Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...

Accurate prediction of the future electricity consumption is crucial for production electricity management. Since the storage of electrical energy is very difficult, reliable and accurate prediction of power consumption is important. Different approaches for this purpose were used. In this paper, Grey model (1,1) based on grey system theory has been used for forecasting results. Annual electric...

Twenty-five years ago, the International Institute of Forecasters was established “to bridge the gap between theory and practice.” Its primary vehicle was the Journal of Forecasting and is now the International Journal of Forecasting. The Institute emphasizes empirical comparisons of reasonable forecasting approaches. Such studies can be used to identify the best forecasting procedures to use u...

Balancing the production and consumption of electricity is an urgent task. Its implementation largely depends on means methods planning production. Forecasting one tools since availability accurate forecast a mechanism for increasing validity management decisions. This study provides overview used to predict supply requirements different objects. The have been reviewed analytically, taking into...

Purpose of the study . The purpose is to develop a model for predicting university performance indicators based on cognitive approach, which construction map that reflects influence set latent factors basic and provides solution problem scenario forecasting. degree achievement required values determine ranking depends magnitude increment identified factors. developed makes it possible choose mo...

This research conducts an error analysis between the forecasting value and the actual value of steel demand of 2010 in China, which is based on the analysis of forecasting methods and their results of Chinese steel demand in the existing studies, and then forecasts China’s steel demand in 2015 by making use of a combined forecasting method. The combined forecasting method includes two stages. I...

The increasing availability of large amounts of historical data and the need of performing accurate forecasting of future behavior in several scientific and applied domains demands the definition of robust and efficient techniques able to infer from observations the stochastic dependency between past and future. The forecasting domain has been influenced, from the 1960s on, by linear statistica...

Many studies have demonstrated that combining forecasts improves accuracy relative to individual forecasts. In this paper, the combing forecasts is used to improve on individual forecasts is investigated. A combining approach based on the modified Group Method Data Handling (GMDH) method and genetic algorithm (GA), is called as the GAGMDH model is proposed. Four time series forecasting techniqu...

It is shown how the closure condition for the set of kinetic equations in Zubarev's Nonequilibrium Statistical Operator Method introduces a series of uxes of a reference set of densities. These uxes are the average values, over a Gibbs-like nonequilibrium generalized grandcanonical ensemble, of Hermitian operators for uxes de ned at the microscopic-mechanical level. The equations of evolution f...

applications of supervised and unsupervised ensemble methods What to say and what to do when mostly your friends love reading? Are you the one that don't have such hobby? So, it's important for you to start having that hobby. You know, reading is not the force. We're sure that reading will lead you to join in better concept of life. Reading will be a positive activity to do every time. And do y...