Back Propagition Neural Network Simulation on Sediment Yield of Watershed Under Single Rainfall

HOU Jian-cai; LI Zhan-bin; LI Mian; WANG Min

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Back Propagition Neural Network Simulation on Sediment Yield of Watershed Under Single Rainfall

- Back Propagition Neural Network Simulation on Sediment Yield of Watershed Under Single Rainfall
- Bulletin of Soiland Water Conservation Vol. 26, Issue 3, Pages: 79-83(2007)
- 作者机构：
  
  1. 西安理工大学,陕西,西安,710048
  2. 黄土高原土壤侵蚀与旱地农业国家重点实验室,陕西杨凌,712100
  3. 黄河水利委员会黄河水利科学研究院,河南,郑州,450003
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2007
- 稿件说明：
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HOU Jian-cai, LI Zhan-bin, LI Mian, et al. Back Propagition Neural Network Simulation on Sediment Yield of Watershed Under Single Rainfall[J]. Bulletin of Soiland Water Conservation, 2007, 26(3): 79-83.
DOI：

HOU Jian-cai, LI Zhan-bin, LI Mian, et al. Back Propagition Neural Network Simulation on Sediment Yield of Watershed Under Single Rainfall[J]. Bulletin of Soiland Water Conservation, 2007, 26(3): 79-83. DOI：

摘要

在分析黄土高原韭园沟流域多年观测资料的基础上

应用BP神经网络建模方法

建立了流域次降雨侵蚀产沙的神经网络模型。通过输入模型变量流域次降雨量、平均降雨强度、径流深和洪峰流量模数

对流域次降雨侵蚀产沙量进行了训练和预测。预测结果表明

所建BP神经网络模型预测精度较高

可近似揭示复杂非线性流域次降雨侵蚀产沙系统的产沙规律

为建立较高预报精度的黄土高原流域次降雨侵蚀产沙预报模型提供了依据。

Abstract

On the basis of the analyses of twenty year data observed in Jiuyuangou watershed on the Loess Plateau

a model of sediment yield of watershed under single rainfall is propounded through the application of back propagition artificial neural network.The network model is trained and predicted by input rainfall

average rainfall intensity

runoff depth and flood-peak modulus.The predicted results show that the network model has good precision and accurately reflects the laws of nonlinear sediment yield of watershed under single rainfall.It provides a new foundation to establish the predicted model of sediment yield of watershed under single rainfall on the Losses Plateau.

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