Application of Neural Network Algorithms to Flood Forecasting Using Traditional Hydrological Models
In order to forecast flood accurately and reduce the loss caused by flood disaster every year.In this paper,a hydrological model that combines the BP neural network algorithm with the semi-distributed Xin'Anjiang(XAJ)model is proposed.The one-cycle correction and real-time correction are tested with a practical case.The results show that the improved hydrological model incorporating BP neural network into the traditional hydrological model can correct the prediction error of the Xin'anjiang model,improve prediction accuracy,and shorten the correction calculation time,which has certain application value.
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