COMBINATION OF NEURAL NETWORKS FORECASTERS FOR MONTHLY NATURAL GAS CONSUMPTION PREDICTION

摘要

This study presents different types of neural network algorithm based model forecasting gas consumption for residential and commercial consumers in Istanbul in Turkey. Using seven neural networks algorithms as forecasting models, we tried to find the best solution on forecasting of monthly natural gas consumption. These models were validated and tested on real monthly data from a distribution area covering two different regions of Anatolian and European sides in Istanbul. The analysis of results obtained for training and test sets show that the seven proposed artificial neural network models could be useful for the natural gas consumption forecast problem. It was shown that a conjugate gradient descent neural network model presented a more efficient solution than the other models.