Water Supply System Demand Forecasting Using Adaptive Neuro-Fuzzy Inference System

Domestic water demand has been increasing due to rapid population growth and better living standards resulting from global economic development. On the other hand, water available for withdrawal and usage show decline in trend due to climate change arising from accelerated urbanization and industrial revolution. Under this starved conditions, the main target of water supply providers should be equitable distribution of limitedly available water to all the consumers. This necessitates to arrive at the compromise between demand and supply level. To ensure the equity in water supply, accurate forecasting of water demand becomes vital so as to plan the level of supply that minimizes the deviation of shortfall from the demand among the consumers. As the demand gets influenced by several factors and often qualitative in nature, this paper presents adaptive neuro-fuzzy inference system to forecast it and the results obtained evidenced the suitability of the proposed model. (C) 2015 The Authors. Published by Elsevier B.V.