This paper presents an assessment of the renewable energy potential in Romania using a clustering based data mining … renewable energy potential for electricity generation was mapped into representative zones using K-Means clustering algorithm …

results. This paper provides an overview of the clustering techniques used to establish suitable customer grouping, included … assessing the performance of the clustering algorithms for load pattern grouping is then addressed, showing how the parameters … used to formulate different clustering methods impact on the clustering validity indicators. It emerges that the clustering …

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.” …