NEURAL NETWORK WITH ADAPTIVE IMMUNE GENETIC ALGORITHM FOR EDDY CURRENT NONDESTRUCTIVE TESTING

摘要：

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.

关键词： ECNDT IGA Prematurity Adaptive algorithm

作者: XIAO-YUN SUN DONG-HUI LIU AI-ZU CHEN ZHI-HONG XUE

作者单位: Hebei University of Science & Technology, Shijiazhuang, 050054, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3106-3109

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）