Medium-Long Term Prediction of Monthly Discharge at Xiangjiang River Based on Neural Network

In this paper, the neural network medium-long term hydrological forecasting model coupling LM algorithm with self-adaptive algorithm is established in combining statistical analysis with fuzzy analysis, choosing predictors such as rainfall and atmospheric circulation in the previous stage that affect the monthly discharge at the Xiangtan station of the Xiangjiang River, comparing the advantage and disadvantage of several modified BP algorithms, discussing several problems in the modeling process. The results of prediction show that the model is highly effective.