Applications of Neural Networks and Fuzzy Logic for Integrated Water Management: Review of Theory and Applications

Author : Neeru Gupta, Parveen Sehgal & Sudesh Rani

Abstract

In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modeling in the water resources management field are considered. Neural network and fuzzy logic have been successfully applied to a wide range of problems covering a variety of sectors. Their practical applications, especially of neural networks expanded enormously starting from mid 80s till 90s partly due to a spectacular increase in computing power. During the last decade ANN evolved from being only a
research tool into a tool that is applied to many real world problems: physical system control, various engineering problems, statistics, medical and biological fields. Consequently they are applied more and more in water management field as well. This paper reviews the applications of neural network and fuzzy adaptive systems for integrated water resources management.

Keywords: Artificial neural network, fuzzy logic, water quality management.