DocumentCode
2895804
Title
Neural Network with Adaptive Immune Genetic Algorithm for Eddy Current Nondestructive Testing
Author
Sun, Xiao-Yun ; Liu, Dong-Hui ; Chen, Ai-zu ; Zhi-Hong Xue
Author_Institution
Hebei Univ. of Sci. & Technol., Shijiazhuang
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
3106
Lastpage
3109
Abstract
For eddy current nondestructive testing (ECNDT), an immune genetic algorithm (IGA) is presented, which can overcome the disadvantages of genetic algorithm (GA), such as possibility of being trapped on locally minimum value and prematurity convergence. Moreover, crossover and mutation operators are selected by adaptive algorithm to overcome prematurity. Compared with GA, the convergence precision and generalization of IGA are improved remarkably
Keywords
artificial intelligence; eddy current testing; genetic algorithms; neural nets; adaptive algorithm; adaptive immune genetic algorithm; convergence precision; eddy current nondestructive testing; neural network; Adaptive systems; Convergence; Eddy currents; Genetic algorithms; Humans; Immune system; Machine learning; Magnetic fields; Neural networks; Nondestructive testing; Pathogens; Adaptive algorithm; ECNDT; IGA; Prematurity;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258399
Filename
4028598
Link To Document