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

Content Provider	IEEE Xplore Digital Library
Author	Yan Guo Zhongmin Liang Suzhen Hou
Copyright Year	2013
Description	Author affiliation: Yellow River Inst. of Hydraulic Res., YRCC, Zhengzhou, China (Yan Guo; Suzhen Hou) \|\| Coll. of Hydrol. & Water Resource, Hohai Univ., Nanjing, China (Zhongmin Liang)
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.
Sponsorship	Nanjing Sect. CIS Chapt.
Starting Page	42
Ending Page	46
File Size	170574
Page Count	5
File Format	PDF
ISBN	9780769550794
DOI	10.1109/ISCID.2013.18
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks projection pursuit set pair analysis flood season staging Reservoirs Rivers Floods Indexes Standards back propagation neural networks flood resource
Content Type	Text
Resource Type	Article

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