Energy Load Forecasting Using Physically-Based Kernel Models

Directory of Open Access Journals (Sweden)

Anand Krishnan Prakash

2018-04-01

Full Text Available Robust and accurate building energy load forecasting is important for helping building managers and utilities to plan, budget, and strategize energy resources in advance. With recent prevalent adoption of smart-meters in buildings, a significant amount of building energy consumption data became available. Many studies have developed physics-based white box models and data-driven black box models to predict building energy consumption; however, they require extensive prior knowledge about building system, need a large set of training data, or lack robustness to different forecasting scenarios. In this paper, we introduce a new building energy forecasting method based on Gaussian Process Regression (GPR that incorporates physical insights about load data characteristics to improve accuracy while reducing training requirements. The GPR is a non-parametric regression method that models the data as a joint Gaussian distribution with mean and covariance functions and forecast using the Bayesian updating. We model the covariance function of the GPR to reflect the data patterns in different forecasting horizon scenarios, as prior knowledge. Our method takes advantage of the modeling flexibility and computational efficiency of the GPR while benefiting from the physical insights to further improve the training efficiency and accuracy. We evaluate our method with three field datasets from two university campuses (Carnegie Mellon University and Stanford University for both short- and long-term load forecasting. The results show that our method performs more accurately, especially when the training dataset is small, compared to other state-of-the-art forecasting models (up to 2.95 times smaller prediction error.

Forecasting ocean wave energy: A Comparison of the ECMWF wave model with time series methods

DEFF Research Database (Denmark)

Reikard, Gordon; Pinson, Pierre; Bidlot, Jean

2011-01-01

Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several...... days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts...... (ECMWF) Wave Model, and two statistical techniques, time-varying parameter regressions and neural networks. Thirteen data sets at locations in the Atlantic and Pacific Oceans and the Gulf of Mexico are tested. The quantities to be predicted are the significant wave height, the wave period, and the wave...

Do we need demographic data to forecast plant population dynamics?

Science.gov (United States)

Tredennick, Andrew T.; Hooten, Mevin B.; Adler, Peter B.

2017-01-01

Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist

Recursive wind speed forecasting based on Hammerstein Auto-Regressive model

International Nuclear Information System (INIS)

Ait Maatallah, Othman; Achuthan, Ajit; Janoyan, Kerop; Marzocca, Pier

2015-01-01

Highlights: • Developed a new recursive WSF model for 1–24 h horizon based on Hammerstein model. • Nonlinear HAR model successfully captured chaotic dynamics of wind speed time series. • Recursive WSF intrinsic error accumulation corrected by applying rotation. • Model verified for real wind speed data from two sites with different characteristics. • HAR model outperformed both ARIMA and ANN models in terms of accuracy of prediction. - Abstract: A new Wind Speed Forecasting (WSF) model, suitable for a short term 1–24 h forecast horizon, is developed by adapting Hammerstein model to an Autoregressive approach. The model is applied to real data collected for a period of three years (2004–2006) from two different sites. The performance of HAR model is evaluated by comparing its prediction with the classical Autoregressive Integrated Moving Average (ARIMA) model and a multi-layer perceptron Artificial Neural Network (ANN). Results show that the HAR model outperforms both the ARIMA model and ANN model in terms of root mean square error (RMSE), mean absolute error (MAE), and Mean Absolute Percentage Error (MAPE). When compared to the conventional models, the new HAR model can better capture various wind speed characteristics, including asymmetric (non-gaussian) wind speed distribution, non-stationary time series profile, and the chaotic dynamics. The new model is beneficial for various applications in the renewable energy area, particularly for power scheduling

Revisiting event horizon finders

International Nuclear Information System (INIS)

Cohen, Michael I; Pfeiffer, Harald P; Scheel, Mark A

2009-01-01

Event horizons are the defining physical features of black hole spacetimes, and are of considerable interest in studying black hole dynamics. Here, we reconsider three techniques to find event horizons in numerical spacetimes: integrating geodesics, integrating a surface, and integrating a level-set of surfaces over a volume. We implement the first two techniques and find that straightforward integration of geodesics backward in time is most robust. We find that the exponential rate of approach of a null surface towards the event horizon of a spinning black hole equals the surface gravity of the black hole. In head-on mergers we are able to track quasi-normal ringing of the merged black hole through seven oscillations, covering a dynamic range of about 10 5 . Both at late times (when the final black hole has settled down) and at early times (before the merger), the apparent horizon is found to be an excellent approximation of the event horizon. In the head-on binary black hole merger, only some of the future null generators of the horizon are found to start from past null infinity; the others approach the event horizons of the individual black holes at times far before merger.

On unlimited frontiers

International Nuclear Information System (INIS)

Graham, J.

1985-01-01

The political system in the United States in unique because our forefathers planned it that way. Unfortunately, this uniqueness does not always serve the interest of those who advocate large nuclear-power facilities and fuel-cycle activities involving reprocessing and breeder reactors. The influence of various political systems on the viability of the nuclear-power option is discussed. As it faces the future, the U.S. nuclear community is divided over its most appropriate courses of action. The current administration is supportive in words if not in deeds, but it is ideologically opposed to advocating the conditions needed for a thriving nuclear industry based on large light water reactors. Will the U.S. enter the new century with ''unlimited frontiers'' in many new nuclear plant designs, or will some major shift in public opinion bring back political conditions that are more compatible with large LWR facilities. This is the $64,000 question confronting the nuclear industry, which must be prepared for any eventuality. The best chance for the U.S. to regain worldwide superiority in nuclear power-technology may lie in our ability to make rapid adjustments and to offer new and advanced machines that best fit utility needs and the political conditions of their own time

78 FR 54298 - Horizons ETFs Management (USA) LLC and Horizons ETF Trust; Notice of Application

Science.gov (United States)

2013-09-03

... ETFs Management (USA) LLC and Horizons ETF Trust; Notice of Application August 27, 2013. AGENCY... Management (USA) LLC (``Horizons'') and Horizons ETF Trust (the ``Trust''). Summary of Application... of the Trust will be the Horizons Active Global Dividend ETF (the ``Initial Fund''), which will seek...

HORIZON SENSING

Energy Technology Data Exchange (ETDEWEB)

Larry G. Stolarczyk

2003-03-18

With the aid of a DOE grant (No. DE-FC26-01NT41050), Stolar Research Corporation (Stolar) developed the Horizon Sensor (HS) to distinguish between the different layers of a coal seam. Mounted on mining machine cutter drums, HS units can detect or sense the horizon between the coal seam and the roof and floor rock, providing the opportunity to accurately mine the section of the seam most desired. HS also enables accurate cutting of minimum height if that is the operator's objective. Often when cutting is done out-of-seam, the head-positioning function facilitates a fixed mining height to minimize dilution. With this technology, miners can still be at a remote location, yet cut only the clean coal, resulting in a much more efficient overall process. The objectives of this project were to demonstrate the feasibility of horizon sensing on mining machines and demonstrate that Horizon Sensing can allow coal to be cut cleaner and more efficiently. Stolar's primary goal was to develop the Horizon Sensor (HS) into an enabling technology for full or partial automation or ''agile mining''. This technical innovation (R&D 100 Award Winner) is quickly demonstrating improvements in productivity and miner safety at several prominent coal mines in the United States. In addition, the HS system can enable the cutting of cleaner coal. Stolar has driven the HS program on the philosophy that cutting cleaner coal means burning cleaner coal. The sensor, located inches from the cutting bits, is based upon the physics principles of a Resonant Microstrip Patch Antenna (RMPA). When it is in proximity of the rock-coal interface, the RMPA impedance varies depending on the thickness of uncut coal. The impedance is measured by the computer-controlled electronics and then sent by radio waves to the mining machine. The worker at the machine can read the data via a Graphical User Interface, displaying a color-coded image of the coal being cut, and direct the machine

What happens at the horizon(s) of an extreme black hole?

International Nuclear Information System (INIS)

Murata, Keiju; Reall, Harvey S; Tanahashi, Norihiro

2013-01-01

A massless scalar field exhibits an instability at the event horizon of an extreme black hole. We study numerically the nonlinear evolution of this instability for spherically symmetric perturbations of an extreme Reissner–Nordstrom (RN) black hole. We find that generically the endpoint of the instability is a non-extreme RN solution. However, there exist fine-tuned initial perturbations for which the instability never decays. In this case, the perturbed spacetime describes a time-dependent extreme black hole. Such solutions settle down to extreme RN outside, but not on, the event horizon. The event horizon remains smooth but certain observers who cross it at late time experience large gradients there. Our results indicate that these dynamical extreme black holes admit a C 1 extension across an inner (Cauchy) horizon. (paper)

Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Zugno, Marco; Madsen, Henrik

2016-01-01

The increasing penetration of wind power has resulted in larger shares of volatile sources of supply in power systems worldwide. In order to operate such systems efficiently, methods for reliable probabilistic forecasts of future wind power production are essential. It is well known...... that the conditional density of wind power production is highly dependent on the level of predicted wind power and prediction horizon. This paper describes a new approach for wind power forecasting based on logistic-type stochastic differential equations (SDEs). The SDE formulation allows us to calculate both state......-dependent conditional uncertainties as well as correlation structures. Model estimation is performed by maximizing the likelihood of a multidimensional random vector while accounting for the correlation structure defined by the SDE formulation. We use non-parametric modelling to explore conditional correlation...

Spacetimes foliated by Killing horizons

International Nuclear Information System (INIS)

Pawlowski, Tomasz; Lewandowski, Jerzy; Jezierski, Jacek

2004-01-01

It seems to be expected that a horizon of a quasi-local type, such as a Killing or an isolated horizon, by analogy with a globally defined event horizon, should be unique in some open neighbourhood in the spacetime, provided the vacuum Einstein or the Einstein-Maxwell equations are satisfied. The aim of our paper is to verify whether that intuition is correct. If one can extend a so-called Kundt metric, in such a way that its null, shear-free surfaces have spherical spacetime sections, the resulting spacetime is foliated by so-called non-expanding horizons. The obstacle is Kundt's constraint induced at the surfaces by the Einstein or the Einstein-Maxwell equations, and the requirement that a solution be globally defined on the sphere. We derived a transformation (reflection) that creates a solution to Kundt's constraint out of data defining an extremal isolated horizon. Using that transformation, we derived a class of exact solutions to the Einstein or Einstein-Maxwell equations of very special properties. Each spacetime we construct is foliated by a family of the Killing horizons. Moreover, it admits another, transversal Killing horizon. The intrinsic and extrinsic geometries of the transversal Killing horizon coincide with the one defined on the event horizon of the extremal Kerr-Newman solution. However, the Killing horizon in our example admits yet another Killing vector tangent to and null at it. The geometries of the leaves are given by the reflection

Inventory model using bayesian dynamic linear model for demand forecasting

Directory of Open Access Journals (Sweden)

Marisol Valencia-Cárdenas

2014-12-01

Full Text Available An important factor of manufacturing process is the inventory management of terminated product. Constantly, industry is looking for better alternatives to establish an adequate plan of production and stored quantities, with optimal cost, getting quantities in a time horizon, which permits to define resources and logistics with anticipation, needed to distribute products on time. Total absence of historical data, required by many statistical models to forecast, demands the search for other kind of accurate techniques. This work presents an alternative that not only permits to forecast, in an adjusted way, but also, to provide optimal quantities to produce and store with an optimal cost, using Bayesian statistics. The proposal is illustrated with real data. Palabras clave: estadística bayesiana, optimización, modelo de inventarios, modelo lineal dinámico bayesiano. Keywords: Bayesian statistics, opti

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Science.gov (United States)

Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut

2016-01-01

Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Directory of Open Access Journals (Sweden)

Waddah Waheeb

Full Text Available Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN and the Dynamic Ridge Polynomial Neural Network (DRPNN. Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Forecast Based Financing for Managing Weather and Climate Risks to Reduce Potential Disaster Impacts

Science.gov (United States)

Arrighi, J.

2017-12-01

There is a critical window of time to reduce potential impacts of a disaster after a forecast for heightened risk is issued and before an extreme event occurs. The concept of Forecast-based Financing focuses on this window of opportunity. Through advanced preparation during system set-up, tailored methodologies are used to 1) analyze a range of potential extreme event forecasts, 2) identify emergency preparedness measures that can be taken when factoring in forecast lead time and inherent uncertainty and 3) develop standard operating procedures that are agreed on and tied to guaranteed funding sources to facilitate emergency measures led by the Red Cross or government actors when preparedness measures are triggered. This presentation will focus on a broad overview of the current state of theory and approaches used in developing a forecast-based financing systems - with a specific focus on hydrologic events, case studies of success and challenges in various contexts where this approach is being piloted, as well as what is on the horizon to be further explored and developed from a research perspective as the application of this approach continues to expand.

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

Zero-sum bias: perceived competition despite unlimited resources.

Science.gov (United States)

Meegan, Daniel V

2010-01-01

Zero-sum bias describes intuitively judging a situation to be zero-sum (i.e., resources gained by one party are matched by corresponding losses to another party) when it is actually non-zero-sum. The experimental participants were students at a university where students' grades are determined by how the quality of their work compares to a predetermined standard of quality rather than to the quality of the work produced by other students. This creates a non-zero-sum situation in which high grades are an unlimited resource. In three experiments, participants were shown the grade distribution after a majority of the students in a course had completed an assigned presentation, and asked to predict the grade of the next presenter. When many high grades had already been given, there was a corresponding increase in low grade predictions. This suggests a zero-sum bias, in which people perceive a competition for a limited resource despite unlimited resource availability. Interestingly, when many low grades had already been given, there was not a corresponding increase in high grade predictions. This suggests that a zero-sum heuristic is only applied in response to the allocation of desirable resources. A plausible explanation for the findings is that a zero-sum heuristic evolved as a cognitive adaptation to enable successful intra-group competition for limited resources. Implications for understanding inter-group interaction are also discussed.

Dealing with rainfall forecast uncertainties in real-time flood control along the Demer river

Directory of Open Access Journals (Sweden)

Vermuyten Evert

2016-01-01

Full Text Available Real-time Model Predictive Control (MPC of hydraulic structures strongly reduces flood consequences under ideal circumstances. The performance of such flood control may, however, be significantly affected by uncertainties. This research quantifies the influence of rainfall forecast uncertainties and related uncertainties in the catchment rainfall-runoff discharges on the control performance for the Herk river case study in Belgium. To limit the model computational times, a fast conceptual model is applied. It is calibrated to a full hydrodynamic river model. A Reduced Genetic Algorithm is used as optimization method. Next to the analysis of the impact of the rainfall forecast uncertainties on the control performance, a Multiple Model Predictive Control (MMPC approach is tested to reduce this impact. Results show that the deterministic MPC-RGA outperforms the MMPC and that it is inherently robust against rainfall forecast uncertainties due to its receding horizon strategy.

Forecasting method for global radiation time series without training phase: Comparison with other well-known prediction methodologies

International Nuclear Information System (INIS)

Voyant, Cyril; Motte, Fabrice; Fouilloy, Alexis; Notton, Gilles; Paoli, Christophe; Nivet, Marie-Laure

2017-01-01

Integration of unpredictable renewable energy sources into electrical networks intensifies the complexity of the grid management due to their intermittent and unforeseeable nature. Because of the strong increase of solar power generation the prediction of solar yields becomes more and more important. Electrical operators need an estimation of the future production. For nowcasting and short term forecasting, the usual technics based on machine learning need large historical data sets of good quality during the training phase of predictors. However data are not always available and induce an advanced maintenance of meteorological stations, making the method inapplicable for poor instrumented or isolated sites. In this work, we propose intuitive methodologies based on the Kalman filter use (also known as linear quadratic estimation), able to predict a global radiation time series without the need of historical data. The accuracy of these methods is compared to other classical data driven methods, for different horizons of prediction and time steps. The proposed approach shows interesting capabilities allowing to improve quasi-systematically the prediction. For one to 10 h horizons Kalman model performances are competitive in comparison to more sophisticated models such as ANN which require both consistent historical data sets and computational resources. - Highlights: • Solar radiation forecasting with time series formalism. • Trainless approach compared to machine learning methods. • Very simple method dedicated to solar irradiation forecasting with high accuracy.

A Forward-looking Model of the Term Structure of Interest Rates

DEFF Research Database (Denmark)

Chun, Albert Lee

of the forecasts are modeled jointly with the physical process driving their realizations. We extend this framework to allow for multiple-horizon forecasts to drive the short rate, yielding its novel interpretation as a forward-looking multiple-horizon monetary policy rule, which facilitates a decomposition...... of monetary policy and the yield curve into short and long horizon expectations. While short horizon forecasts can pin down the short rate, long horizon forecasts embed information that better describes longer maturity yields. In addition, short horizon forecasts of real output growth are obscured...

Cosmological and black hole apparent horizons

CERN Document Server

Faraoni, Valerio

2015-01-01

This book overviews the extensive literature on apparent cosmological and black hole horizons. In theoretical gravity, dynamical situations such as gravitational collapse, black hole evaporation, and black holes interacting with non-trivial environments, as well as the attempts to model gravitational waves occurring in highly dynamical astrophysical processes, require that the concept of event horizon be generalized. Inequivalent notions of horizon abound in the technical literature and are discussed in this manuscript. The book begins with a quick review of basic material in the first one and a half chapters, establishing a unified notation. Chapter 2 reminds the reader of the basic tools used in the analysis of horizons and reviews the various definitions of horizons appearing in the literature. Cosmological horizons are the playground in which one should take baby steps in understanding horizon physics. Chapter 3 analyzes cosmological horizons, their proposed thermodynamics, and several coordinate systems....

Conformal Killing horizons and their thermodynamics

Science.gov (United States)

Nielsen, Alex B.; Shoom, Andrey A.

2018-05-01

Certain dynamical black hole solutions can be mapped to static spacetimes by conformal metric transformations. This mapping provides a physical link between the conformal Killing horizon of the dynamical black hole and the Killing horizon of the static spacetime. Using the Vaidya spacetime as an example, we show how this conformal relation can be used to derive thermodynamic properties of such dynamical black holes. Although these horizons are defined quasi-locally and can be located by local experiments, they are distinct from other popular notions of quasi-local horizons such as apparent horizons. Thus in the dynamical Vaidya spacetime describing constant accretion of null dust, the conformal Killing horizon, which is null by construction, is the natural horizon to describe the black hole.

Spacetimes containing slowly evolving horizons

International Nuclear Information System (INIS)

Kavanagh, William; Booth, Ivan

2006-01-01

Slowly evolving horizons are trapping horizons that are ''almost'' isolated horizons. This paper reviews their definition and discusses several spacetimes containing such structures. These include certain Vaidya and Tolman-Bondi solutions as well as (perturbatively) tidally distorted black holes. Taking into account the mass scales and orders of magnitude that arise in these calculations, we conjecture that slowly evolving horizons are the norm rather than the exception in astrophysical processes that involve stellar-scale black holes

Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models

Directory of Open Access Journals (Sweden)

Hojin Lee

2009-12-01

Full Text Available We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast. Contrary to prior evidence, however, the results in this paper suggest that no asymmetric GARCH model is superior to basic GARCH(1,1 model. It is our prior knowledge that, for equity returns, it is unlikely that positive and negative shocks have the same impact on the volatility. In order to reflect this intuition, we implement three diagnostic tests for volatility models: the Sign Bias Test, the Negative Size Bias Test, and the Positive Size Bias Test and the tests against the alternatives of QGARCH and GJR-GARCH. The asymmetry test results indicate that the sign and the size of the unexpected return shock do not influence current volatility differently which contradicts our presumption that there are asymmetric effects in the stock market volatility. This result is in line with various diagnostic tests which are designed to determine whether the GARCH(1,1 volatility estimates adequately represent the data. The diagnostic tests in section 2 indicate that the GARCH(1,1 model for weekly KOSPI returns is robust to the misspecification test. We also investigate two representative asymmetric GARCH models, QGARCH and GJR-GARCH model, for our out-of-sample forecasting performance. The out-of-sample forecasting ability test reveals that no single model is clearly outperforming. It is seen that the GJR-GARCH and QGARCH model give mixed results in forecasting ability on all four criteria across all forecast horizons considered. Also, the predictive accuracy test of Diebold and Mariano based on both absolute and squared prediction errors suggest that the forecasts from the linear and asymmetric GARCH models need not be significantly different from each other.

Predicting the Heat Consumption in District Heating Systems using Meteorological Forecasts

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg, orlov 31.07.2008; Madsen, Henrik

that meteorological forecasts are available on-line. Such a service has recently been introduced by the Danish Meteorological Institute. However, actual meteorological forecasts has not been available for the work described here. Assuming the climate to be known the mean absolute relative prediction error for 72 hour......Methods for on-line prediction of heat consumption in district heating systems hour by hour for horizons up to 72 hours are considered in this report. Data from the district heating system Vestegnens Kraftvarmeselskab I/S is used in the investigation. During the development it has been assumed......, this is somewhat contrary to practice. The work presented is a demonstration of the value of the so called gray box approach where theoretical knowledge about the system under consideration is combined with information from measurements performed on the system in order to obtain a mathematical description...

Simulating surface oil transport during the Deepwater Horizon oil spill: Experiments with the BioCast system

Science.gov (United States)

Jolliff, Jason Keith; Smith, Travis A.; Ladner, Sherwin; Arnone, Robert A.

2014-03-01

The U.S. Naval Research Laboratory (NRL) is developing nowcast/forecast software systems designed to combine satellite ocean color data streams with physical circulation models in order to produce prognostic fields of ocean surface materials. The Deepwater Horizon oil spill in the Gulf of Mexico provided a test case for the Bio-Optical Forecasting (BioCast) system to rapidly combine the latest satellite imagery of the oil slick distribution with surface circulation fields in order to produce oil slick transport scenarios and forecasts. In one such sequence of experiments, MODIS satellite true color images were combined with high-resolution ocean circulation forecasts from the Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS®) to produce 96-h oil transport simulations. These oil forecasts predicted a major oil slick landfall at Grand Isle, Louisiana, USA that was subsequently observed. A key driver of the landfall scenario was the development of a coastal buoyancy current associated with Mississippi River Delta freshwater outflow. In another series of experiments, longer-term regional circulation model results were combined with oil slick source/sink scenarios to simulate the observed containment of surface oil within the Gulf of Mexico. Both sets of experiments underscore the importance of identifying and simulating potential hydrodynamic conduits of surface oil transport. The addition of explicit sources and sinks of surface oil concentrations provides a framework for increasingly complex oil spill modeling efforts that extend beyond horizontal trajectory analysis.

Examples of plasma horizons

International Nuclear Information System (INIS)

Hanni, R.S.

1975-01-01

The concept of the plasma horizon, defined as the boundary of the region in which an infinitely thin plasma can be supported against Coulomb attraction by a magnetic field, shows that the argument of selective accretion does not rule out the existence of charged black holes embedded in a conducting plasma. A detailed account of the covariant definition of plasma horizon is given and some examples of plasma horizons are presented. 7 references

Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California: A Framework for Objectively Leveraging Weather and Climate Forecasts in a Decision Support Environment

Science.gov (United States)

Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.

2017-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.

Solar Resource Assessment with Sky Imagery and a Virtual Testbed for Sky Imager Solar Forecasting

Science.gov (United States)

Kurtz, Benjamin Bernard

In recent years, ground-based sky imagers have emerged as a promising tool for forecasting solar energy on short time scales (0 to 30 minutes ahead). Following the development of sky imager hardware and algorithms at UC San Diego, we present three new or improved algorithms for sky imager forecasting and forecast evaluation. First, we present an algorithm for measuring irradiance with a sky imager. Sky imager forecasts are often used in conjunction with other instruments for measuring irradiance, so this has the potential to decrease instrumentation costs and logistical complexity. In particular, the forecast algorithm itself often relies on knowledge of the current irradiance which can now be provided directly from the sky images. Irradiance measurements are accurate to within about 10%. Second, we demonstrate a virtual sky imager testbed that can be used for validating and enhancing the forecast algorithm. The testbed uses high-quality (but slow) simulations to produce virtual clouds and sky images. Because virtual cloud locations are known, much more advanced validation procedures are possible with the virtual testbed than with measured data. In this way, we are able to determine that camera geometry and non-uniform evolution of the cloud field are the two largest sources of forecast error. Finally, with the assistance of the virtual sky imager testbed, we develop improvements to the cloud advection model used for forecasting. The new advection schemes are 10-20% better at short time horizons.

