Application of gray system and RBF neural network in the mid-long term hydrological forecasting
The timely and accurate long-term hydrological forecasting can promote the optimization of reservoir management effectively. We regard the monthly runoff of non-flood period as the predictor, calculate the gray correlations of runoff between the future years and the past years, and then select the years with larger gray correlations as example years. The MATLAB is ap-plied to build RBF neural network forecasting model, and the runoff data of the selected example years is used to forecast the flood season runoff of the future forecasting years. Taking Qinghe Reservoir as an example, we forecast the flood season runoff by this forecasting model. The forecasting results show that the model is feasible with quick forecasting speed and satisfying results.
gray systemRBF neural networkmid-long term hydrological forecasting
国家科技期刊平台
NSTL
万方数据
维普
