DocumentCode
2599388
Title
Safety evaluation research of hydraulic steel gate based on BP-neural network
Author
Jianbin, Guo ; Yuanchang, Wen ; Jian, Xiao
Author_Institution
Coll. of Water Conservancy & Hydropower Eng., Hohai Univ., Nanjing, China
fYear
2009
fDate
6-7 April 2009
Firstpage
1
Lastpage
4
Abstract
Aiming at actual condition that the semi-empirical and semi-theoretical researches exist generally in the safety valuation of hydraulic steel gate in service, a new method has been provided, in which the evaluation model is built by BP-neural network, and trained through the normalized corrosion data of hydraulic steel gate. Project applications show that the method evaluated hydraulic steel gate exactly and objectively, and can ensure safety and reliability of gate operation.
Keywords
backpropagation; neural nets; structural engineering computing; BP neural network; backpropagation; hydraulic steel gate; normalized corrosion training data; Hydroelectric power generation; Inspection; Multi-layer neural network; Neural networks; Safety devices; Security; Standards development; Steel; Water conservation; Water resources;
fLanguage
English
Publisher
ieee
Conference_Titel
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-4934-7
Type
conf
DOI
10.1109/SUPERGEN.2009.5348021
Filename
5348021
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