Zero-sum bias: perceived competition despite unlimited resources

Directory of Open Access Journals (Sweden)

Daniel V Meegan

2010-11-01

Full Text Available Zero-sum bias describes intuitively judging a situation to be zero-sum (i.e., resources gained by one party are matched by corresponding losses to another party when it is actually non-zero-sum. The experimental participants were students at a university where students’ grades are determined by how the quality of their work compares to a predetermined standard of quality rather than to the quality of the work produced by other students. This creates a non-zero-sum situation in which high grades are an unlimited resource. In three experiments, participants were shown the grade distribution after a majority of the students in a course had completed an assigned presentation, and asked to predict the grade of the next presenter. When many high grades had already been given, there was a corresponding increase in low grade predictions. This suggests a zero-sum bias, in which people perceive a competition for a limited resource despite unlimited resource availability. Interestingly, when many low grades had already been given, there was not a corresponding increase in high grade predictions. This suggests that a zero-sum heuristic is only applied in response to the allocation of desirable resources. A plausible explanation for the findings is that a zero-sum heuristic evolved as a cognitive adaptation to enable successful intra-group competition for limited resources. Implications for understanding inter-group interaction are also discussed.

A supply chain contract with flexibility as a risk-sharing mechanism for demand forecasting

Science.gov (United States)

Kim, Whan-Seon

2013-06-01

Demand forecasting is one of the main causes of the bullwhip effect in a supply chain. As a countermeasure for demand uncertainty as well as a risk-sharing mechanism for demand forecasting in a supply chain, this article studies a bilateral contract with order quantity flexibility. Under the contract, the buyer places orders in advance for the predetermined horizons and makes minimum purchase commitments. The supplier, in return, provides the buyer with the flexibility to adjust the order quantities later, according to the most updated demand information. To conduct comparative simulations, four-echelon supply chain models, that employ the contracts and different forecasting techniques under dynamic market demands, are developed. The simulation outcomes show that demand fluctuation can be effectively absorbed by the contract scheme, which enables better inventory management and customer service. Furthermore, it has been verified that the contract scheme under study plays a role as an effective coordination mechanism in a decentralised supply chain.

COMPARATIVE STUDY: LIMITED LIABILITY COMPANY VERSUS UNLIMITED LIABILITY COMPANY

Directory of Open Access Journals (Sweden)

Silvia Cristea

2013-11-01

Full Text Available Our goal is to differentiate between the legal regime of the limited partnership and that of the unlimited company, by drawing a comparison between civil and special settlement in terms of the following criteria: definition, contributions, capital divisions, the Articles of Association, registration, management control, withdrawal/exclusion of a partner, dissolution/ liquidation. The opinions expressed in the chapter devoted to conclusions are relevant to Romanian and French Law as well.

A Decision Optimization Model for Leased Manufacturing Equipment with Warranty under Forecasting Production/Maintenance Problem

Directory of Open Access Journals (Sweden)

Zied Hajej

2015-01-01

Full Text Available Due to the expensive production equipment, many manufacturers usually lease production equipment with a warranty period during a finite leasing horizon, rather than purchasing them. The lease contract contains the possibility of obtaining an extended warranty for a given additional cost. In this paper, based on the forecasting production/maintenance optimization problem, we develop a mathematical model to study the lease contract with basic and extended warranty based on win-win relationship between the lessee and the lessor. The influence of the production rates in the equipment degradation consequently on the total cost by each side during the finite leasing horizon is stated in order to determine a theoretical condition under which a compromise-pricing zone exists under different possibilities of maintenance policies.

Modelling and forecasting monthly swordfish catches in the Eastern Mediterranean

Directory of Open Access Journals (Sweden)

Konstantinos I. Stergiou

2003-04-01

Full Text Available In this study, we used the X-11 census technique for modelling and forecasting the monthly swordfish (Xiphias gladius catches in the Greek Seas during 1982-1996 and 1997 respectively, using catches reported by the National Statistical Service of Greece (NSSG. Forecasts built with X-11 were also compared with those derived from ARIMA andWinter’s exponential smoothing (WES models. The X-11 method captured the features of the study series and outperformed the other two methods, in terms of both fitting and forecasting performance, for all the accuracy measures used. Thus, with the exception of October, November and December 1997, when the corresponding absolute percentage error(APE values were very high (as high as 178.6% because of the low level of the catches, monthly catches during the remaining months of 1997 were predicted accurately, with a mean APE of 12.5%. In contrast, the mean APE values of the other two methods for the same months were higher (ARIMA: 14.6%; WES: 16.6%. The overall good performance of X-11 andthe fact that it provides an insight into the various components (i.e. the seasonal, trend-cycle and irregular components of the time series of interest justify its use in fisheries research. The basic features of the swordfish catches revealed by the application of the X-11 method, the effect of the length of the forecasting horizon on forecasting accuracy and the accuracy of the catches reported by NSSG are also discussed.

Stringy horizons

Energy Technology Data Exchange (ETDEWEB)

Giveon, Amit [Racah Institute of Physics, The Hebrew University,Jerusalem 91904 (Israel); Itzhaki, Nissan [Physics Department, Tel-Aviv University,Ramat-Aviv, 69978 (Israel); Kutasov, David [EFI and Department of Physics, University of Chicago,5640 S. Ellis Av., Chicago, IL 60637 (United States)

2015-06-11

We argue that classical (α{sup ′}) effects qualitatively modify the structure of Euclidean black hole horizons in string theory. While low energy modes experience the geometry familiar from general relativity, high energy ones see a rather different geometry, in which the Euclidean horizon can be penetrated by an amount that grows with the radial momentum of the probe. We discuss this in the exactly solvable SL(2,ℝ)/U(1) black hole, where it is a manifestation of the black hole/Sine-Liouville duality.

[Medical human resources planning in Europe: A literature review of the forecasting models].

Science.gov (United States)

Benahmed, N; Deliège, D; De Wever, A; Pirson, M

2018-02-01

Healthcare is a labor-intensive sector in which half of the expenses are dedicated to human resources. Therefore, policy makers, at national and internal levels, attend to the number of practicing professionals and the skill mix. This paper aims to analyze the European forecasting model for supply and demand of physicians. To describe the forecasting tools used for physician planning in Europe, a grey literature search was done in the OECD, WHO, and European Union libraries. Electronic databases such as Pubmed, Medine, Embase and Econlit were also searched. Quantitative methods for forecasting medical supply rely mainly on stock-and-flow simulations and less often on systemic dynamics. Parameters included in forecasting models exhibit wide variability for data availability and quality. The forecasting of physician needs is limited to healthcare consumption and rarely considers overall needs and service targets. Besides quantitative methods, horizon scanning enables an evaluation of the changes in supply and demand in an uncertain future based on qualitative techniques such as semi-structured interviews, Delphi Panels, or focus groups. Finally, supply and demand forecasting models should be regularly updated. Moreover, post-hoc analyze is also needed but too rarely implemented. Medical human resource planning in Europe is inconsistent. Political implementation of the results of forecasting projections is essential to insure efficient planning. However, crucial elements such as mobility data between Member States are poorly understood, impairing medical supply regulation policies. These policies are commonly limited to training regulations, while horizontal and vertical substitution is less frequently taken into consideration. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Day-ahead load forecast using random forest and expert input selection

International Nuclear Information System (INIS)

Lahouar, A.; Ben Hadj Slama, J.

2015-01-01

Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

Forecasting the investors behavior on the capital market in Romania: Trading strategies based on technical analysis versus Artificial Intelligence techniques

Directory of Open Access Journals (Sweden)

Gabriela Victoria Anghelache

2013-07-01

The analysis of various forecasting strategies has been conducted using data sets on a daily basis, on a time horizon of nine years, for a total of 22 companies listed on BSE and for the BET and BET-C exchange indexes; the research is differentiating the pre-crisis period and the crisis period.

Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

Science.gov (United States)

Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

2016-06-01

Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand

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

Introduction of unlimited liability into the atomic law with special regard to the international nuclear liability conventions

International Nuclear Information System (INIS)

Hohlefelder, W.

1984-01-01

The paper was read at the international symposium on nuclear liability held in Munich in September 1984 by OECD/NEA and IAEA. It outlines the basic principles of the Paris liability convention and the international development. The author pleads in favour of unlimited liability for hazards on grounds of history, legal policy, legal dogmatics and practice. Moreover he thinks it useful and appropriate because it also improves the protection of the citizens. The same as the federal government the author holds that unlimited liability for hazards is compatible with the maximum damages and the congruity regulations of the Paris and Brussels liability convention. An amendment to the liability convention, though not necessary, would be desirable to make clear that both options - limited and unlimited liability - are open. (HSCH) [de

Unlimited productivity: your operation can achieve it

Energy Technology Data Exchange (ETDEWEB)

Bovino, V R

1986-10-01

Most mines substantially underestimate their real potential. The market for coal is global and people consider the problems are caused by uncontrolled production of foreign coal, however part of the problem is productivity, that is the ability to produce tons of coal in a cost-effective way, rather than production. Any operation can deliver unlimited productivity by developing the resource within their employees. This paper discusses the areas where the industry has gone wrong, including bureaucracy, blind faith in price rises, wages, adversaries; tradition, narrow job characteristics, conformance over performance for employees, management, money, self-limitations and benefit plans. It also describes three basic ways of improving productivity. These are positive management practices, employee participation and shared rewards.

Solar Radiation Forecasting, Accounting for Daily Variability

Directory of Open Access Journals (Sweden)

Roberto Langella

2016-03-01

Full Text Available Radiation forecast accounting for daily and instantaneous variability was pursued by means of a new bi-parametric statistical model that builds on a model previously proposed by the same authors. The statistical model is developed with direct reference to the Liu-Jordan clear sky theoretical expression but is not bound by a specific clear sky model; it accounts separately for the mean daily variability and for the variation of solar irradiance during the day by means of two corrective parameters. This new proposal allows for a better understanding of the physical phenomena and improves the effectiveness of statistical characterization and subsequent simulation of the introduced parameters to generate a synthetic solar irradiance time series. Furthermore, the analysis of the experimental distributions of the two parameters’ data was developed, obtaining opportune fittings by means of parametric analytical distributions or mixtures of more than one distribution. Finally, the model was further improved toward the inclusion of weather prediction information in the solar irradiance forecasting stage, from the perspective of overcoming the limitations of purely statistical approaches and implementing a new tool in the frame of solar irradiance prediction accounting for weather predictions over different time horizons.

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

Science.gov (United States)

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. Later on, post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS) were implemented into OST. These forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. This presentation will highlight the benefits of the improved forecasts using examples from actual system operations.

Entropy of black holes with multiple horizons

Science.gov (United States)

He, Yun; Ma, Meng-Sen; Zhao, Ren

2018-05-01

We examine the entropy of black holes in de Sitter space and black holes surrounded by quintessence. These black holes have multiple horizons, including at least the black hole event horizon and a horizon outside it (cosmological horizon for de Sitter black holes and "quintessence horizon" for the black holes surrounded by quintessence). Based on the consideration that the two horizons are not independent each other, we conjecture that the total entropy of these black holes should not be simply the sum of entropies of the two horizons, but should have an extra term coming from the correlations between the two horizons. Different from our previous works, in this paper we consider the cosmological constant as the variable and employ an effective method to derive the explicit form of the entropy. We also try to discuss the thermodynamic stabilities of these black holes according to the entropy and the effective temperature.

Short-term load forecast using trend information and process reconstruction

Energy Technology Data Exchange (ETDEWEB)

Santos, P.J.; Pires, A.J.; Martins, J.F. [Instituto Politecnico de Setubal (Portugal). Dept. of Electrical Engineering; Martins, A.G. [University of Coimbra (Portugal). Dept. of Electrical Engineering; Mendes, R.V. [Instituto Superior Tecnico, Lisboa (Portugal). Laboratorio de Mecatronica

2005-07-01

The algorithms for short-term load forecast (STLF), especially within the next-hour horizon, belong to a group of methodologies that aim to render more effective the actions of planning, operating and controlling electric energy systems (EES). In the context of the progressive liberalization of the electricity sector, unbundling of the previous monopolistic structure emphasizes the need for load forecast, particularly at the network level. Methodologies such as artificial neural networks (ANN) have been widely used in next-hour load forecast. Designing an ANN requires the proper choice of input variables, avoiding overfitting and an unnecessarily complex input vector (IV). This may be achieved by trying to reduce the arbitrariness in the choice of endogenous variables. At a first stage, we have applied the mathematical techniques of process-reconstruction to the underlying stochastic process, using coding and block entropies to characterize the measure and memory range. At a second stage, the concept of consumption trend in homologous days of previous weeks has been used. The possibility to include weather-related variables in the IV has also been analysed, the option finally being to establish a model of the non-weather sensitive type. The paper uses a real-life case study. (author)

Variable horizon in a peridynamic medium.

Energy Technology Data Exchange (ETDEWEB)

Silling, Stewart Andrew; Littlewood, David John; Seleson, Pablo

2014-10-01

A notion of material homogeneity is proposed for peridynamic bodies with vari- able horizon but constant bulk properties. A relation is derived that scales the force state according to the position-dependent horizon while keeping the bulk properties un- changed. Using this scaling relation, if the horizon depends on position, artifacts called ghost forces may arise in a body under homogeneous deformation. These artifacts de- pend on the second derivative of horizon and can be reduced by use of a modified equilibrium equation using a new quantity called the partial stress . Bodies with piece- wise constant horizon can be modeled without ghost forces by using a technique called a splice between the regions. As a limiting case of zero horizon, both partial stress and splice techniques can be used to achieve local-nonlocal coupling. Computational examples, including dynamic fracture in a one-dimensional model with local-nonlocal coupling, illustrate the methods.

Black hole versus cosmological horizon entropy

International Nuclear Information System (INIS)

Davis, Tamara M; Davies, P C W; Lineweaver, Charles H

2003-01-01

The generalized second law of thermodynamics states that entropy always increases when all event horizons are attributed with an entropy proportional to their area. We test the generalized second law by investigating the change in entropy when dust, radiation and black holes cross a cosmological event horizon. We generalize for flat, open and closed Friedmann-Robertson-Walker universes by using numerical calculations to determine the cosmological horizon evolution. In most cases, the loss of entropy from within the cosmological horizon is more than balanced by an increase in cosmological event horizon entropy, maintaining the validity of the generalized second law of thermodynamics. However, an intriguing set of open universe models shows an apparent entropy decrease when black holes disappear over the cosmological event horizon. We anticipate that this apparent violation of the generalized second law will disappear when solutions are available for black holes embedded in arbitrary backgrounds

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.

Neighborhoods of isolated horizons and their stationarity

International Nuclear Information System (INIS)

Lewandowski, Jerzy; Pawłowski, Tomasz

2014-01-01

A distinguished (invariant) Bondi-like coordinate system is defined in the spacetime neighborhood of a non-expanding horizon of arbitrary dimension via geometry invariants of the horizon. With its use, the radial expansion of a spacetime metric about the horizon is provided and the free data needed to specify it up to a given order are determined in spacetime dimension 4. For the case of an electro-vacuum horizon in four-dimensional spacetime, the necessary and sufficient conditions for the existence of a Killing field at its neighborhood are identified as differential conditions for the horizon data and data for the null surface transversal to the horizon. (paper)

Horizon Detection In The Visible Spectrum

Science.gov (United States)

2016-09-01

processing units, to the software-based models in [7] and [8]. B. DEFINING THE HORIZON The horizon, according to the Oxford English Dictionary , is “the...Ed. Dordrecht, Holland: D. Reidel Publishing Company, 1978. [10] “horizon,” Oxford English Dictionary Online, 2016.[Online]. Available: http

The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt

Directory of Open Access Journals (Sweden)

Cécile Viboud

2018-03-01

, and to assess model forecasting accuracy for a variety of known and hypothetical pathogens. Keywords: Ebola epidemic, Mathematical modeling, Forecasting challenge, Model comparison, Synthetic data, Prediction performance, Prediction horizon, Data accuracy

Electrodynamics of the event horizon

International Nuclear Information System (INIS)

Punsly, B.; Coroniti, F.V.

1989-01-01

This paper is an investigation of the electrodynamics of the event horizon of a Kerr black hole. It is demonstrated that the event horizon behaves quite generally as an asymptotic vacuum infinity for axisymmetric, charge-neutral, accreting electromagnetic sources. This is in contrast with the general notion that the event horizon can be treated as an imperfect conductive membrane with a surface impedance of 4π/c. The conductive-membrane model has been incorporated into the more sophisticated membrane paradigm of Thorne, Price, and Macdonald by supplementing the model with the full equations of general relativity. In certain situations (in particular those of astrophysical interest), the conductive-membrane interpretation forms the appropriate set of pictures and images in the membrane paradigm. In this paper we reevaluate the specific gedanken experiments that were originally used to motivate the paradigm. We find that great care must be exercised if the detailed interaction of a black hole's external gravitational field with a magnetized plasma is modeled by the electrodynamics of the conductive horizon membrane. For ingoing flows of plasma or electromagnetic waves (when the hole is passively accepting information), the interpretation of the horizon as a vacuum infinity is equivalent to an imperfect conductor with a surface impedance of 4π/c (the impedance of the vacuum). In situations when an imperfect conductor should radiate information (such as a Faraday wheel) the event horizon cannot, since it is an infinity. The event horizon does not behave quite generally as an imperfect conductor, but has electrodynamic properties unique to itself

Three-dimensional orientation-unlimited polarization encryption by a single optically configured vectorial beam.

Science.gov (United States)

Li, Xiangping; Lan, Tzu-Hsiang; Tien, Chung-Hao; Gu, Min

2012-01-01

The interplay between light polarization and matter is the basis of many fundamental physical processes and applications. However, the electromagnetic wave nature of light in free space sets a fundamental limit on the three-dimensional polarization orientation of a light beam. Although a high numerical aperture objective can be used to bend the wavefront of a radially polarized beam to generate the longitudinal polarization state in the focal volume, the arbitrary three-dimensional polarization orientation of a beam has not been achieved yet. Here we present a novel technique for generating arbitrary three-dimensional polarization orientation by a single optically configured vectorial beam. As a consequence, by applying this technique to gold nanorods, orientation-unlimited polarization encryption with ultra-security is demonstrated. These results represent a new landmark of the orientation-unlimited three-dimensional polarization control of the light-matter interaction.

Fiber-optical analog of the event horizon.

Science.gov (United States)

Philbin, Thomas G; Kuklewicz, Chris; Robertson, Scott; Hill, Stephen; König, Friedrich; Leonhardt, Ulf

2008-03-07

The physics at the event horizon resembles the behavior of waves in moving media. Horizons are formed where the local speed of the medium exceeds the wave velocity. We used ultrashort pulses in microstructured optical fibers to demonstrate the formation of an artificial event horizon in optics. We observed a classical optical effect: the blue-shifting of light at a white-hole horizon. We also showed by theoretical calculations that such a system is capable of probing the quantum effects of horizons, in particular Hawking radiation.

Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis

Directory of Open Access Journals (Sweden)

Zhongrong Zhang

2016-01-01

Full Text Available Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, precise wind power forecasts are of primary importance to solve operational, planning and economic problems in the growing wind power scenario. Previous research has focused efforts on the deterministic forecast of wind power values, but less attention has been paid to providing information about wind energy. Based on an optimal Adaptive-Network-Based Fuzzy Inference System (ANFIS and Singular Spectrum Analysis (SSA, this paper develops a hybrid uncertainty forecasting model, IFASF (Interval Forecast-ANFIS-SSA-Firefly Alogorithm, to obtain the upper and lower bounds of daily average wind power, which is beneficial for the practical operation of both the grid company and independent power producers. To strengthen the practical ability of this developed model, this paper presents a comparison between IFASF and other benchmarks, which provides a general reference for this aspect for statistical or artificially intelligent interval forecast methods. The comparison results show that the developed model outperforms eight benchmarks and has a satisfactory forecasting effectiveness in three different wind farms with two time horizons.

Optimal investment horizons

Science.gov (United States)

Simonsen, I.; Jensen, M. H.; Johansen, A.

2002-06-01

In stochastic finance, one traditionally considers the return as a competitive measure of an asset, i.e., the profit generated by that asset after some fixed time span Δt, say one week or one year. This measures how well (or how bad) the asset performs over that given period of time. It has been established that the distribution of returns exhibits ``fat tails'' indicating that large returns occur more frequently than what is expected from standard Gaussian stochastic processes [1-3]. Instead of estimating this ``fat tail'' distribution of returns, we propose here an alternative approach, which is outlined by addressing the following question: What is the smallest time interval needed for an asset to cross a fixed return level of say 10%? For a particular asset, we refer to this time as the investment horizon and the corresponding distribution as the investment horizon distribution. This latter distribution complements that of returns and provides new and possibly crucial information for portfolio design and risk-management, as well as for pricing of more exotic options. By considering historical financial data, exemplified by the Dow Jones Industrial Average, we obtain a novel set of probability distributions for the investment horizons which can be used to estimate the optimal investment horizon for a stock or a future contract.

VMware horizon view essentials

CERN Document Server

von Oven, Peter

2014-01-01

If you are a desktop administrator or an end user of a computing project team looking to speed up to the latest VMware Horizon View solution, then this book is perfect for you. It is your ideal companion to deploy a solution to centrally manage and virtualize your desktop estate using Horizon View 6.0.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

Science.gov (United States)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

Directory of Open Access Journals (Sweden)

Chien-Lin Huang

2015-01-01

Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

Scaling forecast models for wind turbulence and wind turbine power intermittency

Science.gov (United States)

Duran Medina, Olmo; Schmitt, Francois G.; Calif, Rudy

2017-04-01

The intermittency of the wind turbine power remains an important issue for the massive development of this renewable energy. The energy peaks injected in the electric grid produce difficulties in the energy distribution management. Hence, a correct forecast of the wind power in the short and middle term is needed due to the high unpredictability of the intermittency phenomenon. We consider a statistical approach through the analysis and characterization of stochastic fluctuations. The theoretical framework is the multifractal modelisation of wind velocity fluctuations. Here, we consider three wind turbine data where two possess a direct drive technology. Those turbines are producing energy in real exploitation conditions and allow to test our forecast models of power production at a different time horizons. Two forecast models were developed based on two physical principles observed in the wind and the power time series: the scaling properties on the one hand and the intermittency in the wind power increments on the other. The first tool is related to the intermittency through a multifractal lognormal fit of the power fluctuations. The second tool is based on an analogy of the power scaling properties with a fractional brownian motion. Indeed, an inner long-term memory is found in both time series. Both models show encouraging results since a correct tendency of the signal is respected over different time scales. Those tools are first steps to a search of efficient forecasting approaches for grid adaptation facing the wind energy fluctuations.

Entropy of black holes with multiple horizons

Directory of Open Access Journals (Sweden)

Yun He

2018-05-01

Full Text Available We examine the entropy of black holes in de Sitter space and black holes surrounded by quintessence. These black holes have multiple horizons, including at least the black hole event horizon and a horizon outside it (cosmological horizon for de Sitter black holes and “quintessence horizon” for the black holes surrounded by quintessence. Based on the consideration that the two horizons are not independent each other, we conjecture that the total entropy of these black holes should not be simply the sum of entropies of the two horizons, but should have an extra term coming from the correlations between the two horizons. Different from our previous works, in this paper we consider the cosmological constant as the variable and employ an effective method to derive the explicit form of the entropy. We also try to discuss the thermodynamic stabilities of these black holes according to the entropy and the effective temperature.

Cartan invariants and event horizon detection

Science.gov (United States)

Brooks, D.; Chavy-Waddy, P. C.; Coley, A. A.; Forget, A.; Gregoris, D.; MacCallum, M. A. H.; McNutt, D. D.

2018-04-01

We show that it is possible to locate the event horizon of a black hole (in arbitrary dimensions) by the zeros of certain Cartan invariants. This approach accounts for the recent results on the detection of stationary horizons using scalar polynomial curvature invariants, and improves upon them since the proposed method is computationally less expensive. As an application, we produce Cartan invariants that locate the event horizons for various exact four-dimensional and five-dimensional stationary, asymptotically flat (or (anti) de Sitter), black hole solutions and compare the Cartan invariants with the corresponding scalar curvature invariants that detect the event horizon.

