Application of Optimization Model Based on Neural Network in Flood Forecasting of Po-yang Lake

Through analyzing main affecting factors of the artificial neural network model, the optimization model is established and the optimization parameters is obtain based on the method of momentum and self-adaptive of learn rate, This optimize artificial neural network is not only set up with the limited training samples, but also can improve the operating speed and study efficiency. The optimization mode of the of flood prediction of Po-yang Lake is build by past years data of floods in Po-yang Lake, it shows that its precision is high, and its computation is simple. The method by optimization neural network, which applied to flood forecasting of Po-yang Lake, provides a new attempt for Prediction analysis and prove to be feasible and effective for practical experience in complex system engineering of Po-yang Lake.