Short term hourly forecasting of gas consumption using neural networks

This paper presents a neural network based model for forecasting gas consumption for residential and commercial consumers. A feedforward neural network with sigmoid nodes and one hidden layer was trained by backpropagation. The model was validated on real data from a distribution area covering 7% of the total consumption in Croatia, consisting mostly of residential and commercial consumers.