State-space forecasting of Schistosoma haematobium time-series in Niono, Mali.

Science.gov (United States)

Medina, Daniel C; Findley, Sally E; Doumbia, Seydou

2008-08-13

Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with infectious diseases. The incidence of Schistosoma sp.-which are neglected tropical diseases exposing and infecting more than 500 and 200 million individuals in 77 countries, respectively-is rising because of 1) numerous irrigation and hydro-electric projects, 2) steady shifts from nomadic to sedentary existence, and 3) ineffective control programs. Notwithstanding the colossal scope of these parasitic infections, less than 0.5% of Schistosoma sp. investigations have attempted to predict their spatial and or temporal distributions. Undoubtedly, public health programs in developing countries could benefit from parsimonious forecasting and early warning systems to enhance management of these parasitic diseases. In this longitudinal retrospective (01/1996-06/2004) investigation, the Schistosoma haematobium time-series for the district of Niono, Mali, was fitted with general-purpose exponential smoothing methods to generate contemporaneous on-line forecasts. These methods, which are encapsulated within a state-space framework, accommodate seasonal and inter-annual time-series fluctuations. Mean absolute percentage error values were circa 25% for 1- to 5-month horizon forecasts. The exponential smoothing state-space framework employed herein produced reasonably accurate forecasts for this time-series, which reflects the incidence of S. haematobium-induced terminal hematuria. It obliquely captured prior non-linear interactions between disease dynamics and exogenous covariates (e.g., climate, irrigation, and public health interventions), thus obviating the need for more complex forecasting methods in the district of Niono, Mali. Therefore, this framework could assist with managing and assessing S. haematobium transmission and intervention impact, respectively, in this district and potentially elsewhere in the Sahel.

Real-Time Flood Control by Tree-Based Model Predictive Control Including Forecast Uncertainty: A Case Study Reservoir in Turkey

Directory of Open Access Journals (Sweden)

Gökçen Uysal

2018-03-01

Full Text Available Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC. Deterministic Streamflow Forecasts (DSFs are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees.

[A factor analysis method for contingency table data with unlimited multiple choice questions].

Science.gov (United States)

Toyoda, Hideki; Haiden, Reina; Kubo, Saori; Ikehara, Kazuya; Isobe, Yurie

2016-02-01

The purpose of this study is to propose a method of factor analysis for analyzing contingency tables developed from the data of unlimited multiple-choice questions. This method assumes that the element of each cell of the contingency table has a binominal distribution and a factor analysis model is applied to the logit of the selection probability. Scree plot and WAIC are used to decide the number of factors, and the standardized residual, the standardized difference between the sample, and the proportion ratio, is used to select items. The proposed method was applied to real product impression research data on advertised chips and energy drinks. Since the results of the analysis showed that this method could be used in conjunction with conventional factor analysis model, and extracted factors were fully interpretable, and suggests the usefulness of the proposed method in the study of psychology using unlimited multiple-choice questions.

Linking Science of Flood Forecasts to Humanitarian Actions for Improved Preparedness and Effective Response

Science.gov (United States)

Uprety, M.; Dugar, S.; Gautam, D.; Kanel, D.; Kshetri, M.; Kharbuja, R. G.; Acharya, S. H.

2017-12-01

Advances in flood forecasting have provided opportunities for humanitarian responders to employ a range of preparedness activities at different forecast time horizons. Yet, the science of prediction is less understood and realized across the humanitarian landscape, and often preparedness plans are based upon average level of flood risk. Working under the remit of Forecast Based Financing (FbF), we present a pilot from Nepal on how available flood and weather forecast products are informing specific pre-emptive actions in the local preparedness and response plans, thereby supporting government stakeholders and humanitarian agencies to take early actions before an impending flood event. In Nepal, forecasting capabilities are limited but in a state of positive flux. Whilst local flood forecasts based upon rainfall-runoff models are yet to be operationalized, streamflow predictions from Global Flood Awareness System (GLoFAS) can be utilized to plan and implement preparedness activities several days in advance. Likewise, 3-day rainfall forecasts from Nepal Department of Hydrology and Meteorology (DHM) can further inform specific set of early actions for potential flash floods due to heavy precipitation. Existing community based early warning systems in the major river basins of Nepal are utilizing real time monitoring of water levels and rainfall together with localised probabilistic flood forecasts which has increased warning lead time from 2-3 hours to 7-8 hours. Based on these available forecast products, thresholds and trigger levels have been determined for different flood scenarios. Matching these trigger levels and assigning responsibilities to relevant actors for early actions, a set of standard operating procedures (SOPs) are being developed, broadly covering general preparedness activities and science informed anticipatory actions for different forecast lead times followed by the immediate response activities. These SOPs are currently being rolled out and

Generalized Robertson-Walker Space-Time Admitting Evolving Null Horizons Related to a Black Hole Event Horizon.

Science.gov (United States)

Duggal, K L

2016-01-01

A new technique is used to study a family of time-dependent null horizons, called " Evolving Null Horizons " (ENHs), of generalized Robertson-Walker (GRW) space-time [Formula: see text] such that the metric [Formula: see text] satisfies a kinematic condition. This work is different from our early papers on the same issue where we used (1 + n )-splitting space-time but only some special subcases of GRW space-time have this formalism. Also, in contrast to previous work, we have proved that each member of ENHs is totally umbilical in [Formula: see text]. Finally, we show that there exists an ENH which is always a null horizon evolving into a black hole event horizon and suggest some open problems.

Holography beyond the horizon and cosmic censorship

International Nuclear Information System (INIS)

Levi, Thomas S.; Ross, Simon F.

2003-01-01

We investigate the description of the region behind the event horizon in rotating black holes in the AdS conformal field theory correspondence, using the rotating Banados-Teitelboim-Zanelli black hole as a concrete example. We extend a technique introduced by Kraus, Ooguri, and Shenker, based on analytically continuing amplitudes defined in a Euclidean space, to include rotation. In the rotating case, boundary amplitudes again have two different bulk descriptions, involving either integration only over the regions outside the black holes' event horizon, or integration over this region and the region between the event horizon and the Cauchy horizon (inner horizon). We argue that generally, the holographic map will relate the field theory to the region bounded by the Cauchy horizons in spacetime. We also argue that these results suggest that the holographic description of black holes will satisfy strong cosmic censorship

Smart Irrigation From Soil Moisture Forecast Using Satellite And Hydro -Meteorological Modelling

Science.gov (United States)

Corbari, Chiara; Mancini, Marco; Ravazzani, Giovanni; Ceppi, Alessandro; Salerno, Raffaele; Sobrino, Josè

2017-04-01

Increased water demand and climate change impacts have recently enhanced the need to improve water resources management, even in those areas which traditionally have an abundant supply of water. The highest consumption of water is devoted to irrigation for agricultural production, and so it is in this area that efforts have to be focused to study possible interventions. The SIM project funded by EU in the framework of the WaterWorks2014 - Water Joint Programming Initiative aims at developing an operational tool for real-time forecast of crops irrigation water requirements to support parsimonious water management and to optimize irrigation scheduling providing real-time and forecasted soil moisture behavior at high spatial and temporal resolutions with forecast horizons from few up to thirty days. This study discusses advances in coupling satellite driven soil water balance model and meteorological forecast as support for precision irrigation use comparing different case studies in Italy, in the Netherlands, in China and Spain, characterized by different climatic conditions, water availability, crop types and irrigation techniques and water distribution rules. Herein, the applications in two operative farms in vegetables production in the South of Italy where semi-arid climatic conditions holds, two maize fields in Northern Italy in a more water reach environment with flood irrigation will be presented. This system combines state of the art mathematical models and new technologies for environmental monitoring, merging ground observed data with Earth observations. Discussion on the methodology approach is presented, comparing for a reanalysis periods the forecast system outputs with observed soil moisture and crop water needs proving the reliability of the forecasting system and its benefits. The real-time visualization of the implemented system is also presented through web-dashboards.

State estimates and forecasts of the loop current in the Gulf of Mexico using the MITgcm and its adjoint

KAUST Repository

Gopalakrishnan, Ganesh

2013-07-01

An ocean state estimate has been developed for the Gulf of Mexico (GoM) using the MIT general circulation model and its adjoint. The estimate has been tested by forecasting loop current (LC) evolution and eddy shedding in the GoM. The adjoint (or four-dimensional variational) method was used to match the model evolution to observations by adjusting model temperature and salinity initial conditions, open boundary conditions, and atmospheric forcing fields. The model was fit to satellite-derived along-track sea surface height, separated into temporal mean and anomalies, and gridded sea surface temperature for 2 month periods. The optimized state at the end of the assimilation period was used to initialize the forecast for 2 months. Forecasts explore practical LC predictability and provide a cross-validation test of the state estimate by comparing it to independent future observations. The model forecast was tested for several LC eddy separation events, including Eddy Franklin in May 2010 during the deepwater horizon oil spill disaster in the GoM. The forecast used monthly climatological open boundary conditions, atmospheric forcing, and run-off fluxes. The model performance was evaluated by computing model-observation root-mean-square difference (rmsd) during both the hindcast and forecast periods. The rmsd metrics for the forecast generally outperformed persistence (keeping the initial state fixed) and reference (forecast initialized using assimilated Hybrid Coordinate Ocean Model 1/12° global analysis) model simulations during LC eddy separation events for a period of 1̃2 months.

State estimates and forecasts of the loop current in the Gulf of Mexico using the MITgcm and its adjoint

KAUST Repository

Gopalakrishnan, Ganesh; Cornuelle, Bruce D.; Hoteit, Ibrahim; Rudnick, Daniel L.; Owens, W. Brechner

2013-01-01

An ocean state estimate has been developed for the Gulf of Mexico (GoM) using the MIT general circulation model and its adjoint. The estimate has been tested by forecasting loop current (LC) evolution and eddy shedding in the GoM. The adjoint (or four-dimensional variational) method was used to match the model evolution to observations by adjusting model temperature and salinity initial conditions, open boundary conditions, and atmospheric forcing fields. The model was fit to satellite-derived along-track sea surface height, separated into temporal mean and anomalies, and gridded sea surface temperature for 2 month periods. The optimized state at the end of the assimilation period was used to initialize the forecast for 2 months. Forecasts explore practical LC predictability and provide a cross-validation test of the state estimate by comparing it to independent future observations. The model forecast was tested for several LC eddy separation events, including Eddy Franklin in May 2010 during the deepwater horizon oil spill disaster in the GoM. The forecast used monthly climatological open boundary conditions, atmospheric forcing, and run-off fluxes. The model performance was evaluated by computing model-observation root-mean-square difference (rmsd) during both the hindcast and forecast periods. The rmsd metrics for the forecast generally outperformed persistence (keeping the initial state fixed) and reference (forecast initialized using assimilated Hybrid Coordinate Ocean Model 1/12° global analysis) model simulations during LC eddy separation events for a period of 1̃2 months.

Science in support of the Deepwater Horizon response

Science.gov (United States)

Lubchenco, Jane; McNutt, Marcia K.; Dreyfus, Gabrielle; Murawski, Steven A.; Kennedy, David M.; Anastas, Paul T.; Chu, Steven; Hunter, Tom

2012-01-01

This introduction to the Special Feature presents the context for science during the Deepwater Horizon oil spill response, summarizes how scientific knowledge was integrated across disciplines and statutory responsibilities, identifies areas where scientific information was accurate and where it was not, and considers lessons learned and recommendations for future research and response. Scientific information was integrated within and across federal and state agencies, with input from nongovernmental scientists, across a diverse portfolio of needs—stopping the flow of oil, estimating the amount of oil, capturing and recovering the oil, tracking and forecasting surface oil, protecting coastal and oceanic wildlife and habitat, managing fisheries, and protecting the safety of seafood. Disciplines involved included atmospheric, oceanographic, biogeochemical, ecological, health, biological, and chemical sciences, physics, geology, and mechanical and chemical engineering. Platforms ranged from satellites and planes to ships, buoys, gliders, and remotely operated vehicles to laboratories and computer simulations. The unprecedented response effort depended directly on intense and extensive scientific and engineering data, information, and advice. Many valuable lessons were learned that should be applied to future events.

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....

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

75 FR 69577 - Deposit Insurance Regulations; Unlimited Coverage for Noninterest-Bearing Transaction Accounts

Science.gov (United States)

2010-11-15

..., contending that providing such coverage for these accounts promotes moral hazard. Four commenters suggested... withdrawals at any time, whether held by a business, an individual or other type of depositor. Unlike the... for unlimited separate coverage as a noninterest-bearing transaction account. One issue raised during...

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.

The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting

Science.gov (United States)

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

2017-08-01

This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.

Horizon Entropy from Quantum Gravity Condensates.

Science.gov (United States)

Oriti, Daniele; Pranzetti, Daniele; Sindoni, Lorenzo

2016-05-27

We construct condensate states encoding the continuum spherically symmetric quantum geometry of a horizon in full quantum gravity, i.e., without any classical symmetry reduction, in the group field theory formalism. Tracing over the bulk degrees of freedom, we show how the resulting reduced density matrix manifestly exhibits a holographic behavior. We derive a complete orthonormal basis of eigenstates for the reduced density matrix of the horizon and use it to compute the horizon entanglement entropy. By imposing consistency with the horizon boundary conditions and semiclassical thermodynamical properties, we recover the Bekenstein-Hawking entropy formula for any value of the Immirzi parameter. Our analysis supports the equivalence between the von Neumann (entanglement) entropy interpretation and the Boltzmann (statistical) one.

Event horizon image within black hole shadow

OpenAIRE

Dokuchaev, V. I.; Nazarova, N. O.

2018-01-01

The external border of the black hole shadow is washed out by radiation from matter plunging into black hole and approaching the event horizon. This effect will crucially influence the results of future observations by the Event Horizon Telescope. We show that gravitational lensing of the luminous matter plunging into black hole provides the event horizon visualization within black hole shadow. The lensed image of the event horizon is formed by the last highly red-shifted photons emitted by t...

Critical properties of unlimited gliding: Unexpected flocking behavior driven by the exchange of information

Science.gov (United States)

Bigus-Kwiatkowska, Marta; Fronczak, Agata; Fronczak, Piotr

2018-03-01

Inspired by albatrosses that use thermal lifts to fly across oceans we develop a simple model of gliders that serves us to study theoretical limitations of unlimited exploration of the Earth. Our studies, grounded in physical theory of continuous percolation and biased random walks, allow us to identify a variety of percolation transitions, which are understood as providing potentially unlimited movement through a space in a specified direction. We discover an unexpected phenomenon of self-organization of gliders in clusters, which resembles the flock organization of birds. This self-organization is intriguing, as it occurs thanks to exchange of information only and without any particular rules that could favor the clustering of the gliders (in contrast to the causes well known in literature, like, for example, attractive forces used in the Vicsek-type models or fitness functions used in evolutionary computation).

Using ensemble weather forecast in a risk based real time optimization of urban drainage systems

DEFF Research Database (Denmark)

Courdent, Vianney Augustin Thomas; Vezzaro, Luca; Mikkelsen, Peter Steen

2015-01-01

Global Real Time Control (RTC) of urban drainage system is increasingly seen as cost-effective solution in order to respond to increasing performance demand (e.g. reduction of Combined Sewer Overflow, protection of sensitive areas as bathing water etc.). The Dynamic Overflow Risk Assessment (DORA......) strategy was developed to operate Urban Drainage Systems (UDS) in order to minimize the expected overflow risk by considering the water volume presently stored in the drainage network, the expected runoff volume based on a 2-hours radar forecast model and an estimated uncertainty of the runoff forecast....... However, such temporal horizon (1-2 hours) is relatively short when used for the operation of large storage facilities, which may require a few days to be emptied. This limits the performance of the optimization and control in reducing combined sewer overflow and in preparing for possible flooding. Based...

TU-C-HORIZONS-01: The Expanding Horizons Travel Grant Program: ePosters and Discussion

International Nuclear Information System (INIS)

Siewerdsen, J; Jeraj, R

2016-01-01

The Expanding Horizons travel grant program provides opportunity for students and trainees to broaden the scope of scientific meetings they attend and gain insight from research outside traditional domains of medical physics. Through participation in such conferences, early-career researchers are introduced to new topics with relevance to medical physics research as a means to expand the scientific horizons of our discipline. This year, 21 Expanding Horizons travel grants were awarded, granting travel to 17 conferences, including: Radiomics, the World Molecular Imaging Society (WMIS), the 3D Printing Conference and Expo, the GPU Technology Conference, the SIAM Imaging Science Conference, the Human Brain Mapping Conference, the OSA Conference on Clinical and Translational Biophotonics, the Society for Neuroscience, the AACR Conference on Tumor Microenvironment, and the Conference on Knowledge Discovery and Data Mining. The Expanding Horizons electronic poster session gives a venue for AAPM conference attendees to meet and discuss with awardees, learn the hot topics and emerging research areas presented at these conferences, and understand the relevance to future medical physics research.

TU-C-HORIZONS-01: The Expanding Horizons Travel Grant Program: ePosters and Discussion

Energy Technology Data Exchange (ETDEWEB)

Siewerdsen, J [Johns Hopkins University, Baltimore, MD (United States); Jeraj, R [University of Wisconsin, Madison, WI (United States)

2016-06-15

The Expanding Horizons travel grant program provides opportunity for students and trainees to broaden the scope of scientific meetings they attend and gain insight from research outside traditional domains of medical physics. Through participation in such conferences, early-career researchers are introduced to new topics with relevance to medical physics research as a means to expand the scientific horizons of our discipline. This year, 21 Expanding Horizons travel grants were awarded, granting travel to 17 conferences, including: Radiomics, the World Molecular Imaging Society (WMIS), the 3D Printing Conference and Expo, the GPU Technology Conference, the SIAM Imaging Science Conference, the Human Brain Mapping Conference, the OSA Conference on Clinical and Translational Biophotonics, the Society for Neuroscience, the AACR Conference on Tumor Microenvironment, and the Conference on Knowledge Discovery and Data Mining. The Expanding Horizons electronic poster session gives a venue for AAPM conference attendees to meet and discuss with awardees, learn the hot topics and emerging research areas presented at these conferences, and understand the relevance to future medical physics research.

Modeling and optimization of the european oil refining capacities and structures on the horizons 1995, 2000 and 2010

International Nuclear Information System (INIS)

Khebri, S.

1993-04-01

This thesis is a study on petroleum refining. In a first part, the author describes the existing refining processes and the structure of refining units, the structure of petroleum consumption and the interfaces with petroleum chemistry industry and gives a retrospect on world and european petroleum refining. In a second part, the author describes the models used to realize the simulation of supplies, market and refining scheme. Four scenarios are developed (conventional wisdom, driving into tensions, sustaining a high economic growth, high prices) and a forecasting on the horizons 1995, 2000 and 2010 is given. 54 refs

Real-time energy resources scheduling considering short-term and very short-term wind forecast

Energy Technology Data Exchange (ETDEWEB)

Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

2012-07-01

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

Cauchy horizons in Gowdy spacetimes

International Nuclear Information System (INIS)

Chrusciel, Piotr T; Lake, Kayll

2004-01-01

We analyse exhaustively the structure of non-degenerate Cauchy horizons in Gowdy spacetimes, and we establish existence of a large class of non-polarized Gowdy spacetimes with such horizons. Our results here, together with the deep new results of Ringstroem, establish strong cosmic censorship in (toroidal) Gowdy spacetimes

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

Science.gov (United States)

Falat, Lukas; Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

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

Horizon shells and BMS-like soldering transformations

Energy Technology Data Exchange (ETDEWEB)

Blau, Matthias [Albert Einstein Center for Fundamental Physics,Institute for Theoretical Physics, University of Bern,Sidlerstrasse 5, 3012 Bern (Switzerland); O’Loughlin, Martin [University of Nova Gorica,Vipavska 13, 5000 Nova Gorica (Slovenia)

2016-03-07

We revisit the theory of null shells in general relativity, with a particular emphasis on null shells placed at horizons of black holes. We study in detail the considerable freedom that is available in the case that one solders two metrics together across null hypersurfaces (such as Killing horizons) for which the induced metric is invariant under translations along the null generators. In this case the group of soldering transformations turns out to be infinite dimensional, and these solderings create non-trivial horizon shells containing both massless matter and impulsive gravitational wave components. We also rephrase this result in the language of Carrollian symmetry groups. To illustrate this phenomenon we discuss in detail the example of shells on the horizon of the Schwarzschild black hole (with equal interior and exterior mass), uncovering a rich classical structure at the horizon and deriving an explicit expression for the general horizon shell energy-momentum tensor. In the special case of BMS-like soldering supertranslations we find a conserved shell-energy that is strikingly similar to the standard expression for asymptotic BMS supertranslation charges, suggesting a direct relation between the physical properties of these horizon shells and the recently proposed BMS supertranslation hair of a black hole.

Super-horizon primordial black holes

International Nuclear Information System (INIS)

Harada, Tomohiro; Carr, B.J.

2005-01-01

We discuss a new class of solutions to the Einstein equations which describe a primordial black hole (PBH) in a flat Friedmann background. Such solutions arise if a Schwarzschild black hole is patched onto a Friedmann background via a transition region. They are possible providing the black hole event horizon is larger than the cosmological apparent horizon. Such solutions have a number of strange features. In particular, one has to define the black hole and cosmological horizons carefully and one then finds that the mass contained within the black hole event horizon decreases when the black hole is larger than the Friedmann cosmological apparent horizon, although its area always increases. These solutions involve two distinct future null infinities and are interpreted as the conversion of a white hole into a black hole. Although such solutions may not form from gravitational collapse in the same way as standard PBHs, there is nothing unphysical about them, since all energy and causality conditions are satisfied. Their conformal diagram is a natural amalgamation of the Kruskal diagram for the extended Schwarzschild solution and the conformal diagram for a black hole in a flat Friedmann background. In this paper, such solutions are obtained numerically for a spherically symmetric universe containing a massless scalar field, but it is likely that they exist for more general matter fields and less symmetric systems

Ups and downs of economics and econophysics — Facebook forecast

Science.gov (United States)

Gajic, Nenad; Budinski-Petkovic, Ljuba

2013-01-01

What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering - this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.

A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting

International Nuclear Information System (INIS)

Azimi, R.; Ghayekhloo, M.; Ghofrani, M.

2016-01-01

Highlights: • A novel clustering approach is proposed based on the data transformation approach. • A novel cluster selection method based on correlation analysis is presented. • The proposed hybrid clustering approach leads to deep learning for MLPNN. • A hybrid forecasting method is developed to predict solar radiations. • The evaluation results show superior performance of the proposed forecasting model. - Abstract: Accurate forecasting of renewable energy sources plays a key role in their integration into the grid. This paper proposes a hybrid solar irradiance forecasting framework using a Transformation based K-means algorithm, named TB K-means, to increase the forecast accuracy. The proposed clustering method is a combination of a new initialization technique, K-means algorithm and a new gradual data transformation approach. Unlike the other K-means based clustering methods which are not capable of providing a fixed and definitive answer due to the selection of different cluster centroids for each run, the proposed clustering provides constant results for different runs of the algorithm. The proposed clustering is combined with a time-series analysis, a novel cluster selection algorithm and a multilayer perceptron neural network (MLPNN) to develop the hybrid solar radiation forecasting method for different time horizons (1 h ahead, 2 h ahead, …, 48 h ahead). The performance of the proposed TB K-means clustering is evaluated using several different datasets and compared with different variants of K-means algorithm. Solar datasets with different solar radiation characteristics are also used to determine the accuracy and processing speed of the developed forecasting method with the proposed TB K-means and other clustering techniques. The results of direct comparison with other well-established forecasting models demonstrate the superior performance of the proposed hybrid forecasting method. Furthermore, a comparative analysis with the benchmark solar

Dynamical symmetry enhancement near IIA horizons

International Nuclear Information System (INIS)

Gran, University; Gutowski, J.; Kayani, University; Papadopoulos, G.

2015-01-01

We show that smooth type IIA Killing horizons with compact spatial sections preserve an even number of supersymmetries, and that the symmetry algebra of horizons with non-trivial fluxes includes an sl(2,ℝ) subalgebra. This confirms the conjecture of http://dx.doi.org/10.1007/JHEP11(2013)104 for type IIA horizons. As an intermediate step in the proof, we also demonstrate new Lichnerowicz type theorems for spin bundle connections whose holonomy is contained in a general linear group.

