Water Quality Evaluation of RBF Neural Network Based on Optimized Parameter of Genetic Algorithm

In order to improve water quality evaluation of multi-spectral image accurately,this paper puts forward a model for water quality evaluation of Radial Basis Function(RBF) neural network based on optimized parameters of Genetic Algorithm(GA).The method uses SPOT-5 data and the water quality field data.It chooses four representative water quality parameters.RBF neural network is trained and tested,and the parameters of RBF neural network are optimized by particle swarm optimization algorithms.Water quality parameters of COD,NH3-N,DO,CODmn are retrieved by the trained RBF neural network.Experimental result shows that the method has more accuracy than the routine method.