Elie A. Badr

Learn More
Significant errors of train axle generators (tachometers) are due to wheel slip and slide. In this paper, an algorithm is designed to compensate for these errors. The algorithm identifies the wheel slip and slide by examining the variation of the processed vehicle longitudinal acceleration. Whenever wheel slip/slide is identified, then the vehicle speed is(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