Nonlinear solar cycle forecasting: theory and perspectives

Science.gov (United States)

Baranovski, A. L.; Clette, F.; Nollau, V.

2008-02-01

In this paper we develop a modern approach to solar cycle forecasting, based on the mathematical theory of nonlinear dynamics. We start from the design of a static curve fitting model for the experimental yearly sunspot number series, over a time scale of 306 years, starting from year 1700 and we establish a least-squares optimal pulse shape of a solar cycle. The cycle-to-cycle evolution of the parameters of the cycle shape displays different patterns, such as a Gleissberg cycle and a strong anomaly in the cycle evolution during the Dalton minimum. In a second step, we extract a chaotic mapping for the successive values of one of the key model parameters - the rate of the exponential growth-decrease of the solar activity during the n-th cycle. We examine piece-wise linear techniques for the approximation of the derived mapping and we provide its probabilistic analysis: calculation of the invariant distribution and autocorrelation function. We find analytical relationships for the sunspot maxima and minima, as well as their occurrence times, as functions of chaotic values of the above parameter. Based on a Lyapunov spectrum analysis of the embedded mapping, we finally establish a horizon of predictability for the method, which allows us to give the most probable forecasting of the upcoming solar cycle 24, with an expected peak height of 93±21 occurring in 2011/2012.

Instability of enclosed horizons

Science.gov (United States)

Kay, Bernard S.

2015-03-01

We point out that there are solutions to the scalar wave equation on dimensional Minkowski space with finite energy tails which, if they reflect off a uniformly accelerated mirror due to (say) Dirichlet boundary conditions on it, develop an infinite stress-energy tensor on the mirror's Rindler horizon. We also show that, in the presence of an image mirror in the opposite Rindler wedge, suitable compactly supported arbitrarily small initial data on a suitable initial surface will develop an arbitrarily large stress-energy scalar near where the two horizons cross. Also, while there is a regular Hartle-Hawking-Israel-like state for the quantum theory between these two mirrors, there are coherent states built on it for which there are similar singularities in the expectation value of the renormalized stress-energy tensor. We conjecture that in other situations with analogous enclosed horizons such as a (maximally extended) Schwarzschild black hole in equilibrium in a (stationary spherical) box or the (maximally extended) Schwarzschild-AdS spacetime, there will be similar stress-energy singularities and almost-singularities—leading to instability of the horizons when gravity is switched on and matter and gravity perturbations are allowed for. All this suggests it is incorrect to picture a black hole in equilibrium in a box or a Schwarzschild-AdS black hole as extending beyond the past and future horizons of a single Schwarzschild (/Schwarzschild-AdS) wedge. It would thus provide new evidence for 't Hooft's brick wall model while seeming to invalidate the picture in Maldacena's ` Eternal black holes in AdS'. It would thereby also support the validity of the author's matter-gravity entanglement hypothesis and of the paper ` Brick walls and AdS/CFT' by the author and Ortíz.

An application of ensemble/multi model approach for wind power production forecast.

Science.gov (United States)

Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

2010-09-01

model) seems to reach similar level of accuracy of those of the mesocale models (LAMI and RAMS). Finally we have focused on the possibility of using the ensemble model (ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first day ahead period. In fact low spreads often correspond to low forecast error. For longer forecast horizon the correlation between RMSE and ensemble spread decrease becoming too low to be used for this purpose.

Horizons of hermeneutics: Intercultural hermeneutics in a globalizing world

NARCIS (Netherlands)

J. de Mul (Jos)

2011-01-01

textabstractStarting from the often-used metaphor of the "horizon of experience" this article discusses three different types of intercultural hermeneutics, which respectively conceive hermeneutic interpretation as a widening of horizons, a fusion of horizons, and a dissemination of horizons. It is

Energy production forecasting, experiences from Lillgrund. Lillgrund Pilot Project

Energy Technology Data Exchange (ETDEWEB)

Johansson, Lasse; Schelander, Peter; Haakansson, Maans; Hansson, Johan (Vattenfall Vindkraft AB, Stockholm (Sweden))

2010-01-15

assumptions. Production forecasts are not used as a tool in the planning of the operation and maintenance within the wind farm. Maintenance planning is done with a much longer time horizon than the current production forecasts offer. For example, Vattenfall has to inform and coordinate with the owner of the local power network typically three weeks in advance before any maintenance that can cause significant loss of production. It's an inevitable fact that wind turbines must be stopped for maintenance with regular intervals in order to maintain secure and stable operations. However, it is in the power producers' interest to minimize these stops for maintenance work. And of even higher importance, minimize the loss of production by making sure the stops coincide with periods of expected low production. At the end it's always the current weather that determines if the maintenance can be carried out as planned. Maintenance involving boats is dependent on calm weather and thus is correlated with periods of low wind speed and low energy production. Due to the seasonal variations in the wind climate, the summer season offers the best opportunities for planned maintenance work in the wind park. A production stop of larger dignity where sometimes the complete park is set out of operations is always done during the summer season. An analysis of production data from the first year of operation shows that the loss of production due to scheduled stops was almost negligible. However, a six week, unplanned stop of a few turbines caused a loss in production of almost 1.5 GWh

Hawking radiation from quasilocal dynamical horizons

Indian Academy of Sciences (India)

2016-01-06

Jan 6, 2016 ... Abstract. In completely local settings, we establish that a dynamically evolving spherically symmetric black hole horizon can be assigned a Hawking temperature and with the emission of flux, radius of the horizon shrinks.

Across-horizon scattering and information transfer

Science.gov (United States)

Emelyanov, V. A.; Klinkhamer, F. R.

2018-06-01

We address the question whether or not two electrically charged elementary particles can Coulomb scatter if one of these particles is inside the Schwarzschild black-hole horizon and the other outside. It can be shown that the quantum process is consistent with the local energy–momentum conservation law. This result implies that across-horizon scattering is a physical effect, relevant to astrophysical black holes. We propose a Gedankenexperiment which uses the quantum scattering process to transfer information from inside the black-hole horizon to outside.

Tropospheric radiowave propagation beyond the horizon

CERN Document Server

Du Castel, François

1966-01-01

Tropospheric Radiowave Propagation Beyond the Horizon deals with developments concerning the tropospheric propagation of ultra-short radio waves beyond the horizon, with emphasis on the relationship between the theoretical and the experimental. Topics covered include the general conditions of propagation in the troposphere; general characteristics of propagation beyond the horizon; and attenuation in propagation. This volume is comprised of six chapters and begins with a brief historical look at the various stages that have brought the technique of transhorizon links to its state of developmen

Unlimited multistability and Boolean logic in microbial signalling

DEFF Research Database (Denmark)

Kothamachu, Varun B; Feliu, Elisenda; Cardelli, Luca

2015-01-01

The ability to map environmental signals onto distinct internal physiological states or programmes is critical for single-celled microbes. A crucial systems dynamics feature underpinning such ability is multistability. While unlimited multistability is known to arise from multi-site phosphorylation...... seen in the signalling networks of eukaryotic cells, a similarly universal mechanism has not been identified in microbial signalling systems. These systems are generally known as two-component systems comprising histidine kinase (HK) receptors and response regulator proteins engaging in phosphotransfer...... further prove that sharing of downstream components allows a system with n multi-domain hybrid HKs to attain 3n steady states. We find that such systems, when sensing distinct signals, can readily implement Boolean logic functions on these signals. Using two experimentally studied examples of two...

Mastering VMware Horizon 6

CERN Document Server

Oven, Peter von

2015-01-01

If you are working as a desktop admin, part of a EUC team, an architect, or a consultant on a desktop virtualization project and you are looking to use VMware's Horizon solution, this book is for you. This book will demonstrate the new capabilities of Horizon 6. You should have experience in desktop management using Windows and Microsoft Office, and be familiar with Active Directory, SQL, Windows Remote Desktop Session Hosting, and VMware vSphere infrastructure (ESXi and vCenter Server) technology.

Horizon 2020 in sight

CERN Multimedia

Joannah Caborn Wengler

2012-01-01

Every tenth member of the CERN personnel participates in an EU-funded project – a strong indication of CERN’s successful relations with the European Commission (EC), coordinated by the CERN EU projects office. The EC director in charge of preparing “Horizon 2020”, the new EU funding programme for research and innovation (2014-2020), will be giving a presentation at CERN on 8 May. He will reveal more about what the new programme has in store.   “It’s a very interesting time in the development of Horizon 2020, which is focusing the attention of all research communities in Europe,” explains Svetlomir Stavrev, head of the EU projects office. “After a long public consultation and drafting process, the Horizon 2020 proposal documents are now being reviewed by the European Parliament and Council.” CERN already participated in the consultation, making good use of the opportunity to contribute to the shaping of wh...

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...

Implementing VMware Horizon View 5.2

CERN Document Server

Ventresco, Jason

2013-01-01

A step-by-step tutorial covering all components of the View Horizon suite in detail, to ensure that you can utilize all features of the platform, and discover all of the possible ways that it can be used within your own environment.If you are a newcomer in system administration, and you wish to implement a small to midsized Horizon View environment, then this book is for you. It will also benefit individuals who wish to administrate and manage Horizon View more efficiently or are studying for the VCP5-DT.

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...

Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting

Science.gov (United States)

Pasetto, Damiano; Finger, Flavio; Rinaldo, Andrea; Bertuzzo, Enrico

2017-10-01

Although treatment for cholera is well-known and cheap, outbreaks in epidemic regions still exact high death tolls mostly due to the unpreparedness of health care infrastructures to face unforeseen emergencies. In this context, mathematical models for the prediction of the evolution of an ongoing outbreak are of paramount importance. Here, we test a real-time forecasting framework that readily integrates new information as soon as available and periodically issues an updated forecast. The spread of cholera is modeled by a spatially-explicit scheme that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. The framework presents two major innovations for cholera modeling: the use of a data assimilation technique, specifically an ensemble Kalman filter, to update both state variables and parameters based on the observations, and the use of rainfall forecasts to force the model. The exercise of simulating the state of the system and the predictive capabilities of the novel tools, set at the initial phase of the 2010 Haitian cholera outbreak using only information that was available at that time, serves as a benchmark. Our results suggest that the assimilation procedure with the sequential update of the parameters outperforms calibration schemes based on Markov chain Monte Carlo. Moreover, in a forecasting mode the model usefully predicts the spatial incidence of cholera at least one month ahead. The performance decreases for longer time horizons yet allowing sufficient time to plan for deployment of medical supplies and staff, and to evaluate alternative strategies of emergency management.

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

Energy Technology Data Exchange (ETDEWEB)

Martin Wilde, Principal Investigator

2012-12-31

ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational

Neural networks-based operational prototype for flash flood forecasting: application to Liane flash floods (France

Directory of Open Access Journals (Sweden)

Bertin Dominique

2016-01-01

Full Text Available The Liane River is a small costal river, famous for its floods, which can affect the city of Boulogne-sur-Mer. Due to the complexity of land cover and hydrologic processes, a black-box non-linear modelling was chosen using neural networks. The multilayer perceptron model, known for its property of universal approximation is thus chosen. Four models were designed, each one for one forecasting horizon using rainfall forecasts: 24h, 12h, 6h, 3h. The desired output of the model is original: it represents the maximal value of the water level respectively 24h, 12h, 6h, 3h ahead. Working with best forecasts of rain (the observed ones during the event in the past, on the major flood of the database in test set, the model provides excellent forecasts. Nash criteria calculated for the four lead times are 0.98 (3h, 0.97 (6h, 0.91 (12h, 0.89 (24h. Designed models were thus estimated as efficient enough to be implemented in a specific tool devoted to real time operational use. The software tool is described hereafter: designed in Java, it presents a friendly interface allowing applying various scenarios of future rainfalls, and a graphical visualization of the predicted maximum water levels and their associated real time observed values.

Classification of Near-Horizon Geometries of Extremal Black Holes

Directory of Open Access Journals (Sweden)

Hari K. Kunduri

2013-09-01

Full Text Available Any spacetime containing a degenerate Killing horizon, such as an extremal black hole, possesses a well-defined notion of a near-horizon geometry. We review such near-horizon geometry solutions in a variety of dimensions and theories in a unified manner. We discuss various general results including horizon topology and near-horizon symmetry enhancement. We also discuss the status of the classification of near-horizon geometries in theories ranging from vacuum gravity to Einstein–Maxwell theory and supergravity theories. Finally, we discuss applications to the classification of extremal black holes and various related topics. Several new results are presented and open problems are highlighted throughout.

Classification of Near-Horizon Geometries of Extremal Black Holes.

Science.gov (United States)

Kunduri, Hari K; Lucietti, James

2013-01-01

Any spacetime containing a degenerate Killing horizon, such as an extremal black hole, possesses a well-defined notion of a near-horizon geometry. We review such near-horizon geometry solutions in a variety of dimensions and theories in a unified manner. We discuss various general results including horizon topology and near-horizon symmetry enhancement. We also discuss the status of the classification of near-horizon geometries in theories ranging from vacuum gravity to Einstein-Maxwell theory and supergravity theories. Finally, we discuss applications to the classification of extremal black holes and various related topics. Several new results are presented and open problems are highlighted throughout.

Moving Horizon Estimation and Control

DEFF Research Database (Denmark)

Jørgensen, John Bagterp

successful and applied methodology beyond PID-control for control of industrial processes. The main contribution of this thesis is introduction and definition of the extended linear quadratic optimal control problem for solution of numerical problems arising in moving horizon estimation and control...... problems. Chapter 1 motivates moving horizon estimation and control as a paradigm for control of industrial processes. It introduces the extended linear quadratic control problem and discusses its central role in moving horizon estimation and control. Introduction, application and efficient solution....... It provides an algorithm for computation of the maximal output admissible set for linear model predictive control. Appendix D provides results concerning linear regression. Appendix E discuss prediction error methods for identification of linear models tailored for model predictive control....

Sociopathic Knowledge Bases: Correct Knowledge Can Be Harmful Even Given Unlimited Computation

Science.gov (United States)

1989-08-01

1757 I Sociopathic Knowledge Bases: Correct Knowledge Can Be Harmful Even Given Unlimited Computation DTIC5 by flELECTE 5David C. Wilkins and Yong...NUMBERSWOKNI PROGRAM RAT TSWOKUI 61153N RR04206 OC 443g-008 11 TITLE (Include Security Classification) Sociopathic Knowledge Bases: Correct Knowledge Can be...probabilistic rules are shown to be sociopathic and so this problem is very widespread. Sociopathicity has important consequences for rule induction

Solar energy prediction and verification using operational model forecasts and ground-based solar measurements

International Nuclear Information System (INIS)

Kosmopoulos, P.G.; Kazadzis, S.; Lagouvardos, K.; Kotroni, V.; Bais, A.

2015-01-01

The present study focuses on the predictions and verification of these predictions of solar energy using ground-based solar measurements from the Hellenic Network for Solar Energy and the National Observatory of Athens network, as well as solar radiation operational forecasts provided by the MM5 mesoscale model. The evaluation was carried out independently for the different networks, for two forecast horizons (1 and 2 days ahead), for the seasons of the year, for varying solar elevation, for the indicative energy potential of the area, and for four classes of cloud cover based on the calculated clearness index (k_t): CS (clear sky), SC (scattered clouds), BC (broken clouds) and OC (overcast). The seasonal dependence presented relative rRMSE (Root Mean Square Error) values ranging from 15% (summer) to 60% (winter), while the solar elevation dependence revealed a high effectiveness and reliability near local noon (rRMSE ∼30%). An increment of the errors with cloudiness was also observed. For CS with mean GHI (global horizontal irradiance) ∼ 650 W/m"2 the errors are 8%, for SC 20% and for BC and OC the errors were greater (>40%) but correspond to much lower radiation levels (<120 W/m"2) of consequently lower energy potential impact. The total energy potential for each ground station ranges from 1.5 to 1.9 MWh/m"2, while the mean monthly forecast error was found to be consistently below 10%. - Highlights: • Long term measurements at different atmospheric cases are needed for energy forecasting model evaluations. • The total energy potential at the Greek sites presented ranges from 1.5 to 1.9 MWh/m"2. • Mean monthly energy forecast errors are within 10% for all cases analyzed. • Cloud presence results of an additional forecast error that varies with the cloud cover.

Multimodel hydrological ensemble forecasts for the Baskatong catchment in Canada using the TIGGE database.

Science.gov (United States)

Tito Arandia Martinez, Fabian

2014-05-01

Adequate uncertainty assessment is an important issue in hydrological modelling. An important issue for hydropower producers is to obtain ensemble forecasts which truly grasp the uncertainty linked to upcoming streamflows. If properly assessed, this uncertainty can lead to optimal reservoir management and energy production (ex. [1]). The meteorological inputs to the hydrological model accounts for an important part of the total uncertainty in streamflow forecasting. Since the creation of the THORPEX initiative and the TIGGE database, access to meteorological ensemble forecasts from nine agencies throughout the world have been made available. This allows for hydrological ensemble forecasts based on multiple meteorological ensemble forecasts. Consequently, both the uncertainty linked to the architecture of the meteorological model and the uncertainty linked to the initial condition of the atmosphere can be accounted for. The main objective of this work is to show that a weighted combination of meteorological ensemble forecasts based on different atmospheric models can lead to improved hydrological ensemble forecasts, for horizons from one to ten days. This experiment is performed for the Baskatong watershed, a head subcatchment of the Gatineau watershed in the province of Quebec, in Canada. Baskatong watershed is of great importance for hydro-power production, as it comprises the main reservoir for the Gatineau watershed, on which there are six hydropower plants managed by Hydro-Québec. Since the 70's, they have been using pseudo ensemble forecast based on deterministic meteorological forecasts to which variability derived from past forecasting errors is added. We use a combination of meteorological ensemble forecasts from different models (precipitation and temperature) as the main inputs for hydrological model HSAMI ([2]). The meteorological ensembles from eight of the nine agencies available through TIGGE are weighted according to their individual performance and

Mapping and Visualization of The Deepwater Horizon Oil Spill Using Satellite Imagery

Science.gov (United States)

Ferreira Pichardo, E.

2017-12-01

Satellites are man-made objects hovering around the Earth's orbit and are essential for Earth observation, i.e. the monitoring and gathering of data about the Earth's vital systems. Environmental Satellites are used for atmospheric research, weather forecasting, and warning as well as monitoring extreme weather events. These satellites are categorized into Geosynchronous and Low Earth (Polar) orbiting satellites. Visualizing satellite data is critical to understand the Earth's systems and changes to our environment. The objective of this research is to examine satellite-based remotely sensed data that needs to be processed and rendered in the form of maps or other forms of visualization to understand and interpret the satellites' observations to monitor the status, changes and evolution of the mega-disaster Deepwater Horizon Spill that occurred on April 20, 2010 in the Gulf of Mexico. In this project, we will use an array of tools and programs such as Python, CSPP and Linux. Also, we will use data from the National Oceanic and Atmospheric Administration (NOAA): Polar-Orbiting Satellites Terra Earth Observing System AM-1 (EOS AM-1), and Aqua EOS PM-1 to investigate the mega-disaster. Each of these satellites carry a variety of instruments, and we will use the data obtained from the remote sensor Moderate-Resolution Imaging Spectroradiometer (MODIS). Ultimately, this study shows the importance of mapping and visualizing data such as satellite data (MODIS) to understand the extents of environmental impacts disasters such as the Deepwater Horizon Oil spill.

Stretched horizons, quasiparticles, and quasinormal modes

International Nuclear Information System (INIS)

Iizuka, Norihiro; Kabat, Daniel; Lifschytz, Gilad; Lowe, David A.

2003-01-01

We propose that stretched horizons can be described in terms of a gas of noninteracting quasiparticles. The quasiparticles are unstable, with a lifetime set by the imaginary part of the lowest quasinormal mode frequency. If the horizon arises from an AdS-CFT style duality the quasiparticles are also the effective low-energy degrees of freedom of the finite-temperature CFT. We analyze a large class of models including Schwarzschild black holes, nonextremal Dp-branes, the rotating BTZ black hole and de Sitter space, and we comment on degenerate horizons. The quasiparticle description makes manifest the relationship between entropy and area

Forecasts of the capacity properties of Goterisskiy deposits of the eastern closure of the Predkopetdhskiy trough. [Siberia

Energy Technology Data Exchange (ETDEWEB)

Odekov, O.A.; Tulayev, S.V.

1982-01-01

Primary sedimentation porosity varies due to gravitational compaction of sediments, therefore its regular reduction with increase of bed depth is suggested. Relationships for determining the value of sediment compaction, coefficient of rock compaction, value of porosity, which is forecasted for a certain horizon are given. Based on data for the territory of Eastern Turkmenistan the pattern of change of collector properties of the Shatlyk horizon of Murgaskaya gas-bearing region and its analogs is established. A general emperical formula of porosity for the Eastern Turkmenistan is presented. Graphs of the relationships of capacity properties of the Lower Goterisskiy deposits for Eastern Turkmenistan and for the region of the eastern closure of the Predkopetdhskiy trough are plotted. Evidence is given of the good prospects of the Lower Cretaceous and especially the Lower Goterisskiy deposits of the region for natural gas from collector properties and from tectonic and lithofacial reasons.

Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

Science.gov (United States)

Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

2015-04-01

The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

Science.gov (United States)

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

2009-04-01

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

Predictive, Preventive and Personalised Medicine as the hardcore of ‘Horizon 2020’: EPMA position paper

Science.gov (United States)

2014-01-01

The European Association for Predictive, Preventive and Personalised Medicine (EPMA) considers acute problems in medical sciences as well as the quality and management of medical services challenging health care systems in Europe and worldwide. This actuality has motivated the representatives of EPMA to comment on the efforts in promoting an integrative approach based on multidisciplinary expertise to advance health care-related research and management. The current paper provides a global overview of the problems related to medical services: pandemic scenario in the progression of common non-communicable diseases, delayed interventional approaches of reactive medicine, poor economy of health care systems, lack of specialised educational programmes, problematic ethical aspects of several treatments as well as inadequate communication among professional groups and policymakers. In the form of individual paragraphs, the article presents a consolidated position of PPPM professionals towards the new European programme ‘Horizon 2020’ providing the long-lasting instruments for scientific and technological progress in medical services and health care-related programmes. In the author's opinion, Horizon 2020 provides unlimited room for research and implementation in Predictive, Preventive and Personalised Medicine. However, the overall success of the programme strongly depends on the effective communication and consolidation of professionals relevant for PPPM as well as the communication quality with policymakers. Smart political decision is the prerequisite of the effective PPPM implementation in the health care sector. This position is focused on the patients' needs, innovative medical sciences, optimal health and disease management, expert recommendations for the relevant medical fields and optimal solutions which have a potential to advance health care services if the long-term strategies were to be effectively implemented as proposed here. PMID:24708704

Nonlinear optics of fibre event horizons.

Science.gov (United States)

Webb, Karen E; Erkintalo, Miro; Xu, Yiqing; Broderick, Neil G R; Dudley, John M; Genty, Goëry; Murdoch, Stuart G

2014-09-17

The nonlinear interaction of light in an optical fibre can mimic the physics at an event horizon. This analogue arises when a weak probe wave is unable to pass through an intense soliton, despite propagating at a different velocity. To date, these dynamics have been described in the time domain in terms of a soliton-induced refractive index barrier that modifies the velocity of the probe. Here we complete the physical description of fibre-optic event horizons by presenting a full frequency-domain description in terms of cascaded four-wave mixing between discrete single-frequency fields, and experimentally demonstrate signature frequency shifts using continuous wave lasers. Our description is confirmed by the remarkable agreement with experiments performed in the continuum limit, reached using ultrafast lasers. We anticipate that clarifying the description of fibre event horizons will significantly impact on the description of horizon dynamics and soliton interactions in photonics and other systems.

Short-term wind power combined forecasting based on error forecast correction

International Nuclear Information System (INIS)

Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

2016-01-01

Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

UD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks

KAUST Repository

Dehwah, Ahmad H.

