Application of Improved BP Neural Network in XAJ with Multiple Water Sources

This paper tries to apply particle swarm optimization (pso) algorithm to improve the BP-neural network, and the second water source, three water, four water XAJ parameter calibration, the predicted results are compared. The results of different models of river basin water right choice. This paper mainly studies the BP neural network based on PSO algorithm of distributed four water xin an river model calculation, this paper did research work includes the following aspects: (1) based on the research of the common water level model, select the appropriate parameters, establish proper data model (2) based on the research of the common prediction algorithm, BP neural network as the main algorithm to parameter calibration, and apply the PSO algorithm to optimize the BP neural network.