Abstract
Socio‐economic variables including gross domestic product, population, and energy and electricity production are used in modeling and forecasting national energy demands of the United Arab Emirates, Saudi Arabia, and Qatar. The proposed model features: (i) the nonlinear component of energy demand (removal of linear trend), (ii) application of double exponential smoothing method for input data projection, and (iii) genetic algorithm‐based artificial neural network (ANN) models. The proposed neuro‐genetic model performed very well for the three selected countries. The coefficient of determination and Willmott's index of agreement for the training and testing dataset are quite high whereas the mean absolute error, mean absolute percentage error and root mean squared error are quite low. The acceptable agreements between the observed energy consumption and the model predictions revealed its viability for the study of energy demand in the three selected member states of the energy exporting regional alliance Gulf Cooperation Council (GCC). © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1208–1216, 2017
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