Application of BP Neural Networks to Testing the Reasonableness of Flood Season Staging

Yan Guo, Zhongmin Liang, Suzhen Hou
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Abstract

Flood season staging scientifically and reasonably can coordinate the relationship of reservoir of flood control and beneficial use, and realize flood resource sustainable utilization. At present, there are many methods of flood season staging, but the results reasonableness testing are remained to be done. In this paper, on the basis of Projection Pursuit (PP) and Set Pair Analysis (SPA) introductions, use the Panjiakou reservoir in Luan River basin as example, divide the flood season with the two methods, and simulate the results with back propagation neural networks (BPNN), use the errors of simulation results as indexes, analyze and contrast the results of the two methods. The result shows that the model is reasonable, it brings up a new idea to test the reasonableness of division of flood season.
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BP神经网络在汛期分期合理性检验中的应用
科学合理的汛期分期可以协调水库防洪与有益利用的关系,实现洪水资源的可持续利用。目前,汛期分期的方法很多,但结果的合理性还有待检验。本文在投影寻踪法(Projection Pursuit, PP)和集对分析法(Set Pair Analysis, SPA)介绍的基础上,以滦河流域潘家口水库为例,用这两种方法对汛期进行划分,并利用反向传播神经网络(back propagation neural network, BPNN)对结果进行模拟,以模拟结果的误差为指标,对两种方法的结果进行分析对比。结果表明,该模型是合理的,为检验汛期划分的合理性提供了一种新的思路。
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