Forecasting yearly natural gas consumption using Artificial Neural Network for the Algerian market

Abstract

the focus of this paper is put on developing Neural Networks approach to predict annual natural gas consumption in Algeria for the three pressure sectors (low pressure, medium pressure and high-pressure sector). Four main distribution areas constitutes the Algerian distribution company (SONALGAZ). Beside each distribution area consists of several distribution divisions (DD). Thus in this paper instead of creating a single neural network model with one dataset to estimate a sector consumption, each DD is considered on its own by selecting the most influential inputs, then developing its specific Multi Layer Perceptron (MLP) model trained with Levenberg-Marquardt learning algorithm, and finally summing their results to get the total consumption for the sectors.