2017-04-11

Energy estimation and forecast represents an important role for energy management in solar-powered wireless sensor networks (WSNs). In general, the energy in such networks is managed over a finite time horizon in the future based on input solar power forecasts to enable continuous operation of the WSNs and achieve the sensing objectives while ensuring that no node runs out of energy. In this article, we propose a dynamic version of the weather conditioned moving average technique (UD-WCMA) to estimate and predict the variations of the solar power in a wireless sensor network. The presented approach combines the information from the real-time measurement data and a set of stored profiles representing the energy patterns in the WSNs location to update the prediction model. The UD-WCMA scheme is based on adaptive weighting parameters depending on the weather changes which makes it flexible compared to the existing estimation schemes without any precalibration. A performance analysis has been performed considering real irradiance profiles to assess the UD-WCMA prediction accuracy. Comparative numerical tests to standard forecasting schemes (EWMA, WCMA, and Pro-Energy) shows the outperformance of the new algorithm. The experimental validation has proven the interesting features of the UD-WCMA in real time low power sensor nodes.

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

Directory of Open Access Journals (Sweden)

Lukas Falat

2016-01-01

Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

Science.gov (United States)

Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

Black holes or firewalls: A theory of horizons

Science.gov (United States)

Nomura, Yasunori; Varela, Jaime; Weinberg, Sean J.

2013-10-01

We present a quantum theory of black hole (and other) horizons, in which the standard assumptions of complementarity are preserved without contradicting information theoretic considerations. After the scrambling time, the quantum mechanical structure of a black hole becomes that of an eternal black hole at the microscopic level. In particular, the stretched horizon degrees of freedom and the states entangled with them can be mapped into the near-horizon modes in the two exterior regions of an eternal black hole, whose mass is taken to be that of the evolving black hole at each moment. Salient features arising from this picture include (i) the number of degrees of freedom needed to describe a black hole is eA/2lP2, where A is the area of the horizon; (ii) black hole states having smooth horizons, however, span only an eA/4lP2-dimensional subspace of the relevant eA/2lP2-dimensional Hilbert space; (iii) internal dynamics of the horizon is such that an infalling observer finds a smooth horizon with a probability of 1 if a state stays in this subspace. We identify the structure of local operators responsible for describing semiclassical physics in the exterior and interior spacetime regions and show that this structure avoids the arguments for firewalls—the horizon can keep being smooth throughout the evolution. We discuss the fate of infalling observers under various circumstances, especially when the observers manipulate degrees of freedom before entering the horizon, and we find that an observer can never see a firewall by making a measurement on early Hawking radiation. We also consider the presented framework from the viewpoint of an infalling reference frame and argue that Minkowski-like vacua are not unique. In particular, the number of true Minkowski vacua is infinite, although the label discriminating these vacua cannot be accessed in usual nongravitational quantum field theory. An application of the framework to de Sitter horizons is also discussed.

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)

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.

29 CFR 1625.11 - Exemption for employees serving under a contract of unlimited tenure.

Science.gov (United States)

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Exemption for employees serving under a contract of unlimited tenure. 1625.11 Section 1625.11 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT... within the exemption can lawfully be forced to retire on account of age at age 70 (see paragraph (a)(1...

Forecasting extreme temperature health hazards in Europe

Science.gov (United States)

Di Napoli, Claudia; Pappenberger, Florian; Cloke, Hannah L.

2017-04-01

Extreme hot temperatures, such as those experienced during a heat wave, represent a dangerous meteorological hazard to human health. Heat disorders such as sunstroke are harmful to people of all ages and responsible for excess mortality in the affected areas. In 2003 more than 50,000 people died in western and southern Europe because of a severe and sustained episode of summer heat [1]. Furthermore, according to the Intergovernmental Panel on Climate Change heat waves are expected to get more frequent in the future thus posing an increasing threat to human lives. Developing appropriate tools for extreme hot temperatures prediction is therefore mandatory to increase public preparedness and mitigate heat-induced impacts. A recent study has shown that forecasts of the Universal Thermal Climate Index (UTCI) provide a valid overview of extreme temperature health hazards on a global scale [2]. UTCI is a parameter related to the temperature of the human body and its regulatory responses to the surrounding atmospheric environment. UTCI is calculated using an advanced thermo-physiological model that includes the human heat budget, physiology and clothing. To forecast UTCI the model uses meteorological inputs, such as 2m air temperature, 2m water vapour pressure and wind velocity at body height derived from 10m wind speed, from NWP models. Here we examine the potential of UTCI as an extreme hot temperature prediction tool for the European area. UTCI forecasts calculated using above-mentioned parameters from ECMWF models are presented. The skill in predicting UTCI for medium lead times is also analysed and discussed for implementation to international health-hazard warning systems. This research is supported by the ANYWHERE project (EnhANcing emergencY management and response to extreme WeatHER and climate Events) which is funded by the European Commission's HORIZON2020 programme. [1] Koppe C. et al., Heat waves: risks and responses. World Health Organization. Health and

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

Science.gov (United States)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

A multiscale forecasting method for power plant fleet management

Science.gov (United States)

Chen, Hongmei

In recent years the electric power industry has been challenged by a high level of uncertainty and volatility brought on by deregulation and globalization. A power producer must minimize the life cycle cost while meeting stringent safety and regulatory requirements and fulfilling customer demand for high reliability. Therefore, to achieve true system excellence, a more sophisticated system-level decision-making process with a more accurate forecasting support system to manage diverse and often widely dispersed generation units as a single, easily scaled and deployed fleet system in order to fully utilize the critical assets of a power producer has been created as a response. The process takes into account the time horizon for each of the major decision actions taken in a power plant and develops methods for information sharing between them. These decisions are highly interrelated and no optimal operation can be achieved without sharing information in the overall process. The process includes a forecasting system to provide information for planning for uncertainty. A new forecasting method is proposed, which utilizes a synergy of several modeling techniques properly combined at different time-scales of the forecasting objects. It can not only take advantages of the abundant historical data but also take into account the impact of pertinent driving forces from the external business environment to achieve more accurate forecasting results. Then block bootstrap is utilized to measure the bias in the estimate of the expected life cycle cost which will actually be needed to drive the business for a power plant in the long run. Finally, scenario analysis is used to provide a composite picture of future developments for decision making or strategic planning. The decision-making process is applied to a typical power producer chosen to represent challenging customer demand during high-demand periods. The process enhances system excellence by providing more accurate market

Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

Directory of Open Access Journals (Sweden)

Jinyin Ye

2016-01-01

Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

Nonlinear solar cycle forecasting: theory and perspectives

Directory of Open Access Journals (Sweden)

A. L. Baranovski

2008-02-01

Full Text Available In this paper we develop a modern approach to solar cycle forecasting, based on the mathematical theory of nonlinear dynamics. We start from the design of a static curve fitting model for the experimental yearly sunspot number series, over a time scale of 306 years, starting from year 1700 and we establish a least-squares optimal pulse shape of a solar cycle. The cycle-to-cycle evolution of the parameters of the cycle shape displays different patterns, such as a Gleissberg cycle and a strong anomaly in the cycle evolution during the Dalton minimum. In a second step, we extract a chaotic mapping for the successive values of one of the key model parameters – the rate of the exponential growth-decrease of the solar activity during the n-th cycle. We examine piece-wise linear techniques for the approximation of the derived mapping and we provide its probabilistic analysis: calculation of the invariant distribution and autocorrelation function. We find analytical relationships for the sunspot maxima and minima, as well as their occurrence times, as functions of chaotic values of the above parameter. Based on a Lyapunov spectrum analysis of the embedded mapping, we finally establish a horizon of predictability for the method, which allows us to give the most probable forecasting of the upcoming solar cycle 24, with an expected peak height of 93±21 occurring in 2011/2012.

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

Science.gov (United States)

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

Cemented Horizons and Hardpans in the Coastal Tablelands of Northeastern Brazil

Directory of Open Access Journals (Sweden)

João Bosco Vasconcellos Gomes

Full Text Available ABSTRACT Horizons with varying degrees of cementation are a common feature of the soils from the coastal tablelands of Northeastern Brazil. In most cases, these horizons are represented by the following subsurface horizons: fragipan, duripan, ortstein, and placic. The aims of this study were to analyze differences regarding the development and the degree of expression of cementation in soils from the coastal tablelands of Northeastern Brazil: Planossolo Háplico (p-SX, Espodossolo Humilúvico (p-EK, Espodossolo Ferrihumilúvico (p-ESK, and Argissolo Acinzentado (p-PAC pedons. The pedons studied displayed features related to drainage impediments. The cemented horizons from p-SX and p-EK had the same designation (Btgm, displaying a duric character that coincided with gleization features and are under podzolized horizons. In the p-ESK, the podzolization process is of such magnitude that it leads to the cementation of its own spodic horizons, which were both of the ortstein type (Bhsx and Bsm. In the p-PAC cementation is observed in two placic horizons and in the Btx/Bt horizon, as well as in the upper parts of the Bt/Btx horizon. Analysis of the micrographies from the cemented horizons showed predominance of a low porosity matrix. Such porosity is relatively greater in the horizons of “x” subscript than in the horizons with duric character. The Fe segregation lines were notable in the cemented horizons from p-EK and p-PAC, which corroborates the presence of placic horizons in such pedons. The preponderance of kaolinite in the clay fraction was widely verified in all the cemented horizons analyzed. Water immersion tests were the criteria adopted to define the duric character of the Btgm horizons from p-SX and p-EK, and in the Bsm horizon from the p-ESK. These tests were also used to confirm field morphology. In most cases, the maximum values of Fe, Al, and Si, determined by different extractions, occurred in positions overlaying the cemented

VMware Horizon Workspace essentials

CERN Document Server

von Oven, Peter; Lindberg, Joel

2014-01-01

This book uses a step-by-step approach to teach you how to design, deploy, and manage a Horizon Workspace based on real world experience. Written in an easy-to-follow style, this book explains the terminology in a clear and concise manner. Each feature is explained starting at a high level and then drilling down into the technical detail, using diagrams and screenshots.This book is perfect for IT administrators who want to deploy a solution to centrally manage access to corporate applications, data, and virtual desktops using Horizon Workspace. You need to have some experience in delivering BY

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...

Microbiomes structure and diversity in different horizons of full soil profiles

Science.gov (United States)

Chernov, Timofey; Tkhakakhova, Azida; Zhelezova, Alena; Semenov, Mikhail; Kutovaya, Olga

2017-04-01

Topsoil is a most common object for soil metagenomic studies; sometimes soil profile is being formally split in layers by depth. However, Russian Soil Science School formulated the idea of soil profile as a complex of soil horizons, which can differ in their properties and genesis. In this research we analyzed 57 genetic soil horizons of 8 different soils from European part of Russia: Albeluvisol, Greyzemic Phaeozem, three Chermozems (different land use - till, fallow, wind-protecting tree line), Rhodic Cambisol, Haplic Kastanozem and Salic Solonetz (WRB classification). Sampling was performed from all genetic horizons in each soil profile starting from topsoil until subsoil. Total DNA was extracted and 16S rRNA sequencing was provided together with chemical analysis of soil (pH measurement, C and N contents, etc.). Structure and diversity of prokaryotic community are significantly different in those soil horizons, which chemical properties and processes of origin are contrasting with nearest horizons: Na-enriched horizon of Solonetz, eluvial horizon of Albeluvisol, plough pan of Agrochernozem. Actinobacteria were abundant in top horizons of soils in warm and dry climate, while Acidobacteria had the highest frequency in soils of moist and cold regions. Concerning Archaea, Thaumarchaeota prevailed in all studied soils. Their rate was higher in microbiomes of upper horizons of steppe soils and it was reducing with depth down the profile. Prokaryotic communities in Chernozems were clustered by soil horizons types: microbiomes of A (organic topsoil) and B (mineral) horizons formed non-overlapping clusters by principal component analysis, cluster formed by prokaryotic communities of transitional soil horizons (AB) take place between clusters of A and B horizons. Moreover, prokaryotic communities of A horizons differ from each other strongly, while microbiomes of B horizons formed a narrow small cluster. It must be explaned by more diverse conditions in upper A horizons

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...

A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset

International Nuclear Information System (INIS)

Deo, Ravinesh C.; Wen, Xiaohu; Qi, Feng

2016-01-01

analysis with single predictor variables yielded the best performance with S_t as an input, confirming that the largest contributions for forecasting solar energy is derived from the sunshine hours per day compared to the other prescribed inputs. All six inputs were required in the optimum W-SVM for Brisbane and Cairns stations to yield r = 0.928, d = 0.927, E_N_S = 0.858, P_d_v = 1.757%, MAE = 1.819 MJ m"−"2 and r = 0.881, d = 0.870, E_N_S = 0.762, P_d_v = 9.633%, MAE = 2.086 MJ m"−"2, respectively. However, for Townsville, the time-series of S_t, T_m_i_n and T_m_a_x and E were required in the optimum model to yield r = 0.858, d = 0.886, E_N_S = 0.722, P_d_v = 10.282% and MAE = 2.167 MJ m"−"2. In terms of the relative model errors over daily forecast horizon, W-SVM model was the most accurate precise for Townsville (RRMSE = 12.568%; MAPE = 12.666%) followed by Brisbane (13.313%; 13.872%) and Cairns (14.467%; 15.675%) weather stations. A set of alternative models developed over the monthly, seasonal and annual forecast horizons verified the long-term forecasting skill, where lagged inputs of T_m_a_x, T_m_i_n, E, P and VP for Roma Post Office and Toowoomba Regional stations were employed. The wavelet-coupled model performed well, with r = 0.965, d = 0.964, P_d_v = 2.249%, RRMSE = 5.942% and MAPE = 4.696% (Roma) and r = 0.958, d = 0.943, P_d_v = 0.979%, RRMSE = 7.66% and MAPE = 6.20% (Toowoomba). Accordingly, the results conclusively ascertained the importance of wavelet-coupled SVM predictive model as a qualified stratagem for short and long-term forecasting of solar energy for assessment of solar energy prospectivity in this study region.

Stock Return and Cash Flow Predictability: The Role of Volatility Risk

DEFF Research Database (Denmark)

Bollerslev, Tim; Xu, Lai; Zhou, Hao

risk premium positively forecast both short-horizon returns and dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it cannot forecast dividend growth rates. Our equilibrium-based “structural” factor GARCH model permits much more accurate...

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 ...

Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

DEFF Research Database (Denmark)

Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

accuracy metric evaluated for wind speed data consistently translates to an improvement for wind power. For two time series describing the temporal development of the same variable, though by different means, it is assumed that phase errors account for most of the departure from perfect correlation between...... the two time series. Results on limited-area NWP model performance, with focus on the 12th to 48th forecast hour horizon relevant for Elspot auction bidding on the Nord Pool Spot market [2], are presented....

The influence of time horizon on results of cost-effectiveness analyses.

Science.gov (United States)

Kim, David D; Wilkinson, Colby L; Pope, Elle F; Chambers, James D; Cohen, Joshua T; Neumann, Peter J

2017-12-01

Debates persist on the appropriate time horizon from a payer's perspective and how the time horizon in cost-effectiveness analysis (CEA) influences the value assessment. We systematically reviewed the Tufts Medical Center CEA Registry and identified US-based studies that used a payer perspective from 2005-2014. We classified the identified CEAs as short-term (time horizon ≤ 5 years) and long-term (> 5 years), and examined associations between study characteristics and the specified time horizon. We also developed case studies with selected interventions to further explore the relationship between time horizon and projected costs, benefits, and incremental cost-effectiveness ratios (ICER). Among 782 identified studies that met our inclusion criteria, 552 studies (71%) utilized a long-term time horizon while 198 studies (25%) used a short-term horizon. Among studies that employed multiple time horizons, the extension of the time horizon yielded more favorable ICERs in 19 cases and less favorable ICERs in 4 cases. Case studies showed the use of a longer time horizon also yielded more favorable ICERs. The assumed time horizon in CEAs can substantially influence the value assessment of medical interventions. To capture all consequences, we encourage the use of time horizons that extend sufficiently into the future.

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)

Cosmological event horizons, thermodynamics, and particle creation

International Nuclear Information System (INIS)

Gibbons, G.W.; Hawking, S.W.

1977-01-01

It is shown that the close connection between event horizons and thermodynamics which has been found in the case of black holes can be extended to cosmological models with a repulsive cosmological constant. An observer in these models will have an event horizon whose area can be interpreted as the entropy or lack of information of the observer about the regions which he cannot see. Associated with the event horizon is a surface gravity kappa which enters a classical ''first law of event horizons'' in a manner similar to that in which temperature occurs in the first law of thermodynamics. It is shown that this similarity is more than an analogy: An observer with a particle detector will indeed observe a background of thermal radiation coming apparently from the cosmological event horizon. If the observer absorbs some of this radiation, he will gain energy and entropy at the expense of the region beyond his ken and the event horizon will shrink. The derivation of these results involves abandoning the idea that particles should be defined in an observer-independent manner. They also suggest that one has to use something like the Everett-Wheeler interpretation of quantum mechanics because the back reaction and hence the spacetime metric itself appear to be observer-dependent, if one assumes, as seems reasonable, that the detection of a particle is accompanied by a change in the gravitational field

A 'destination port' for the Brazilian electric system. Characteristics of the Brazilian integrated electric systems and forecasting up to the year 2035

International Nuclear Information System (INIS)

Alvim, Carlos Feu coord.; Vargas, Jose Israel; Silva, Oothon Luiz Pinheiro da; Ferreira, Omar Campos; Eidelman, Frida

2005-01-01

In order to establish a policy for the Electric System in Brazil it is necessary to foresee its future. In a predominantly hydroelectric system where thermal complementation is being introduced, a thirty-year horizon seems to be adequate for forecasting its port of destination and establishing its route to get there. The study describes the existing model, studies its regulation and projects the macro economic scenario, the electricity demand and the necessary generation park. (author)

Protective effect of inhaled budesonide against unlimited airway narrowing to methacholine in atopic patients with asthma

NARCIS (Netherlands)

Booms, P.; Cheung, D.; Timmers, M. C.; Zwinderman, A. H.; Sterk, P. J.

1997-01-01

Patients with asthma who have moderate to severe airway hyperresponsiveness often demonstrate progressive, unlimited airway narrowing in response to inhaled bronchoconstrictor stimuli, which is likely to be due to inflammatory changes within the airway wall. It is unknown whether regular therapy

Horizon quantum mechanics of rotating black holes

Energy Technology Data Exchange (ETDEWEB)

Casadio, Roberto [Universita di Bologna, Dipartimento di Fisica e Astronomia, Bologna (Italy); I.N.F.N., Sezione di Bologna, I.S. FLAG, Bologna (Italy); Giugno, Andrea [Ludwig-Maximilians-Universitaet, Arnold Sommerfeld Center, Munich (Germany); Giusti, Andrea [Universita di Bologna, Dipartimento di Fisica e Astronomia, Bologna (Italy); I.N.F.N., Sezione di Bologna, I.S. FLAG, Bologna (Italy); Ludwig-Maximilians-Universitaet, Arnold Sommerfeld Center, Munich (Germany); Micu, Octavian [Institute of Space Science, Bucharest, P.O. Box MG-23, Bucharest-Magurele (Romania)

2017-05-15

The horizon quantum mechanics is an approach that was previously introduced in order to analyze the gravitational radius of spherically symmetric systems and compute the probability that a given quantum state is a black hole. In this work, we first extend the formalism to general space-times with asymptotic (ADM) mass and angular momentum. We then apply the extended horizon quantum mechanics to a harmonic model of rotating corpuscular black holes. We find that simple configurations of this model naturally suppress the appearance of the inner horizon and seem to disfavor extremal (macroscopic) geometries. (orig.)

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

Bootstrap, universality and horizons

Energy Technology Data Exchange (ETDEWEB)

Chang, Chi-Ming [Center for Theoretical Physics and Department of Physics,University of California, Berkeley, CA 94704 (United States); Lin, Ying-Hsuan [Jefferson Physical Laboratory, Harvard University,Cambridge, MA 02138 (United States)

2016-10-13

We present a closed form expression for the semiclassical OPE coefficients that are universal for all 2D CFTs with a “weak” light spectrum, by taking the semiclassical limit of the fusion kernel. We match this with a properly regularized and normalized bulk action evaluated on a geometry with three conical defects, analytically continued in the deficit angles beyond the range for which a metric with positive signature exists. The analytically continued geometry has a codimension-one coordinate singularity surrounding the heaviest conical defect. This singularity becomes a horizon after Wick rotating to Lorentzian signature, suggesting a connection between universality and the existence of a horizon.

Redshift of a photon emitted along the black hole horizon

Energy Technology Data Exchange (ETDEWEB)

Toporensky, A.V. [Lomonosov Moscow State University, Sternberg Astronomical Institute, Moscow (Russian Federation); Kazan Federal University, Kazan (Russian Federation); Zaslavskii, O.B. [Kazan Federal University, Kazan (Russian Federation); Kharkov V.N. Karazin National University, Department of Physics and Technology, Kharkov (Ukraine)

2017-03-15

In this work we derive some general features of the redshift measured by radially moving observers in the black hole background. Let observer 1 cross the black hole horizon emitting a photon, while observer 2 crossing the same horizon later receives it. We show that if (i) the horizon is the outer one (event horizon) and (ii) it is nonextremal, the received frequency is redshifted. This generalizes recent results in the literature. For the inner horizon (like in the Reissner-Nordstroem metric) the frequency is blueshifted. If the horizon is extremal, the frequency does not change. We derive explicit formulas describing the frequency shift in generalized Kruskal- and Lemaitre-like coordinates. (orig.)

Pricing Liquidity Risk with Heterogeneous Investment Horizons

NARCIS (Netherlands)

Beber, Alessandro; Driessen, Joost; Neuberger, A.; Tuijp, P

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk)

Reflection, radiation, and interference near the black hole horizon

International Nuclear Information System (INIS)

Kuchiev, M.Yu.

2004-01-01

The event horizon of black holes is capable of reflection: there is a finite probability for any particle that approaches the horizon to bounce back. The albedo of the horizon depends on the black hole temperature and the energy of the incoming particle. The reflection shares its physical origins with the Hawking process of radiation; both of them arise as consequences of the mixing of the incoming and outgoing waves that takes place due to quantum processes on the event horizon

Plasmonic Horizon in Gold Nanosponges.

Science.gov (United States)

Vidal, Cynthia; Sivun, Dmitry; Ziegler, Johannes; Wang, Dong; Schaaf, Peter; Hrelescu, Calin; Klar, Thomas A

2018-02-14

An electromagnetic wave impinging on a gold nanosponge coherently excites many electromagnetic hot-spots inside the nanosponge, yielding a polarization-dependent scattering spectrum. In contrast, a hole, recombining with an electron, can locally excite plasmonic hot-spots only within a horizon given by the lifetime of localized plasmons and the speed carrying the information that a plasmon has been created. This horizon is about 57 nm, decreasing with increasing size of the nanosponge. Consequently, photoluminescence from large gold nanosponges appears unpolarized.

Quantum-corrected geometry of horizon vicinity

Energy Technology Data Exchange (ETDEWEB)

Park, I.Y. [Department of Applied Mathematics, Philander Smith College, Little Rock, AR (United States)

2017-12-15

We study the deformation of the horizon-vicinity geometry caused by quantum gravitational effects. Departure from the semi-classical picture is noted, and the fact that the matter part of the action comes at a higher order in Newton's constant than does the Einstein-Hilbert term is crucial for the departure. The analysis leads to a Firewall-type energy measured by an infalling observer for which quantum generation of the cosmological constant is critical. The analysis seems to suggest that the Firewall should be a part of such deformation and that the information be stored both in the horizon-vicinity and asymptotic boundary region. We also examine the behavior near the cosmological horizon. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Quantum-corrected geometry of horizon vicinity

International Nuclear Information System (INIS)

Park, I.Y.

2017-01-01

We study the deformation of the horizon-vicinity geometry caused by quantum gravitational effects. Departure from the semi-classical picture is noted, and the fact that the matter part of the action comes at a higher order in Newton's constant than does the Einstein-Hilbert term is crucial for the departure. The analysis leads to a Firewall-type energy measured by an infalling observer for which quantum generation of the cosmological constant is critical. The analysis seems to suggest that the Firewall should be a part of such deformation and that the information be stored both in the horizon-vicinity and asymptotic boundary region. We also examine the behavior near the cosmological horizon. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

QFT holography near the horizon of Schwarzschild-like spacetimes

OpenAIRE

Moretti, Valter; Pinamonti, Nicola

2003-01-01

It is argued that free QFT can be defined on the event horizon of a Schwarzschild-like spacetime and that this theory is unitarily and algebraically equivalent to QFT in the bulk (near the horizon). Under that unitary equivalence the bulk hidden SL(2,R) symmetry found in a previous work becomes manifest on the event horizon, it being induced by a group of horizon diffeomorphisms. The class of generators of that group can be enlarged to include a full Virasoro algebra of fields which are defin...

