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
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;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1341940
