张小峰, 许全喜, 裴莹. 流域产流产沙BP网络预报模型的初步研究[J]. 水科学进展, 2001, 12(1): 17-22.
引用本文: 张小峰, 许全喜, 裴莹. 流域产流产沙BP网络预报模型的初步研究[J]. 水科学进展, 2001, 12(1): 17-22.
ZHANG Xiao-feng, XU Quan-xi, PEI Ying. Preliminary Research on the BP Networks Foreasting Model of Watershed Runoff and Sediment Yielding[J]. Advances in Water Science, 2001, 12(1): 17-22.
Citation: ZHANG Xiao-feng, XU Quan-xi, PEI Ying. Preliminary Research on the BP Networks Foreasting Model of Watershed Runoff and Sediment Yielding[J]. Advances in Water Science, 2001, 12(1): 17-22.

流域产流产沙BP网络预报模型的初步研究

Preliminary Research on the BP Networks Foreasting Model of Watershed Runoff and Sediment Yielding

  • 摘要: 运用BP神经网络模型的基本原理,以流域降水条件为基本因子,建立了流域产流产沙BP网络预报模型.该模型能用于定量分析流域人类活动因素对流域产流产沙的影响.西汉水、大通江、香溪河流域资料验证表明,模型基本合理、可靠.

     

    Abstract: In this paper,considering the radical principle of neural networks and acting rainfall condition as the main affecting factors,a back propagation (BP) networks model of watershed runoff and sediment yielding is discussed.The model has satisfactory learning and generalization performance,and it may be used to value the human-action influence on runoff and sediment yielding in a watershed.The results identified by Xihanshui, Datongjiang and Xiangcihe basins's observed data indicate that the model are satisfactory.

     

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