Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Research on Neural Network Flood Forecasting Model Based on Hydrological Model

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322689,
        author={Fanchun  Li},
        title={Research on Neural Network Flood Forecasting Model Based on Hydrological Model},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={bp neural network model; stochastic model; runoff forecast},
        doi={10.4108/eai.17-6-2022.2322689}
    }
    
  • Fanchun Li
    Year: 2022
    Research on Neural Network Flood Forecasting Model Based on Hydrological Model
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322689
Fanchun Li1,*
  • 1: Jiangxi University of Applied Science
*Contact email: zhc010314@163.com

Abstract

In view of the problem of inaccurate flood prediction of the current BP neural network model, establishing a neural network flood prediction model based on the random information of the hydrological model can effectively combine the advantages of various hydrological models and avoid the disadvantages of various hydrological models, so as to accurately predict the flood information. Hydrologic model randomly simulates large floods, and then inputs flood information into the neural network model, which can enhance the accuracy of flood prediction. It can also be seen from the last example that this method is more effective, and the flood prediction model based on the neural network model can be better put into application.