ANN models have very high accuracy for prediction and better forecasting performance than the other models. The proposed …

development of wind power production, improvement of the prediction of wind turbine output energy using classical or intelligent … energy from the wind by prediction the optimal values of the wind turbine reaction torque. To build an effective prediction …) for prediction of wind turbine reaction torque in this research study. Instead of minimizing the observed training error …

potential domains is control, where short-term prediction of heat load can play a significant role. With reliable prediction of … functions, with different set of input variables and for four prediction horizons. Model building and testing was performed …-mean-square error) and the coefficient of determination (R2). The prediction results of SVR–POLY models outperformed the results of SVR …

the prediction of CO2, CO/CO2 ratio, TF and (η) of DG. The training and testing data required to develop the ANN were … that the ANN models are reliable tools for the prediction of the performance and exhaust emissions of DGs. …

This paper presents methods for prediction of energy consumption of different appliances in homes. The aim is to …

prediction of 2005–2008, 2010, 2012 and 2015 Greek energy consumption. The produced ANN results for years 2005–2008 were compared … accurate tool for the Greek long-term energy consumption prediction problem, which up today has not been faced effectively. …

taken from the literature were tested for prediction of monthly mean daily global solar radiation over six major cities of …

This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction …

to predict total electricity consumption during a subsequent “prediction period.” …