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

Hydrological classification of orthic A horizons in Weatherley, South ...

African Journals Online (AJOL)

Orthic A horizons carry little interpretive, especially hydrological, value. This paper aims to elucidate the hydrological interpretation of orthic A horizons. Measured water contents in the orthic A horizons of 28 profiles in the Weatherley catchment of South Africa were used to classify the topsoils into wetness classes. The very ...

Competition, Time Horizon and Corporate Social Performance

NARCIS (Netherlands)

Graafland, J.J.; Smid, H.

2013-01-01

Abstract: This paper develops and tests a conceptual framework on the relationships between competition, time horizon and corporate social performance (CSP). We hypothesize that more intense competition discourages CSP by lowering the time horizon of companies. We test the hypothesis on a sample of

Maximal indecomposable past sets and event horizons

International Nuclear Information System (INIS)

Krolak, A.

1984-01-01

The existence of maximal indecomposable past sets MIPs is demonstrated using the Kuratowski-Zorn lemma. A criterion for the existence of an absolute event horizon in space-time is given in terms of MIPs and a relation to black hole event horizon is shown. (author)

Forecasting telecommunication new service demand by analogy method and combined forecast

Directory of Open Access Journals (Sweden)

Lin Feng-Jenq

2005-01-01

Full Text Available In the modeling forecast field, we are usually faced with the more difficult problems of forecasting market demand for a new service or product. A new service or product is defined as that there is absence of historical data in this new market. We hardly use models to execute the forecasting work directly. In the Taiwan telecommunication industry, after liberalization in 1996, there are many new services opened continually. For optimal investment, it is necessary that the operators, who have been granted the concessions and licenses, forecast this new service within their planning process. Though there are some methods to solve or avoid this predicament, in this paper, we will propose one forecasting procedure that integrates the concept of analogy method and the idea of combined forecast to generate new service forecast. In view of the above, the first half of this paper describes the procedure of analogy method and the approach of combined forecast, and the second half provides the case of forecasting low-tier phone demand in Taiwan to illustrate this procedure's feasibility.

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

Science.gov (United States)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

Methodology for forecasting in the Swedish–Norwegian market for el-certificates

International Nuclear Information System (INIS)

Wolfgang, Ove; Jaehnert, Stefan; Mo, Birger

2015-01-01

In this paper we describe a novel methodology for forecasting in the Swedish–Norwegian el-certificate market, which is a variant of a tradable green certificate scheme. For the forecasting, the el-certificate market is integrated in the electricity-market model EMPS, which has weekly to hourly time-step length, whereas the planning horizon can be several years. Strategies for the certificate inventory are calculated by stochastic dynamic programming, whereas penalty-rates for non-compliance during the annual settlement of certificates are determined endogenously. In the paper the methodology is described, and we show the performance of the model under different cases that can occur in the el-certificate market. The general results correspond to theoretical findings in previous studies for tradable green certificate markets, in particular that price-scenarios spread out in such a way that the unconditional expected value of certificates is relatively stable throughout the planning period. In addition the presented methodologies allows to assess the actual dynamics of the certificate price due to climatic uncertainty. Finally, special cases are indentified where the certificate price becomes excessively high respectively zero, due the design-specific dynamics of the penalty rate. - Highlights: • A method for forecasting in the Swedish–Norwegian el-certificate market is proposed. • The developed model integrates the el-certificate and the power market. • Banking of certificates and the endogenously calculated penalty rate are included. • The certificate value is calculated using Stochastic-Dynamic-Programming. • Price dynamics due to climatic weather uncertainties are assessed and illustrated

High Resolution Air Quality Forecasts in the Western Mediterranean area within the MACC, MACC-II and MACC-III European projects

Energy Technology Data Exchange (ETDEWEB)

Cansado, A.; Martinez, I.; Morales, T.

2015-07-01

The European Earth observation programme Copernicus, formerly known as GMES (Global Monitoring for Environment and Security) is establishing a core global and regional environmental atmospheric service as a component of the Europes Copernicus/GMES initiative through successive R and D projects led by ECMWF (European Center for Medium-range Weather Forecasting) and funded by the 6th and 7th European Framework Programme for Research and Horizon 2020 Programme: GEMS, MACC, MACC-II and MACC-III. AEMET (Spanish State Meteorological Agency) has participated in the projects MACC and MACC-II and continues participating in MACC-III (http://atmosphere.copernicus.eu). AEMET has contributed to those projects by generating highresolution (0.05 degrees) daily air-quality forecasts for the Western Mediterranean up to 48 hours aiming to analyse the dependence of the quality of forecasts on resolution. We monitor the evolution of different chemical species such as NO{sub 2}, O{sub 3}, CO y SO{sub 2} at surface and different vertical levels using the global model MOCAGE and the MACC Regional Ensemble forecasts as chemical boundary conditions. We will show different case-studies, where the considered chemical species present high values and will show a validation of the air-quality by comparing to some of the available air-quality observations (EMEP/GAW, regional -autonomous communities- and local -city councils- air-quality monitoring networks) over the forecast domain. The aim of our participation in these projects is helping to improve the understanding of the processes involved in the air-quality forecast in the Mediterranean where special factors such as highly populated areas together with an intense solar radiation make air-quality forecasting particularly challenging. (Author)

High Resolution Air Quality Forecasts in the Western Mediterranean area within the MACC, MACC-II and MACC-III European projects

Energy Technology Data Exchange (ETDEWEB)

Cansado, A.; Martinez, I.; Morales, T.

2015-07-01

The European Earth observation programme Copernicus, formerly known as GMES (Global Monitoring for Environment and Security) is establishing a core global and regional environmental atmospheric service as a component of the Europe’s Copernicus/GMES initiative through successive R&D projects led by ECMWF (European Center for Medium-range Weather Forecasting) and funded by the 6th and 7th European Framework Programme for Research and Horizon 2020 Programme: GEMS, MACC, MACC-II and MACC-III. AEMET (Spanish State Meteorological Agency) has participated in the projects MACC and MACC-II and continues participating in MACC-III (http://atmosphere.copernicus.eu). AEMET has contributed to those projects by generating highresolution (0.05 degrees) daily air-quality forecasts for the Western Mediterranean up to 48 hours aiming to analyse the dependence of the quality of forecasts on resolution. We monitor the evolution of different chemical species such as NO2, O3, CO y SO2 at surface and different vertical levels using the global model MOCAGE and the MACC Regional Ensemble forecasts as chemical boundary conditions. We will show different case-studies, where the considered chemical species present high values and will show a validation of the air-quality by comparing to some of the available air-quality observations (EMEP/GAW, regional -autonomous communities- and local -city councils- air-quality monitoring networks) over the forecast domain. The aim of our participation in these projects is helping to improve the understanding of the processes involved in the air-quality forecast in the Mediterranean where special factors such as highly populated areas together with an intense solar radiation make air-quality forecasting particularly challenging. (Author)

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

Energy Technology Data Exchange (ETDEWEB)

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-09-01

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

Cosmological horizons as new examples of the membrane paradigm

International Nuclear Information System (INIS)

Wang, Tower

2015-01-01

In this paper we aim to provide new examples of the application and the generality of the membrane paradigm. The membrane paradigm is a formalism for studying the event horizon of black holes. After analyzing it with some technical details and realizing it in the Reissner–Nordström black hole, we apply the paradigm to cosmological horizons, first to the pure de Sitter horizon, and then to the trapping horizon of the Friedmann–Lemaître–Robertson–Walker Universe. In the latter case, the cosmological stretched horizon is oblique, thus the running of the renormalization parameter is nonzero in the timelike direction and gives a correction to the membrane pressure. In this paradigm, the cosmological equations come from continuity equations of the membrane fluid and the bulk fluid respectively. (paper)

The absence of horizon in black-hole formation

Energy Technology Data Exchange (ETDEWEB)

Ho, Pei-Ming, E-mail: pmho@phys.ntu.edu.tw

2016-08-15

With the back-reaction of Hawking radiation taken into consideration, the work of Kawai, Matsuo and Yokokura [1] has shown that, under a few assumptions, the collapse of matter does not lead to event horizon nor apparent horizon. In this paper, we relax their assumptions and elaborate on the space-time geometry of a generic collapsing body with spherical symmetry. The geometry outside the collapsing sphere is found to be approximated by the geometry outside the white-hole horizon, hence the collapsing matter remains outside the Schwarzschild radius. As particles in Hawking radiation are created in the vicinity of the collapsing matter, the information loss paradox is alleviated. Assuming that the collapsing body evaporates within finite time, there is no event horizon.

The absence of horizon in black-hole formation

Directory of Open Access Journals (Sweden)

Pei-Ming Ho

2016-08-01

Full Text Available With the back-reaction of Hawking radiation taken into consideration, the work of Kawai, Matsuo and Yokokura [1] has shown that, under a few assumptions, the collapse of matter does not lead to event horizon nor apparent horizon. In this paper, we relax their assumptions and elaborate on the space-time geometry of a generic collapsing body with spherical symmetry. The geometry outside the collapsing sphere is found to be approximated by the geometry outside the white-hole horizon, hence the collapsing matter remains outside the Schwarzschild radius. As particles in Hawking radiation are created in the vicinity of the collapsing matter, the information loss paradox is alleviated. Assuming that the collapsing body evaporates within finite time, there is no event horizon.

The absence of horizon in black-hole formation

International Nuclear Information System (INIS)

Ho, Pei-Ming

2016-01-01

With the back-reaction of Hawking radiation taken into consideration, the work of Kawai, Matsuo and Yokokura [1] has shown that, under a few assumptions, the collapse of matter does not lead to event horizon nor apparent horizon. In this paper, we relax their assumptions and elaborate on the space-time geometry of a generic collapsing body with spherical symmetry. The geometry outside the collapsing sphere is found to be approximated by the geometry outside the white-hole horizon, hence the collapsing matter remains outside the Schwarzschild radius. As particles in Hawking radiation are created in the vicinity of the collapsing matter, the information loss paradox is alleviated. Assuming that the collapsing body evaporates within finite time, there is no event horizon.

Application of integrated data mining techniques in stock market forecasting

Directory of Open Access Journals (Sweden)

Chin-Yin Huang

2014-12-01

Full Text Available Stock market is considered too uncertain to be predictable. Many individuals have developed methodologies or models to increase the probability of making a profit in their stock investment. The overall hit rates of these methodologies and models are generally too low to be practical for real-world application. One of the major reasons is the huge fluctuation of the market. Therefore, the current research focuses in the stock forecasting area is to improve the accuracy of stock trading forecast. This paper introduces a system that addresses the particular need. The system integrates various data mining techniques and supports the decision-making for stock trades. The proposed system embeds the top-down trading theory, artificial neural network theory, technical analysis, dynamic time series theory, and Bayesian probability theory. To experimentally examine the trading return of the presented system, two examples are studied. The first uses the Taiwan Semiconductor Manufacturing Company (TSMC data-set that covers an investment horizon of 240 trading days from 16 February 2011 to 23 January 2013. Eighty four transactions were made using the proposed approach and the investment return of the portfolio was 54% with an 80.4% hit rate during a 12-month period in which the TSMC stock price increased by 25% (from $NT 78.5 to $NT 101.5. The second example examines the stock data of Evergreen Marine Corporation, an international marine shipping company. Sixty four transactions were made and the investment return of the portfolio was 128% in 12 months. Given the remarkable investment returns in trading the example TSMC and Evergreen stocks, the proposed system demonstrates promising potentials as a viable tool for stock market forecasting.

Beyond the veil: Inner horizon instability and holography

International Nuclear Information System (INIS)

Balasubramanian, Vijay; Levi, Thomas S.

2004-01-01

We show that scalar perturbations of the eternal, rotating Banados-Teitelboim-Zanelli (BTZ) black hole should lead to an instability of the inner (Cauchy) horizon, preserving strong cosmic censorship. Because of backscattering from the geometry, plane-wave modes have a divergent stress tensor at the event horizon, but suitable wave packets avoid this difficulty, and are dominated at late times by quasinormal behavior. The wave packets have cuts in the complexified coordinate plane that are controlled by requirements of continuity, single-valuedness, and positive energy. Due to a focusing effect, regular wave packets nevertheless have a divergent stress energy at the inner horizon, signaling an instability. We propose that this instability, which is localized behind the event horizon, is detected holographically as a breakdown in the semiclassical computation of dual conformal field theory (CFT) expectation values in which the analytic behavior of wave packets in the complexified coordinate plane plays an integral role. In the dual field theory, this is interpreted as an encoding of physics behind the horizon in the entanglement between otherwise independent CFTs

Signature for the absence of an event horizon

International Nuclear Information System (INIS)

Barbieri, James; Chapline, George

2012-01-01

One of the most celebrated predictions of general relativity is that compact astrophysical objects with masses greater than a few solar masses are surrounded by an event horizon where time stands still and communication from the interior to the exterior is cutoff. Despite profound theoretical reasons for doubting whether an event horizon is physically possible, no definitive test as to whether event horizons really exist has yet been proposed. In this Letter we propose an experimental signature for the non-existence of event horizons. In particular we point out that a sharp dip in the spectrum of π 0 decay gamma rays below 70 MeV coming from compact objects with masses exceeding a few solar masses would be definitive evidence that these objects have a physical surface and there is no event horizon. Observation of such gamma rays would also for the first time open an experimental window on physical processes at energies near to the Planck scale. The prospects for seeing the 70 MeV feature in the near future are briefly discussed.

Xenogeneic chimera-Generated by blastocyst complementation-As a potential unlimited source of recipient-tailored organs.

Science.gov (United States)

Oldani, Graziano; Peloso, Andrea; Lacotte, Stéphanie; Meier, Raphael; Toso, Christian

2017-07-01

Blastocyst complementation refers to the injection of cells into a blastocyst. The technology allows for the creation of chimeric animals, which have the potential to be used as an unlimited source of organ donors. Pluripotent stem cells could be generated from a patient in need of a transplantation and injected into a large animal blastocyst (potentially of a pig), leading to the creation of organ(s) allowing immunosuppression-free transplantation. Various chimera combinations have already been generated, but one of the most recent steps leads to the creation of human-pig chimeras, which could be studied at an embryo stage. Although still far from clinical reality, the potential application is almost unlimited. The present review illustrates the historical steps of intra- and interspecific blastocyst complementation in rodents and large animals, specifically looking at its potential for generation of organ grafts. We also speculate on how it could change transplant indications, on its economic impact, and on the linked ethical concerns. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Hawking radiation of an apparent horizon in a FRW universe

International Nuclear Information System (INIS)

Cai Ronggen; Cao Liming; Hu Yapeng

2009-01-01

Hawking radiation is an important quantum phenomenon of a black hole, which is closely related to the existence of an event horizon of a black hole. The cosmological event horizon of de Sitter space is also of Hawking radiation with a thermal spectrum. By use of the tunneling approach, we show that there is indeed a Hawking radiation with temperature, T=1/(2πr-tilde A , for a locally defined apparent horizon of a Friedmann-Robertson-Walker universe with any spatial curvature, where r-tilde A is the apparent horizon radius. Thus we fill in the gap existing in the literature investigating the relation between the first law of thermodynamics and Friedmann equations; there the apparent horizon is assumed to have such a temperature without any proof. In addition, we stress the implication of the Hawking temperature associated with the apparent horizon.

Black hole entropy, universality, and horizon constraints

International Nuclear Information System (INIS)

Carlip, Steven

2006-01-01

To ask a question about a black hole in quantum gravity, one must restrict initial or boundary data to ensure that a black hole is actually present. For two-dimensional dilaton gravity, and probably a much wider class of theories, I show that the imposition of a 'stretched horizon' constraint modifies the algebra of symmetries at the horizon, allowing the use of conformal field theory techniques to determine the asymptotic density of states. The result reproduces the Bekenstein-Hawking entropy without any need for detailed assumptions about the microscopic theory. Horizon symmetries may thus offer an answer to the problem of universality of black hole entropy

Black hole entropy, universality, and horizon constraints

Energy Technology Data Exchange (ETDEWEB)

Carlip, Steven [Department of Physics, University of California, Davis, CA 95616 (United States)

2006-03-01

To ask a question about a black hole in quantum gravity, one must restrict initial or boundary data to ensure that a black hole is actually present. For two-dimensional dilaton gravity, and probably a much wider class of theories, I show that the imposition of a 'stretched horizon' constraint modifies the algebra of symmetries at the horizon, allowing the use of conformal field theory techniques to determine the asymptotic density of states. The result reproduces the Bekenstein-Hawking entropy without any need for detailed assumptions about the microscopic theory. Horizon symmetries may thus offer an answer to the problem of universality of black hole entropy.

The NMC Horizon Report: 2015 Museum Edition

Science.gov (United States)

Johnson, L.; Adams Becker, S.; Estrada, V.; Freeman, A.

2015-01-01

The internationally recognized series of "Horizon Reports" is part of the New Media Consortium's Horizon Project, a comprehensive research venture established in 2002 that identifies and describes emerging technologies likely to have a large impact over the coming years on a variety of sectors around the globe. This "2015 Horizon…

Unlimited Energy Gain in the Laser-Driven Radiation Pressure Dominant Acceleration of Ions

OpenAIRE

Bulanov, S. V.; Echkina, E. Yu.; Esirkepov, T. Zh.; Inovenkov, I. N.; Kando, M.; Pegoraro, F.; Korn, G.

2009-01-01

The energy of the ions accelerated by an intense electromagnetic wave in the radiation pressure dominated regime can be greatly enhanced due to a transverse expansion of a thin target. The expansion decreases the number of accelerated ions in the irradiated region increasing the energy and the longitudinal velocity of remaining ions. In the relativistic limit, the ions become phase-locked with respect to the electromagnetic wave resulting in the unlimited ion energy gain. This effect and the ...

26 CFR 1.642(c)-1 - Unlimited deduction for amounts paid for a charitable purpose.

Science.gov (United States)

2010-04-01

... the election was made, (iii) The office of the district director, or the service center, where the....642(c)-1 Unlimited deduction for amounts paid for a charitable purpose. (a) In general. (1) Any part... election, to a related estate, as defined under § 1.645-1(b), for the amount so paid. (2) In determining...

Fermions tunneling from apparent horizon of FRW universe

International Nuclear Information System (INIS)

Li Ran; Ren Jirong; Shi Dunfu

2009-01-01

In the paper [R.-G. Cai, L.-M. Cao, Y.-P. Hu, (arXiv: 0809.1554)], the scalar particles' Hawking radiation from the apparent horizon of Friedmann-Robertson-Walker (FRW) universe was investigated by using the tunneling formalism. They obtained the Hawking temperature associated with the apparent horizon, which was extensively applied in investigating the relationship between the first law of thermodynamics and Friedmann equations. In this Letter, we calculate fermions' Hawking radiation from the apparent horizon of FRW universe via tunneling formalism. Applying WKB approximation to the general covariant Dirac equation in FRW spacetime background, the radiation spectrum and Hawking temperature of apparent horizon are correctly recovered, which supports the arguments presented in the paper [R.-G. Cai, L.-M. Cao, Y.-P. Hu, (arXiv: 0809.1554)

Falling through the black hole horizon

International Nuclear Information System (INIS)

Brustein, Ram; Medved, A.J.M.

2015-01-01

We consider the fate of a small classical object, a “stick”, as it falls through the horizon of a large black hole (BH). Classically, the equivalence principle dictates that the stick is affected by small tidal forces, and Hawking’s quantum-mechanical model of BH evaporation makes essentially the same prediction. If, on the other hand, the BH horizon is surrounded by a “firewall”, the stick will be consumed as it falls through. We have recently extended Hawking’s model by taking into account the quantum fluctuations of the geometry and the classical back-reaction of the emitted particles. Here, we calculate the strain exerted on the falling stick for our model. The strain depends on the near-horizon state of the Hawking pairs. We find that, after the Page time when the state of the pairs deviates significantly from maximal entanglement (as required by unitarity), the induced strain in our semiclassical model is still parametrically small. This is because the number of the disentangled pairs is parametrically smaller than the BH entropy. A firewall does, however, appear if the number of disentangled pairs near the horizon is of order of the BH entropy, as implicitly assumed in previous discussions in the literature.

Assimilation of Wave Imaging Radar Observations for Real-Time Wave-by-Wave Forecasting

Science.gov (United States)

Haller, M. C.; Simpson, A. J.; Walker, D. T.; Lynett, P. J.; Pittman, R.; Honegger, D.

2016-02-01

It has been shown in various studies that a controls system can dramatically improve Wave Energy Converter (WEC) power production by tuning the device's oscillations to the incoming wave field, as well as protect WEC devices by decoupling them in extreme wave conditions. A requirement of the most efficient controls systems is a phase-resolved, "deterministic" surface elevation profile, alerting the device to what it will experience in the near future. The current study aims to demonstrate a deterministic method of wave forecasting through the pairing of an X-Band marine radar with a predictive Mild Slope Equation (MSE) wave model. Using the radar as a remote sensing technique, the wave field up to 1-4 km surrounding a WEC device can be resolved. Individual waves within the radar scan are imaged through the contrast between high intensity wave faces and low intensity wave troughs. Using a recently developed method, radar images are inverted into the radial component of surface slope, shown in the figure provided using radar data from Newport, Oregon. Then, resolved radial slope images are assimilated into the MSE wave model. This leads to a best-fit model hindcast of the waves within the domain. The hindcast is utilized as an initial condition for wave-by-wave forecasting with a target forecast horizon of 3-5 minutes (tens of wave periods). The methodology is currently being tested with synthetic data and comparisons with field data are imminent.

Locating the Gribov horizon

Energy Technology Data Exchange (ETDEWEB)

Gao, Fei; Qin, Si-Xue; Roberts, Craig D.; Rodríguez-Quintero, Jose

2018-02-01

We explore whether a tree-level expression for the gluon two-point function, supposed to express effects of an horizon term introduced to eliminate the Gribov ambiguity, is consistent with the propagator obtained in simulations of lattice-regularised quantum chromodynamics (QCD). In doing so, we insist that the gluon two-point function obey constraints that ensure a minimal level of consistency with parton-like behaviour at ultraviolet momenta. In consequence, we are led to a position which supports a conjecture that the gluon mass and horizon scale are equivalent emergent massscales, each with a value of roughly 0.5 GeV; and wherefrom it appears plausible that the dynamical generation of a running gluon mass may alone be sufficient to remove the Gribov ambiguity.

Locating the Gribov horizon

Science.gov (United States)

Gao, Fei; Qin, Si-Xue; Roberts, Craig D.; Rodríguez-Quintero, Jose

2018-02-01

We explore whether a tree-level expression for the gluon two-point function, supposed to express effects of an horizon term introduced to eliminate the Gribov ambiguity, is consistent with the propagator obtained in simulations of lattice-regularized quantum chromodynamics (QCD). In doing so, we insist that the gluon two-point function obey constraints that ensure a minimal level of consistency with parton-like behavior on the ultraviolet domain. In consequence, we are led to a position which supports a conjecture that the gluon mass and horizon scale are equivalent emergent mass-scales, each with a value of roughly 0.5 GeV; and wherefrom it appears plausible that the dynamical generation of a running gluon mass may alone be sufficient to remove the Gribov ambiguity.

Deepwater Horizon Seafood Safety Response - Deepwater Horizon Oil Spill Seafood Safety Response

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — In the aftermath of the Deepwater Horizon oil spill in 2010, there was concern about the risk to human health through consumption of contaminated seafood from the...

Membrane viewpoint on black holes: Dynamical electromagnetic fields near the horizon

International Nuclear Information System (INIS)

Macdonald, D.A.; Suen, W.

