DocumentCode :
1982326
Title :
Application of BP Neural Networks to Testing the Reasonableness of Flood Season Staging
Author :
Yan Guo ; Zhongmin Liang ; Suzhen Hou
Author_Institution :
Yellow River Inst. of Hydraulic Res., YRCC, Zhengzhou, China
Volume :
1
fYear :
2013
fDate :
28-29 Oct. 2013
Firstpage :
42
Lastpage :
46
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.
Keywords :
backpropagation; floods; geophysics computing; neural nets; reservoirs; rivers; BP neural networks; BPNN; Luan River basin; PP; Panjiakou reservoir; SPA; back propagation neural networks; flood control; flood resource sustainable utilization; flood season staging; projection pursuit; reasonableness testing; set pair analysis; simulation error; Floods; Indexes; Neural networks; Reservoirs; Rivers; Standards; back propagation neural networks; flood resource; flood season staging; projection pursuit; set pair analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/ISCID.2013.18
Filename :
6804782
Link To Document :
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