Neural and fuzzy neural networks for natural gas consumption prediction

Abstract

In this work several approaches to prediction of natural gas consumption with neural and fuzzy neural systems for a certain region of Poland are analyzed and tested. Prediction strategies tested in the paper include: single neural net module approach, combination of three neural modules, temperature clusterization based method, and application of fuzzy neural networks. The results indicate the superiority of temperature clusterization based method over modular and fuzzy neural approaches. One of the interesting issues observed in the paper is relatively good performance of the tested methods in the case of a long-term (four week) prediction compared to mid-term (one week) prediction. Generally, the results are significantly better than those obtained by statistical methods currently used in the gas company under consideration.