DocumentCode
1560712
Title
Neural network with adaptive genetic algorithm for eddy current nondestructive testing
Author
Xiaoyun, Sun ; Donghui, Liu ; Kai, Zhang ; Liwei, Guo ; Ran, Zhen ; Jianye, Liu
Author_Institution
Dept. of Autom. Eng., Hebei Univ. of Sci. & Technol., China
Volume
3
fYear
2004
Firstpage
2034
Abstract
For eddy current nondestructive testing (ECNDT), adaptive genetic algorithm (GA) is adopted, which can overcome the disadvantages of back propagation (BP) artificial neural network (ANN), such as a possibility of being trapped on locally minimum value. Moreover, GA operators are selected by adaptive algorithm to overcome the prematurity. Compared with BP-ANN, the convergence precision and generalization of GA-ANN are improved remarkably.
Keywords
backpropagation; eddy current testing; electrical engineering computing; generalisation (artificial intelligence); genetic algorithms; neural nets; BP-ANN; adaptive genetic algorithm; artificial neural network; back propagation; convergence precision; eddy current nondestructive testing; generalization; Adaptive systems; Artificial neural networks; Biological cells; Eddy currents; Genetic algorithms; Genetic engineering; Genetic mutations; Magnetic fields; Neural networks; Nondestructive testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1341940
Filename
1341940
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