1985-01-01

This paper is part of a series of papers with the aim of developing a complete self-consistent formalism for the treatment of electromagnetic and gravitational fields in the neighborhood of a black-hole horizon. In this membrane formalism, the horizon is treated as a closed two-dimensional membrane lying in a curved three-dimensional space, and endowed with familiar physical properties such as entropy and temperature, surface pressure and viscosity, and electrical conductivity, charge, and current. This paper develops the concept of the ''stretched horizon,'' which will be vital for both the electromagnetic and gravitational aspects of the formalism, and it presents several model problems illustrating the interaction of dynamical electromagnetic fields with stationary black-hole horizons: The field of a test charge in various states of motion outside the Schwarzschild horizon is analyzed in the near-horizon limit, where the spatial curvature may be ignored and the metric may be approximated by that of Rindler. This analysis elucidates the influence of the horizon on the shapes and motions of electric and magnetic field lines when external agents move the field lines in arbitrary manners. It also illustrates how the field lines interact with the horizon's charge and current to produce an exchange of energy and momentum between the external agent and the horizon. A numerical calculation of the dynamical relaxation of a magnetic field threading a Schwarzschild black hole is also presented, illustrating the ''cleaning'' of a complicated field structure by a black-hole horizon, and elucidating the constraints on the location of the stretched horizon

Hawking radiation from the cosmological horizon in a FRW universe

International Nuclear Information System (INIS)

Hu Yapeng

2011-01-01

It is well known that there is a Hawking radiation from the cosmological horizon of the de Sitter spacetime, and the de Sitter spacetime can be a special case of a FRW universe. Therefore, there may be a corresponding Hawking radiation in a FRW universe. Indeed, there have been several clues showing that there is a Hawking radiation from the apparent horizon of a FRW universe. In our Letter, however, we find that the Hawking radiation may come from the cosmological horizon. Moreover, we also find that the Hawking radiation from the apparent horizon of a FRW universe in some previous works can be a special case in our result, and the condition is that the variation rate of cosmological horizon r . H is zero. Note that, this condition is also consistent with the underlying integrable condition in these works from the apparent horizon.

The pedogeochemical segregation a few horizons in soils from glass houses

Science.gov (United States)

Bulgariu, Dumitru; Rusu, Constantin; Filipov, Feodor; Buzgar, Nicolae; Bulgariu, Laura

2010-05-01

Our studies have focused the apparition and manifestation conditions of pedogeochemical segregation phenomena in case of soils from Copou - Iaşi, Bacău and Bârlad (Romania) glass house, and the effects of this on the pedogeochemical and agrochemical characteristics of soils from glass houses cultivated with vegetables. The utilization of intensive cultivation technologies of vegetables in glass houses determined the degradation of morphological, physical and chemical characteristics of soils, by rapid evolution of salted processes (salinization and / or sodization), compaction, carbonatation, eluviation-illuviation, frangipane formation, stagnogleization, gleization etc. Under these conditions, at depth of 30-40 cm is formed a compact and impenetrable horizon - Ahok(x) horizon. In function of exploitation conditions and by the chemical-mineralogical characteristics of soils from glasshouses, the Ahok horizons can have frangipane properties, expressed more or less. These horizons determined a geochemical segregation of soils from glass houses: (i) superior horizons, above Ahok(x) horizon evolve in weak oxidative conditions, weak alkaline pH, higher salinity, humidity and temperature; (ii) inferior horizons, below Ahok(x) horizon evolve in weak reducing conditions weak acid pH, lower salinity, humidity and temperature. Concomitant with the development of Ahok(x) horizons, the rapid degradation of the properties of soils from glasshouses is observed. The aspects about the formation of frangipane horizon in soils from glasshouses are not yet sufficiently know. Whatever of the formation processes, the frangipane horizons determined a sever segregation in pedogeochemical evolution of soils from glass houses, with very important consequences on the agrochemical quality of these soils. The segregation effects are manifested in the differential dynamics of pedogeochemical processes from superior horizons (situated above the segregation horizon), in comparison with the

Subjective Life Horizon and Portfolio Choice

OpenAIRE

Spaenjers , Christophe; Spira, Sven Michael

2013-01-01

Using data from a U.S. household survey, we examine the empirical relation between subjective life horizon (i.e., the self-reported expectation of remaining life span) and portfolio choice. We find that equity portfolio shares are higher for investors with longer horizons, ceteris paribus, in line with theoretical predictions. This result is robust to controlling for optimism and health status, accounting for the endogeneity of equity market participation, or instrumenting subjective life hor...

Null infinity and extremal horizons in AdS-CFT

International Nuclear Information System (INIS)

Hickling, Andrew; Wiseman, Toby; Lucietti, James

2015-01-01

We consider AdS gravity duals to CFT on background spacetimes with a null infinity. Null infinity on the conformal boundary may extend to an extremal horizon in the bulk. For example it does so for Poincaré–AdS, although does not for planar Schwarzschild–AdS. If null infinity does extend into an extremal horizon in the bulk, we show that the bulk near-horizon geometry is determined by the geometry of the boundary null infinity. Hence the ‘infra-red’ geometry of the bulk is fixed by the large scale behaviour of the CFT spacetime. In addition the boundary stress tensor must have a particular decay at null infinity. As an application, we argue that for CFT on asymptotically flat backgrounds, any static bulk dual containing an extremal horizon extending from the boundary null infinity, must have the near-horizon geometry of Poincaré–AdS. We also discuss a class of boundary null infinity that cannot extend to a bulk extremal horizon, although we give evidence that they can extend to an analogous null surface in the bulk which possesses an associated scale-invariant ‘near-geometry’. (paper)

On the membrane paradigm and spontaneous breaking of horizon BMS symmetries

International Nuclear Information System (INIS)

Eling, Christopher; Oz, Yaron

2016-01-01

We consider a BMS-type symmetry action on isolated horizons in asymptotically flat spacetimes. From the viewpoint of the non-relativistic field theory on a horizon membrane, supertranslations shift the field theory spatial momentum. The latter is related by a Ward identity to the particle number symmetry current and is spontaneously broken. The corresponding Goldstone boson shifts the horizon angular momentum and can be detected quantum mechanically. Similarly, area preserving superrotations are spontaneously broken on the horizon membrane and we identify the corresponding gapless modes. In asymptotically AdS spacetimes we study the BMS-type symmetry action on the horizon in a holographic superfluid dual. We identify the horizon supertranslation Goldstone boson as the holographic superfluid Goldstone mode.

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

Energy Technology Data Exchange (ETDEWEB)

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-01-01

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

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...

CFT/gravity correspondence on the isolated horizon

Energy Technology Data Exchange (ETDEWEB)

Ghosh, Amit, E-mail: amit.ghosh@saha.ac.in [Saha Institute of Nuclear Physics, 1/AF Bidhan Nagar, 700064 Kolkata (India); Pranzetti, Daniele, E-mail: daniele.pranzetti@gravity.fau.de [Institute for Quantum Gravity, University of Erlangen-Nürnberg (FAU), Staudtstrasse 7/B2, 91058 Erlangen (Germany)

2014-12-15

A quantum isolated horizon can be modelled by an SU(2) Chern–Simons theory on a punctured 2-sphere. We show how a local 2-dimensional conformal symmetry arises at each puncture inducing an infinite set of new observables localised at the horizon which satisfy a Kac–Moody algebra. By means of the isolated horizon boundary conditions, we represent the gravitational flux degrees of freedom in terms of the zero modes of the Kac–Moody algebra defined on the boundary of a punctured disk. In this way, our construction encodes a precise notion of CFT/gravity correspondence. The higher modes in the algebra represent new nongeometric charges which can be represented in terms of free matter field degrees of freedom. When computing the CFT partition function of the system, these new states induce an extra degeneracy factor, representing the density of horizon states at a given energy level, which reproduces the Bekenstein's holographic bound for an imaginary Immirzi parameter. This allows us to recover the Bekenstein–Hawking entropy formula without the large quantum gravity corrections associated with the number of punctures.

Wider horizons, wiser choices: horizon scanning for public health protection and improvement.

Science.gov (United States)

Urquhart, Graham J; Saunders, Patrick

2017-06-01

Systematic continuous thinking about the future helps organizations, professions and communities to both prepare for, and shape, the future. This becomes ever more critical given the accelerating rate at which new data emerge, and in some cases uncertainties around their reliability and interpretation. Businesses with the capability to filter and analyse vast volumes of data to create knowledge and insights requiring action have a competitive advantage. Similarly Government and the public sector, including public health can be more effective and efficient through the early identification of emerging issues (both threats and opportunities). Horizon scanning approaches, and the use of resulting intelligence related to health protection and improvement were reviewed. Public health horizon scanning systems have to date focussed on health technologies and infectious diseases. While these have been successful there is a major gap in terms of non-infectious hazards and health improvement. Any system to meet this need must recognize the changed environment for delivering front line public health services and the critical role of local authorities and the local democratic process. This presents opportunities and challenges and this paper explores those dynamics describing an existing environment and health horizon scanning system which could readily and rapidly be re-engineered to provide a national service. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Universality of P−V criticality in horizon thermodynamics

Energy Technology Data Exchange (ETDEWEB)

Hansen, Devin; Kubizňák, David [Perimeter Institute,31 Caroline St. N., Waterloo, Ontario, N2L 2Y5 (Canada); Department of Physics and Astronomy, University of Waterloo,Waterloo, Ontario, N2L 3G1 (Canada); Mann, Robert B. [Department of Physics and Astronomy, University of Waterloo,Waterloo, Ontario, N2L 3G1 (Canada)

2017-01-11

We study P−V criticality of black holes in Lovelock gravities in the context of horizon thermodynamics. The corresponding first law of horizon thermodynamics emerges as one of the Einstein-Lovelock equations and assumes the universal (independent of matter content) form δE=TδS−PδV, where P is identified with the total pressure of all matter in the spacetime (including a cosmological constant Λ if present). We compare this approach to recent advances in extended phase space thermodynamics of asymptotically AdS black holes where the ‘standard’ first law of black hole thermodynamics is extended to include a pressure-volume term, where the pressure is entirely due to the (variable) cosmological constant. We show that both approaches are quite different in interpretation. Provided there is sufficient non-linearity in the gravitational sector, we find that horizon thermodynamics admits the same interesting black hole phase behaviour seen in the extended case, such as a Hawking-Page transition, Van der Waals like behaviour, and the presence of a triple point. We also formulate the Smarr formula in horizon thermodynamics and discuss the interpretation of the quantity E appearing in the horizon first law.

Universality of P−V criticality in horizon thermodynamics

International Nuclear Information System (INIS)

Hansen, Devin; Kubizňák, David; Mann, Robert B.

2017-01-01

We study P−V criticality of black holes in Lovelock gravities in the context of horizon thermodynamics. The corresponding first law of horizon thermodynamics emerges as one of the Einstein-Lovelock equations and assumes the universal (independent of matter content) form δE=TδS−PδV, where P is identified with the total pressure of all matter in the spacetime (including a cosmological constant Λ if present). We compare this approach to recent advances in extended phase space thermodynamics of asymptotically AdS black holes where the ‘standard’ first law of black hole thermodynamics is extended to include a pressure-volume term, where the pressure is entirely due to the (variable) cosmological constant. We show that both approaches are quite different in interpretation. Provided there is sufficient non-linearity in the gravitational sector, we find that horizon thermodynamics admits the same interesting black hole phase behaviour seen in the extended case, such as a Hawking-Page transition, Van der Waals like behaviour, and the presence of a triple point. We also formulate the Smarr formula in horizon thermodynamics and discuss the interpretation of the quantity E appearing in the horizon first law.

Receding Horizon H∞ Control for Input-Delayed Systems

Directory of Open Access Journals (Sweden)

Han Woong Yoo

2012-01-01

Full Text Available We propose the receding horizon H∞ control (RHHC for input-delayed systems. A new cost function for a finite horizon dynamic game problem is first introduced, which includes two terminal weighting terms parameterized by a positive definite matrix, called a terminal weighing matrix. Secondly, the RHHC is obtained from the solution to the finite dynamic game problem. Thirdly, we propose an LMI condition under which the saddle point value satisfies the nonincreasing monotonicity. Finally, we show the asymptotic stability and H∞ boundedness of the closed-loop system controlled by the proposed RHHC. The proposed RHHC has a guaranteed H∞ performance bound for nonzero external disturbances and the quadratic cost can be improved by adjusting the prediction horizon length for nonzero initial condition and zero disturbance, which is not the case for existing memoryless state-feedback controllers. It is shown through a numerical example that the proposed RHHC is stabilizing and satisfies the infinite horizon H∞ performance bound. Furthermore, the performance in terms of the quadratic cost is shown to be improved by adjusting the prediction horizon length when there exists no external disturbance with nonzero initial condition.

A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Chengshi Tian

2018-03-01

Full Text Available Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids.

Horizon thermodynamics in fourth-order gravity

Directory of Open Access Journals (Sweden)

Meng-Sen Ma

2017-03-01

Full Text Available In the framework of horizon thermodynamics, the field equations of Einstein gravity and some other second-order gravities can be rewritten as the thermodynamic identity: dE=TdS−PdV. However, in order to construct the horizon thermodynamics in higher-order gravity, we have to simplify the field equations firstly. In this paper, we study the fourth-order gravity and convert it to second-order gravity via a so-called “Legendre transformation” at the cost of introducing two other fields besides the metric field. With this simplified theory, we implement the conventional procedure in the construction of the horizon thermodynamics in 3 and 4 dimensional spacetime. We find that the field equations in the fourth-order gravity can also be written as the thermodynamic identity. Moreover, we can use this approach to derive the same black hole mass as that by other methods.

Thermal and nonthermal particle production without event horizons

International Nuclear Information System (INIS)

Sanchez, N.

1979-01-01

Usually, particle production in accelerated frames is discussed in connection with the presence of event horizons and with a planckian spectrum. Accelerated frames without event horizons, where particle production takes place with thermal as well as nonthermal distributions, are constructed. (Auth.)

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

Science.gov (United States)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Medium Range Forecasts Representation (and Long Range Forecasts?)

Science.gov (United States)

Vincendon, J.-C.

2009-09-01

The progress of the numerical forecasts urges us to interest us in more and more distant ranges. We thus supply more and more forecasts with term of some days. Nevertheless, precautions of use are necessary to give the most reliable and the most relevant possible information. Available in a TV bulletin or on quite other support (Internet, mobile phone), the interpretation and the representation of a medium range forecast (5 - 15 days) must be different from those of a short range forecast. Indeed, the "foresee-ability” of a meteorological phenomenon decreases gradually in the course of the ranges, it decreases all the more quickly that the phenomenon is of small scale. So, at the end of some days, the probability character of a forecast becomes very widely dominating. That is why in Meteo-France the forecasts of D+4 to D+7 are accompanied with a confidence index since around ten years. It is a figure between 1 and 5: the more we approach 5, the more the confidence in the supplied forecast is good. In the practice, an indication is supplied for period D+4 / D+5, the other one for period D+6 / D+7, every day being able to benefit from a different forecast, that is be represented in a independent way. We thus supply a global tendency over 24 hours with less and less precise symbols as the range goes away. Concrete examples will be presented. From now on two years, we also publish forecasts to D+8 / J+9, accompanied with a sign of confidence (" good reliability " or " to confirm "). These two days are grouped together on a single map because for us, the described tendency to this term is relevant on a duration about 48 hours with a spatial scale slightly superior to the synoptic scale. So, we avoid producing more than two zones of types of weather over France and we content with giving an evolution for the temperatures (still, in increase or in decline). Newspapers began to publish this information, it should soon be the case of televisions. It is particularly

Hawking spectrum for a fiber-optical analog of the event horizon

Science.gov (United States)

Bermudez, David; Leonhardt, Ulf

2016-05-01

Hawking radiation has been regarded as a more general phenomenon than in gravitational physics, in particular in laboratory analogs of the event horizon. Here we consider the fiber-optical analog of the event horizon, where intense light pulses in fibers establish horizons for probe light. Then, we calculate the Hawking spectrum in an experimentally realizable system. We found that the Hawking radiation is peaked around group-velocity horizons in which the speed of the pulse matches the group velocity of the probe light. The radiation nearly vanishes at the phase horizon where the speed of the pulse matches the phase velocity of light.

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...

Deepwater Horizon - Baseline Dataset

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — In 2010, the Deepwater Horizon oil spill occurred in the Gulf of Mexico and the Natural Resources Damage Assessment (NRDA) was initiated to determine the extent of...

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,

Incorporating wind generation forecast uncertainty into power system operation, dispatch, and unit commitment procedures

Energy Technology Data Exchange (ETDEWEB)

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jiam; Subbarao, Krishnappa [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

2010-07-01

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the ''flying-brick'' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors. (orig.)

The two event horizons - an apparent contribution of vacuum to gravitation

International Nuclear Information System (INIS)

Dinculescu, A.

1994-01-01

Our possibilities of investigation are limited by two horizons: a local one - the black hole horizon R 0 , and the global one - the cosmic horizon R u . Till now, only the first horizon has been taken into consideration as a measure of the curvature of space near a massive body. It is argued that in order to satisfy Mach's principle when characterizing matter in a point relative to a center of mass, one has to take into consideration both event horizons. Accordingly, a local cosmological term Λ * =(R 0 R u ) -1 is defined as a combination of the above horizons in a given point. The corresponding non-dimensional coefficient ξ=Λ * R 2 is an indicator of the position of a mass point between the two event horizons. When taking into account as a contribution of vacuum energy to the gravitational field it restores the low of conservation of energy in an expanding universe, and explains the dynamics of galaxies and clusters of galaxies without resorting to the 'dark matter' hypothesis. (Author) 3 Tabs., 38 Refs

Proposed cuts to Horizon 2020 are short-sighted

CERN Multimedia

2015-01-01

When the latest incarnation of Europe’s framework programme for science funding, Horizon 2020, was announced, it was to great acclaim. Horizon 2020 builds on the already considerable success of its forerunners, which have made international research at the European level a reality and have contributed greatly to European competitiveness on the world stage.   We at CERN have benefited considerably, through projects that have enabled us to build on CERN’s core competencies to develop science at the grass-roots level across the continent. Horizon 2020 is more ambitious and more streamlined than its predecessors, and, funded at the level of €70 billion over seven years, it is potentially transformative. All of which makes the Commission’s plan to raid the Horizon 2020 budget to the tune of €2.7 billion rather incomprehensible. Keen to stimulate Europe’s economies, Commission President Jean-Claude Juncker has proposed a €21 billio...

VMware Horizon View 6 desktop virtualization cookbook

CERN Document Server

Ventresco, Jason

2014-01-01

If you want a more detailed explanation concerning the implementation of several different core features of VMware Horizon View, this is the book for you. Whether you are new to VMware Horizon View or an existing user, this book will provide you with the knowledge you need to successfully deploy several core features and get introduced to the latest features of version 6.0 as well.

Planning horizon affects prophylactic decision-making and epidemic dynamics.

Science.gov (United States)

Nardin, Luis G; Miller, Craig R; Ridenhour, Benjamin J; Krone, Stephen M; Joyce, Paul; Baumgaertner, Bert O

2016-01-01

The spread of infectious diseases can be impacted by human behavior, and behavioral decisions often depend implicitly on a planning horizon-the time in the future over which options are weighed. We investigate the effects of planning horizons on epidemic dynamics. We developed an epidemiological agent-based model (along with an ODE analog) to explore the decision-making of self-interested individuals on adopting prophylactic behavior. The decision-making process incorporates prophylaxis efficacy and disease prevalence with the individuals' payoffs and planning horizon. Our results show that for short and long planning horizons individuals do not consider engaging in prophylactic behavior. In contrast, individuals adopt prophylactic behavior when considering intermediate planning horizons. Such adoption, however, is not always monotonically associated with the prevalence of the disease, depending on the perceived protection efficacy and the disease parameters. Adoption of prophylactic behavior reduces the epidemic peak size while prolonging the epidemic and potentially generates secondary waves of infection. These effects can be made stronger by increasing the behavioral decision frequency or distorting an individual's perceived risk of infection.

Entropy bound of horizons for accelerating, rotating and charged Plebanski–Demianski black hole

International Nuclear Information System (INIS)

Debnath, Ujjal

2016-01-01

We first review the accelerating, rotating and charged Plebanski–Demianski (PD) black hole, which includes the Kerr–Newman rotating black hole and the Taub-NUT spacetime. The main feature of this black hole is that it has 4 horizons like event horizon, Cauchy horizon and two accelerating horizons. In the non-extremal case, the surface area, entropy, surface gravity, temperature, angular velocity, Komar energy and irreducible mass on the event horizon and Cauchy horizon are presented for PD black hole. The entropy product, temperature product, Komar energy product and irreducible mass product have been found for event horizon and Cauchy horizon. Also their sums are found for both horizons. All these relations are dependent on the mass of the PD black hole and other parameters. So all the products are not universal for PD black hole. The entropy and area bounds for two horizons have been investigated. Also we found the Christodoulou–Ruffini mass for extremal PD black hole. Finally, using first law of thermodynamics, we also found the Smarr relation for PD black hole.

Entropy bound of horizons for accelerating, rotating and charged Plebanski–Demianski black hole

Energy Technology Data Exchange (ETDEWEB)

Debnath, Ujjal, E-mail: ujjaldebnath@yahoo.com

2016-09-15

We first review the accelerating, rotating and charged Plebanski–Demianski (PD) black hole, which includes the Kerr–Newman rotating black hole and the Taub-NUT spacetime. The main feature of this black hole is that it has 4 horizons like event horizon, Cauchy horizon and two accelerating horizons. In the non-extremal case, the surface area, entropy, surface gravity, temperature, angular velocity, Komar energy and irreducible mass on the event horizon and Cauchy horizon are presented for PD black hole. The entropy product, temperature product, Komar energy product and irreducible mass product have been found for event horizon and Cauchy horizon. Also their sums are found for both horizons. All these relations are dependent on the mass of the PD black hole and other parameters. So all the products are not universal for PD black hole. The entropy and area bounds for two horizons have been investigated. Also we found the Christodoulou–Ruffini mass for extremal PD black hole. Finally, using first law of thermodynamics, we also found the Smarr relation for PD black hole.

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

Relating Tropical Cyclone Track Forecast Error Distributions with Measurements of Forecast Uncertainty

Science.gov (United States)

2016-03-01

CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS WITH MEASUREMENTS OF FORECAST UNCERTAINTY by Nicholas M. Chisler March 2016 Thesis Advisor...March 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE RELATING TROPICAL CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS...WITH MEASUREMENTS OF FORECAST UNCERTAINTY 5. FUNDING NUMBERS 6. AUTHOR(S) Nicholas M. Chisler 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES

En Garde: Fencing at Kansas City's Central Computers Unlimited/Classical Greek Magnet High School, 1991-1995

Science.gov (United States)

Poos, Bradley W.

2015-01-01

Central High School in Kansas City, Missouri is one of the oldest schools west of the Mississippi and the first public high school built in Kansas City. Kansas City's magnet plan resulted in Central High School being rebuilt as the Central Computers Unlimited/Classical Greek Magnet High School, a school that was designed to offer students an…

Conference Offers Girls Opportunity to Expand Career Horizons

Science.gov (United States)

Offers Girls Opportunity to Expand Career Horizons For more information contact: e:mail: Public Affairs Golden, Colo., Feb. 11, 1997 -- Expanding Your Horizons, a conference for girls grades 6 - 9 and Employed Women, Girls Incorporated of Metro Denver, King Soopers, McDonalds, the TCI Adult Program and the

Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

Directory of Open Access Journals (Sweden)

Jui-Yi Ho

2015-04-01

Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

Event and Apparent Horizon Finders for 3 + 1 Numerical Relativity.

Science.gov (United States)

Thornburg, Jonathan

2007-01-01

Event and apparent horizons are key diagnostics for the presence and properties of black holes. In this article I review numerical algorithms and codes for finding event and apparent horizons in numerically-computed spacetimes, focusing on calculations done using the 3 + 1 ADM formalism. The event horizon of an asymptotically-flat spacetime is the boundary between those events from which a future-pointing null geodesic can reach future null infinity and those events from which no such geodesic exists. The event horizon is a (continuous) null surface in spacetime. The event horizon is defined nonlocally in time : it is a global property of the entire spacetime and must be found in a separate post-processing phase after all (or at least the nonstationary part) of spacetime has been numerically computed. There are three basic algorithms for finding event horizons, based on integrating null geodesics forwards in time, integrating null geodesics backwards in time, and integrating null surfaces backwards in time. The last of these is generally the most efficient and accurate. In contrast to an event horizon, an apparent horizon is defined locally in time in a spacelike slice and depends only on data in that slice, so it can be (and usually is) found during the numerical computation of a spacetime. A marginally outer trapped surface (MOTS) in a slice is a smooth closed 2-surface whose future-pointing outgoing null geodesics have zero expansion Θ. An apparent horizon is then defined as a MOTS not contained in any other MOTS. The MOTS condition is a nonlinear elliptic partial differential equation (PDE) for the surface shape, containing the ADM 3-metric, its spatial derivatives, and the extrinsic curvature as coefficients. Most "apparent horizon" finders actually find MOTSs. There are a large number of apparent horizon finding algorithms, with differing trade-offs between speed, robustness, accuracy, and ease of programming. In axisymmetry, shooting algorithms work well

Gravitational pressure, apparent horizon and thermodynamics of FLRW universe in the teleparallel gravity

Science.gov (United States)

da Rocha-Neto, J. F.; Morais, B. R.

