Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation
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Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation
Bulletin of Soiland Water ConservationVol. 26, Issue 6, Pages: 152-224(2007)
作者机构:
1. 长沙理工大学 水利学院
2. ,陕西,西安,710048
3. 中国水电工程顾问集团公司中南勘测设计研究院
4. 西安理工大学 水资源研究所
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Published:2007
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LI Miao, ZHOU Jian-guo, SONG Xiao-yu, et al. Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation[J]. Bulletin of Soiland Water Conservation, 2007, 26(6): 152-224.
DOI:
LI Miao, ZHOU Jian-guo, SONG Xiao-yu, et al. Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation[J]. Bulletin of Soiland Water Conservation, 2007, 26(6): 152-224.DOI:
Application of BP Neural Network to the Analyses of Runoff and Sediment Yield with Different Types of Vegetation
simulation and prediction of runoff generation and sediment yield in four different runoff plots(farmland
wood land
artificial grassland
and abandoned land) are studied.Relative errors of runoff generation in four different plots are 0.2%- 5.7%
0.1%- 2.5%
0.7%-2.9%
and 0.1%-3%
respectively; relative errors of sediment yield
0.1%-3.2%
0.2% -3.1%
0.6%-4.2%
and 0.2%-2.7%; maximum relative errors of runoff generation
-11%
14%
-14.6%
and 18%; the maximum relative errors of sediment yield
10.9%
27.3%
15.0%
and 26.3%.The results show that the effect of simulation and prediction of runoff generation and sediment yield using the met hod of BP neural network is good and that application of this method to the analyses of impound and intercepting sediment from runoff plot is feasible.