Artificial Intelligence Approaches for Urban Water Demand Forecasting: A Review

Abstract

In various research fields such as medicine, science, marketing, engineering and military. Artificial intelligence approaches have been applied, mainly due to their powerful reasoning capability, flexibility, modeling and forecasting capacity. In this paper, an attempt to review urban water demand forecasting using various artificial intelligence based approaches such as fuzzy logic systems, support vector machines, extreme learning machines, ANN and an ARIMA as well as hybrid models which consist of an integration of two or more artificial intelligence approaches are applied. The paper illustrates how the different artificial intelligence approaches plays a vital role in urban water demand forecasting while recommending some future research directions.