Part of #Application of Wavelet-GP Model for Estimation of Daily Rivers Suspended Sediment Load# :
Publishing year : 2011
Conference : The first international conference and the third national conference on hydroelectric dam and power plants
Number of pages : 10
Abstract: Accurate estimation of sediment outflow is one of the most important factors in water development projects. Estimate of sediment yield is required in a wide spectrum of problems such as: design of reservoirs and dams, transport and deposition of sediments in channel networks and water pollution. It is difficult to designate the governor equations of suspended sediments because of different parameter effects, and comparative mathematical models do not usually have sufficient accuracy. In this study, we use a conjunction of wavelet and genetic programming to develop a black box prediction of sediment Genetic Programming (GP) is also one of the evolutionary methods in developing black-box models in hydrology. This paper studies the effect of decomposing inputs by wavelet GP performance and investigates the functions and decomposition levels which represent better performance. The results of this study show that the four major matemative operators estimate the sediment load better. The use of wavelet-genetic programming modules in reservoirs load estimation is also studied in this Paper. Although both GP and WGP are both satisfied G, employing wavelet transform to decompose inputs reduces the need to increase the temporal memory of models.