Application of Neural Network and GA in Runoff Prediction Model

A new method for training the neural network prediction model is presented. In this method, the genetic algorithm(GA),a general-purpose global search algorithm is used to update the initial weights for minimizing the error between the network output and the desired output. Then the back-propagation(BP) algorithm is used to further train the neural network prediction model. This method is used to speed up the convergence and improve the performance. Analyzing and discussing the case of Yazikou,Qingjiang demonstrated the procedures and performance of this neural network-training algorithm.