2018-04-01

In the context of the teleparallel equivalent of general relativity the concept of gravitational pressure and gravitational energy-momentum arisen in a natural way. In the case of a Friedmann-Lemaitre-Robertson-Walker space FLRW we obtain the total energy contained inside the apparent horizon and the radial pressure over the apparent horizon area. We use these definitions to written a thermodynamics relation TAdSA = dEA+PAdVA at the apparent horizon, where EA is the total energy inside the apparent horizon, VA is the areal volume of the apparent horizon, PA is the radial pressure over the apparent horizon area, SA is the entropy which can be assumed as one quarter of the apparent horizon area only for a non stationary apparent horizon. We identify TA as the temperature at the surface of the apparent horizon. We shown that for all expanding accelerated FLRW model of universe the radial pressure is positive.

Geometric properties of static Einstein-Maxwell dilaton horizons with a Liouville potential

International Nuclear Information System (INIS)

Abdolrahimi, Shohreh; Shoom, Andrey A.

2011-01-01

We study nondegenerate and degenerate (extremal) Killing horizons of arbitrary geometry and topology within the Einstein-Maxwell-dilaton model with a Liouville potential (the EMdL model) in d-dimensional (d≥4) static space-times. Using Israel's description of a static space-time, we construct the EMdL equations and the space-time curvature invariants: the Ricci scalar, the square of the Ricci tensor, and the Kretschmann scalar. Assuming that space-time metric functions and the model fields are real analytic functions in the vicinity of a space-time horizon, we study the behavior of the space-time metric and the fields near the horizon and derive relations between the space-time curvature invariants calculated on the horizon and geometric invariants of the horizon surface. The derived relations generalize similar relations known for horizons of static four- and five-dimensional vacuum and four-dimensional electrovacuum space-times. Our analysis shows that all the extremal horizon surfaces are Einstein spaces. We present the necessary conditions for the existence of static extremal horizons within the EMdL model.

The Event Horizon of The Schwarzschild Black Hole in Noncommutative Spaces

OpenAIRE

Nasseri, Forough

2005-01-01

The event horizon of Schwarzschild black hole is obtained in noncommutative spaces up to the second order of perturbative calculations. Because this type of black hole is non-rotating, to the first order there is no any effect on the event horizon due to the noncommutativity of space. A lower limit for the noncommutativity parameter is also obtained. As a result, the event horizon in noncommutative spaces is less than the event horizon in commutative spaces.

On crossing the Cauchy horizon of a Reissner-Nordstroem black-hole

International Nuclear Information System (INIS)

Chandrasekhar, S.; Hartle, J.B.

1982-01-01

The behaviour, on the Cauchy horizon, of a flux of gravitational and/or electromagnetic radiation crossing the event horizon of a Reissner-Nordstroem black-hole is investigated as a problem in the theory of one-dimensional potential-scattering. It is shown that the flux of radiation received by an observer crossing the Cauchy horizon, along a radial time-like geodesic, diverges for all physically perturbations crossing the event horizon, even including those with compact support. (author)

Petascale Diagnostic Assessment of the Global Portfolio Rainfall Space Missions' Ability to Support Flood Forecasting

Science.gov (United States)

Reed, P. M.; Chaney, N.; Herman, J. D.; Wood, E. F.; Ferringer, M. P.

2015-12-01

This research represents a multi-institutional collaboration between Cornell University, The Aerospace Corporation, and Princeton University that has completed a Petascale diagnostic assessment of the current 10 satellite missions providing rainfall observations. Our diagnostic assessment has required four core tasks: (1) formally linking high-resolution astrodynamics design and coordination of space assets with their global hydrological impacts within a Petascale "many-objective" global optimization framework, (2) developing a baseline diagnostic evaluation of a 1-degree resolution global implementation of the Variable Infiltration Capacity (VIC) model to establish the required satellite observation frequencies and coverage to maintain acceptable global flood forecasts, (3) evaluating the limitations and vulnerabilities of the full suite of current satellite precipitation missions including the recently approved Global Precipitation Measurement (GPM) mission, and (4) conceptualizing the next generation spaced-based platforms for water cycle observation. Our team exploited over 100 Million hours of computing access on the 700,000+ core Blue Waters machine to radically advance our ability to discover and visualize key system tradeoffs and sensitivities. This project represents to our knowledge the first attempt to develop a 10,000 member Monte Carlo global hydrologic simulation at one degree resolution that characterizes the uncertain effects of changing the available frequencies of satellite precipitation on drought and flood forecasts. The simulation—optimization components of the work have set a theoretical baseline for the best possible frequencies and coverages for global precipitation given unlimited investment, broad international coordination in reconfiguring existing assets, and new satellite constellation design objectives informed directly by key global hydrologic forecasting requirements. Our research poses a step towards realizing the integrated

Short-term residential load forecasting: Impact of calendar effects and forecast granularity

DEFF Research Database (Denmark)

Lusis, Peter; Khalilpour, Kaveh Rajab; Andrew, Lachlan

2017-01-01

forecasting for a single-customer or even down at an appliance level. Access to high resolution data from smart meters has enabled the research community to assess conventional load forecasting techniques and develop new forecasting strategies suitable for demand-side disaggregated loads. This paper studies...... how calendar effects, forecasting granularity and the length of the training set affect the accuracy of a day-ahead load forecast for residential customers. Root mean square error (RMSE) and normalized RMSE were used as forecast error metrics. Regression trees, neural networks, and support vector...... regression yielded similar average RMSE results, but statistical analysis showed that regression trees technique is significantly better. The use of historical load profiles with daily and weekly seasonality, combined with weather data, leaves the explicit calendar effects a very low predictive power...

Euclidean scalar Green's functions near the black hole and black brane horizons

International Nuclear Information System (INIS)

Haba, Z

2009-01-01

We discuss approximations of the Riemannian geometry near the horizon. If a (D + 1)-dimensional manifold N has a bifurcate Killing horizon then we approximate N by a product of the two-dimensional Rindler space R 2 and a (D - 1)-dimensional Riemannian manifold M. We obtain approximate formulae for scalar Green's functions. We study the behavior of the Green's functions near the horizon and their dimensional reduction. We show that if M is compact then the Green's function near the horizon can be approximated by the Green's function of the two-dimensional quantum field theory. The correction term is exponentially small away from the horizon. We extend the results to black brane solutions of supergravity in 10 and 11 dimensions. The near-horizon geometry can be approximated by N=AdS p xS q . We discuss the Euclidean Green's functions on N and their behavior near the horizon.

26 CFR 1.642(c)-3 - Adjustments and other special rules for determining unlimited charitable contributions deduction.

Science.gov (United States)

2010-04-01

... the gross income of the estate for 1972, and N University receives $100,000 from the estate in such... INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES... unlimited charitable contributions deduction. (a) Income in respect of a decedent. For purposes of §§ 1.642...

Operational flood-forecasting in the Piemonte region – development and verification of a fully distributed physically-oriented hydrological model

Directory of Open Access Journals (Sweden)

D. Rabuffetti

2009-03-01

Full Text Available A hydrological model for real time flood forecasting to Civil Protection services requires reliability and rapidity. At present, computational capabilities overcome the rapidity needs even when a fully distributed hydrological model is adopted for a large river catchment as the Upper Po river basin closed at Ponte Becca (nearly 40 000 km². This approach allows simulating the whole domain and obtaining the responses of large as well as of medium and little sized sub-catchments. The FEST-WB hydrological model (Mancini, 1990; Montaldo et al., 2007; Rabuffetti et al., 2008 is implemented. The calibration and verification activities are based on more than 100 flood events, occurred along the main tributaries of the Po river in the period 2000–2003. More than 300 meteorological stations are used to obtain the forcing fields, 10 cross sections with continuous and reliable discharge time series are used for calibration while verification is performed on about 40 monitored cross sections. Furthermore meteorological forecasting models are used to force the hydrological model with Quantitative Precipitation Forecasts (QPFs for 36 h horizon in "operational setting" experiments. Particular care is devoted to understanding how QPF affects the accuracy of the Quantitative Discharge Forecasts (QDFs and to assessing the QDF uncertainty impact on the warning system reliability. Results are presented either in terms of QDF and of warning issues highlighting the importance of an "operational based" verification approach.

Measuring Item Fill-Rate Performance in a Finite Horizon

OpenAIRE

Douglas J. Thomas

2005-01-01

The standard treatment of fill rate relies on stationary and serially independent demand over an infinite horizon. Even if demand is stationary, managers are held accountable for performance over a finite horizon. In a finite horizon, the fill rate is a random variable. Studying the distribution is relevant because a vendor may be subject to financial penalty if she fails to achieve her target fill rate over a specified finite period. It is known that for a zero lead time, base-stock model, t...

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...

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.

Structure of diagnostics horizons and humus classification

Directory of Open Access Journals (Sweden)

Zanella A

2008-03-01

Full Text Available The classification of the main humus forms is generally based on the morpho-genetic characters of the A and OH diagnostic horizons. This is the case in the new European key of classification presented in Freiburg on September 2004 (Eurosoil Congress. Among the morpho-genetic characters, the soil structure covers a very important role. In this work, the structure of the diagnostic A and OH horizons has been analysed in terms of aggregation force, diameter and composition of the soil lumps (peds. In order to study the aggregation force, two disaggregating tools have been conceived and used. The diameter of the lumps has been measured by sieving the soil samples with standardised webs. Observing the samples thanks to a binocular magnifying 10X and 50X, the organic or/and mineral composition of the soil aggregates has been determined, data being investigated with ANOVA and Factorial Analysis. The article examines the argument from two points of view: crashing tools for estimating the soil structure (part 1 and the dimensions of the peds given in European key of humus forms classification (part 2. The categories of soil peds diameter and composition seem to be linked to the main humus forms. For instance, aggregates having a diamater larger than 1 mm and well amalgamate organo-mineral composition are more present in the A horizons of the Mull forms than in which of the other forms; contrary to the OH horizon of the Moder or Mor, the OH horizon of the Amphi forms shows an important percent of small organic lumps. Some propositions have been given in order to improve the European key of humus forms classification.

Horizon Scanning for Pharmaceuticals

DEFF Research Database (Denmark)

Lepage-Nefkens, Isabelle; Douw, Karla; Mantjes, GertJan

for a joint horizon scanning system (HSS).  We propose to create a central “horizon scanning unit” to perform the joint HS activities (a newly established unit, an existing HS unit, or a third party commissioned and financed by the collaborating countries). The unit will be responsible for the identification...... and filtration of new and emerging pharmaceutical products. It will maintain and update the HS database, organise company pipeline meetings, and disseminate the HSS’s outputs.  The HS unit works closely together with the designated national HS experts in each collaborating country. The national HS experts...... will collect country-specific information, liaise between the central HS unit and country-specific clinical and other experts, coordinate the national prioritization process (to select products for early assessment), and communicate the output of the HSS to national decision makers.  The outputs of the joint...

Near-horizon symmetries of extremal black holes

International Nuclear Information System (INIS)

Kunduri, Hari K; Lucietti, James; Reall, Harvey S

2007-01-01

Recent work has demonstrated an attractor mechanism for extremal rotating black holes subject to the assumption of a near-horizon SO(2, 1) symmetry. We prove the existence of this symmetry for any extremal black hole with the same number of rotational symmetries as known four- and five-dimensional solutions (including black rings). The result is valid for a general two-derivative theory of gravity coupled to Abelian vectors and uncharged scalars, allowing for a non-trivial scalar potential. We prove that it remains valid in the presence of higher-derivative corrections. We show that SO(2, 1)-symmetric near-horizon solutions can be analytically continued to give SU(2)-symmetric black hole solutions. For example, the near-horizon limit of an extremal 5D Myers-Perry black hole is related by analytic continuation to a non-extremal cohomogeneity-1 Myers-Perry solution

Infinite-horizon optimal control problems in economics

International Nuclear Information System (INIS)

Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V

2012-01-01

This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.

Does the black hole shadow probe the event horizon geometry?

Science.gov (United States)

Cunha, Pedro V. P.; Herdeiro, Carlos A. R.; Rodriguez, Maria J.

2018-04-01

There is an exciting prospect of obtaining the shadow of astrophysical black holes (BHs) in the near future with the Event Horizon Telescope. As a matter of principle, this justifies asking how much one can learn about the BH horizon itself from such a measurement. Since the shadow is determined by a set of special photon orbits, rather than horizon properties, it is possible that different horizon geometries yield similar shadows. One may then ask how sensitive is the shadow to details of the horizon geometry? As a case study, we consider the double Schwarzschild BH and analyze the impact on the lensing and shadows of the conical singularity that holds the two BHs in equilibrium—herein taken to be a strut along the symmetry axis in between the two BHs. Whereas the conical singularity induces a discontinuity of the scattering angle of photons, clearly visible in the lensing patterns along the direction of the strut's location, it produces no observable effect on the shadows, whose edges remain everywhere smooth. The latter feature is illustrated by examples including both equal and unequal mass BHs. This smoothness contrasts with the intrinsic geometry of the (spatial sections of the) horizon of these BHs, which is not smooth, and provides a sharp example on how BH shadows are insensitive to some horizon geometry details. This observation, moreover, suggests that for the study of their shadows, this static double BH system may be an informative proxy for a dynamical binary.

Using electronic health records and Internet search information for accurate influenza forecasting.

Science.gov (United States)

Yang, Shihao; Santillana, Mauricio; Brownstein, John S; Gray, Josh; Richardson, Stewart; Kou, S C

2017-05-08

Accurate influenza activity forecasting helps public health officials prepare and allocate resources for unusual influenza activity. Traditional flu surveillance systems, such as the Centers for Disease Control and Prevention's (CDC) influenza-like illnesses reports, lag behind real-time by one to 2 weeks, whereas information contained in cloud-based electronic health records (EHR) and in Internet users' search activity is typically available in near real-time. We present a method that combines the information from these two data sources with historical flu activity to produce national flu forecasts for the United States up to 4 weeks ahead of the publication of CDC's flu reports. We extend a method originally designed to track flu using Google searches, named ARGO, to combine information from EHR and Internet searches with historical flu activities. Our regularized multivariate regression model dynamically selects the most appropriate variables for flu prediction every week. The model is assessed for the flu seasons within the time period 2013-2016 using multiple metrics including root mean squared error (RMSE). Our method reduces the RMSE of the publicly available alternative (Healthmap flutrends) method by 33, 20, 17 and 21%, for the four time horizons: real-time, one, two, and 3 weeks ahead, respectively. Such accuracy improvements are statistically significant at the 5% level. Our real-time estimates correctly identified the peak timing and magnitude of the studied flu seasons. Our method significantly reduces the prediction error when compared to historical publicly available Internet-based prediction systems, demonstrating that: (1) the method to combine data sources is as important as data quality; (2) effectively extracting information from a cloud-based EHR and Internet search activity leads to accurate forecast of flu.

Fractal markets: Liquidity and investors on different time horizons

Science.gov (United States)

Li, Da-Ye; Nishimura, Yusaku; Men, Ming

2014-08-01

In this paper, we propose a new agent-based model to study the source of liquidity and the “emergent” phenomenon in financial market with fractal structure. The model rests on fractal market hypothesis and agents with different time horizons of investments. What is interesting is that though the agent-based model reveals that the interaction between these heterogeneous agents affects the stability and liquidity of the financial market the real world market lacks detailed data to bring it to light since it is difficult to identify and distinguish the investors with different time horizons in the empirical approach. results show that in a relatively short period of time fractal market provides liquidity from investors with different horizons and the market gains stability when the market structure changes from uniformity to diversification. In the real world the fractal structure with the finite of horizons can only stabilize the market within limits. With the finite maximum horizons, the greater diversity of the investors and the fractal structure will not necessarily bring more stability to the market which might come with greater fluctuation in large time scale.

Air Pollution Forecasts: An Overview.

Science.gov (United States)

Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

2018-04-17

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Air Pollution Forecasts: An Overview

Directory of Open Access Journals (Sweden)

Lu Bai

2018-04-01

Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Air Pollution Forecasts: An Overview

Science.gov (United States)

Bai, Lu; Wang, Jianzhou; Lu, Haiyan

2018-01-01

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

A redefinition of Hawking temperature on the event horizon: Thermodynamical equilibrium

International Nuclear Information System (INIS)

Saha, Subhajit; Chakraborty, Subenoy

2012-01-01

In this Letter we have used the recently introduced redefined Hawking temperature on the event horizon and investigated whether the generalized second law of thermodynamics (GSLT) and thermodynamic equilibrium holds for both the event and the apparent horizons. Here we have considered FRW universe and examined the GSLT and thermodynamic equilibrium with three examples. Finally, we have concluded that from the thermodynamic viewpoint, the universe bounded by the event horizon is more realistic than that by the apparent horizon at least for some examples.

On the topology of stationary black hole event horizons in higher dimensions

International Nuclear Information System (INIS)

Helfgott, Craig; Oz, Yaron; Yanay, Yariv

2006-01-01

In four dimensions the topology of the event horizon of an asymptotically flat stationary black hole is uniquely determined to be the two-sphere S 2 . We consider the topology of event horizons in higher dimensions. First, we reconsider Hawking's theorem and show that the integrated Ricci scalar curvature with respect to the induced metric on the event horizon is positive also in higher dimensions. Using this and Thurston's geometric types classification of three-manifolds, we find that the only possible geometric types of event horizons in five dimensions are S 3 and S 2 x S 1 . In six dimensions we use the requirement that the horizon is cobordant to a four-sphere (topological censorship), Friedman's classification of topological four-manifolds and Donaldson's results on smooth four-manifolds, and show that simply connected event horizons are homeomorphic to S 4 or S 2 x S 2 . We show that the non-simply connected event horizons S 3 x S 1 and S 2 x Σ g and event horizons with finite non-abelian first homotopy group whose universal cover is S 4 , are possible. Finally, we discuss the classification in dimensions higher than six

Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system

International Nuclear Information System (INIS)

Fang, Tingting; Lahdelma, Risto

2016-01-01

Highlights: • Social factor is considered for the linear regression models besides weather file. • Simultaneously optimize all the coefficients for linear regression models. • SARIMA combined with linear regression is used to forecast the heat demand. • The accuracy for both linear regression and time series models are evaluated. - Abstract: Forecasting heat demand is necessary for production and operation planning of district heating (DH) systems. In this study we first propose a simple regression model where the hourly outdoor temperature and wind speed forecast the heat demand. Weekly rhythm of heat consumption as a social component is added to the model to significantly improve the accuracy. The other type of model is the seasonal autoregressive integrated moving average (SARIMA) model with exogenous variables as a combination to take weather factors, and the historical heat consumption data as depending variables. One outstanding advantage of the model is that it peruses the high accuracy for both long-term and short-term forecast by considering both exogenous factors and time series. The forecasting performance of both linear regression models and time series model are evaluated based on real-life heat demand data for the city of Espoo in Finland by out-of-sample tests for the last 20 full weeks of the year. The results indicate that the proposed linear regression model (T168h) using 168-h demand pattern with midweek holidays classified as Saturdays or Sundays gives the highest accuracy and strong robustness among all the tested models based on the tested forecasting horizon and corresponding data. Considering the parsimony of the input, the ease of use and the high accuracy, the proposed T168h model is the best in practice. The heat demand forecasting model can also be developed for individual buildings if automated meter reading customer measurements are available. This would allow forecasting the heat demand based on more accurate heat consumption

Gravitational black hole hair from event horizon supertranslations

Energy Technology Data Exchange (ETDEWEB)

Averin, Artem [Arnold-Sommerfeld-Center for Theoretical Physics,Ludwig-Maximilians-Universität, 80333 München (Germany); Max-Planck-Institut für Physik, Werner-Heisenberg-Institut,80805 München (Germany); Dvali, Gia [Arnold-Sommerfeld-Center for Theoretical Physics,Ludwig-Maximilians-Universität, 80333 München (Germany); Max-Planck-Institut für Physik, Werner-Heisenberg-Institut,80805 München (Germany); Center for Cosmology and Particle Physics, Department of Physics, New York University,4 Washington Place, New York, NY 10003 (United States); Gomez, Cesar [Instituto de Física Teórica UAM-CSIC, C-XVI, Universidad Autónoma de Madrid,Cantoblanco, 28049 Madrid (Spain); Lüst, Dieter [Arnold-Sommerfeld-Center for Theoretical Physics,Ludwig-Maximilians-Universität, 80333 München (Germany); Max-Planck-Institut für Physik, Werner-Heisenberg-Institut,80805 München (Germany)

2016-06-16

We discuss BMS supertranslations both at null-infinity BMS{sup −} and on the horizon BMS{sup H} for the case of the Schwarzschild black hole. We show that both kinds of supertranslations lead to infinetly many gapless physical excitations. On this basis we construct a quotient algebra A≡BMS{sup H}/BMS{sup −} using suited superpositions of both kinds of transformations which cannot be compensated by an ordinary BMS-supertranslation and therefore are intrinsically due to the presence of an event horizon. We show that transformations in A are physical and generate gapless excitations on the horizon that can account for the gravitational hair as well as for the black hole entropy. We identify the physics of these modes as associated with Bogolioubov-Goldstone modes due to quantum criticality. Classically the number of these gapless modes is infinite. However, we show that due to quantum criticality the actual amount of information-carriers becomes finite and consistent with Bekenstein entropy. Although we only consider the case of Schwarzschild geometry, the arguments are extendable to arbitrary space-times containing event horizons.

Gravitational black hole hair from event horizon supertranslations

International Nuclear Information System (INIS)

Averin, Artem; Dvali, Gia; Gomez, Cesar; Lüst, Dieter

2016-01-01

We discuss BMS supertranslations both at null-infinity BMS"− and on the horizon BMS"H for the case of the Schwarzschild black hole. We show that both kinds of supertranslations lead to infinetly many gapless physical excitations. On this basis we construct a quotient algebra A≡BMS"H/BMS"− using suited superpositions of both kinds of transformations which cannot be compensated by an ordinary BMS-supertranslation and therefore are intrinsically due to the presence of an event horizon. We show that transformations in A are physical and generate gapless excitations on the horizon that can account for the gravitational hair as well as for the black hole entropy. We identify the physics of these modes as associated with Bogolioubov-Goldstone modes due to quantum criticality. Classically the number of these gapless modes is infinite. However, we show that due to quantum criticality the actual amount of information-carriers becomes finite and consistent with Bekenstein entropy. Although we only consider the case of Schwarzschild geometry, the arguments are extendable to arbitrary space-times containing event horizons.

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...

Quantum correlations through event horizons: Fermionic versus bosonic entanglement

International Nuclear Information System (INIS)

Martin-Martinez, Eduardo; Leon, Juan

2010-01-01

We disclose the behavior of quantum and classical correlations among all the different spatial-temporal regions of a space-time with an event horizon, comparing fermionic with bosonic fields. We show the emergence of conservation laws for entanglement and classical correlations, pointing out the crucial role that statistics plays in the information exchange (and more specifically, the entanglement tradeoff) across horizons. The results obtained here could shed new light on the problem of information behavior in noninertial frames and in the presence of horizons, giving better insight into the black-hole information paradox.

klax 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...

kprc 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...

katl 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...

kmcn 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...

kogb 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...

kama 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...

ptkk 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...

kiwa 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...

kavp 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...

kdca 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...

kbwg 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...

kdfw 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...

kssi 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...

pahn 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...

ksrq 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...

kpvd 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...

kisp 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...

kttd 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...

pmdy 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...

kmgm 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...

khib 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...

pavd 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...

kfar 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...

kluk 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...

kwwr 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...

klse Terminal Aerodrome Forecast