DocumentCode :
3211186
Title :
BP network model optimized using the genetic algorithms and the application on fault diagnose of equipments
Author :
Meng Xianyao ; Han Xinjie ; Meng Song
Author_Institution :
Dalian Maritime Univ., Liaoning, China
fYear :
2006
fDate :
7-11 Aug. 2006
Firstpage :
1276
Lastpage :
1280
Abstract :
The BP nerve network has been widely applied on fault diagnosis. The BP network due to adopt search arithmetic along grads drop, therefore there are some problems such as slow convergence rate and easily getting into local infinitesimal. The genetic algorithms has the excellence of rapid searching rate. Therefore, auto-adapt genetic algorithms is adopted to optimize the BP algorithms in the paper. For example, for fault diagnosis in shafting of main engine, an ideal effect can be got while adopting BP network which had been optimized by genetic algorithms.
Keywords :
arithmetic; backpropagation; convergence; fault diagnosis; genetic algorithms; search problems; BP network model; equipment fault diagnosis; genetic algorithms; main engine shafting; search arithmetic; Arithmetic; Artificial intelligence; Convergence; Engines; Flyback transformers; Genetic algorithms; IEEE catalog; BP network; equipment; fault diagnose; genetic algorithms; shafting of main engine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
Type :
conf
DOI :
10.1109/CHICC.2006.280639
Filename :
4060289
Link To Document :
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