ANN based on PSO for surface water quality evaluation model and its application

In view of the deficiency of the traditional methods, according to the analysis of surface water in Suzhou city, a BP neural network model is proposed to evaluate water quality. Firstly The present situation and changing trends of surface water are analyzed. The structure of BP model is described and the choice of hidden layer is also optimized. Finally, the proposed model was applied to evaluate the surface water quality in Suzhou city. BP neural network is trained using PSO. The evaluation result was compared with that of the BP neural network method without training by PSO and the reported results. It indicated that the performance of proposed neural network model is practically feasible in the application of water quality assessment and its operation is simple.