Review of Genetic Programing in Water Resource Engineering

Correct estimation of sediment volume carried by a river is very important for many water resources projects. Empirical relations such as sediment rating curves are often applied to determine the average relationship between discharge and suspended sediment load. This type of models generally underestimates or overestimates the amount of sediment. During recent decades, some black box models based on artificial neural networks have been developed to overcome this problem. GP has been applied to a wide range of problems in artificial intelligence, engineering and science applications, industrial, and mechanical models. The main purpose of this paper is literature review of Genetic Programming for suspended sediment estimation.