Learn More
This paper applies econometric models to investigate determinants of electrical energy Ž . consumption in post-war Lebanon. The impact of the Gross Domestic Product GDP , Ž . Ž . proxied by total imports TI , and degree days DD on electricity consumption is investigated over different time spans covering the period from 1993 to 1997. The time spans are(More)
This paper applies artificial neural networks to forecast gasoline consumption. The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. To forecast gasoline(More)
This paper presents an artificial neural network (ANN) approach to electric energy consumption (EEC) forecasting. In order provide the forecasted energy consumption, the ANN interpolates between the EEC and its determinants in a training data set. In this study, two ANN models are presented and implemented on real EEC data. The first model is a univariate(More)
  • 1