会议专题

Research on the Genetic Algorithm Simulating Human Reproduction Mode and its Blending Application with Neural Network

  In this study,a genetic algorithm simulating human reproduction mode (HRGA) is proposed.The genetic operators of HRGA include selection operator,help operator,crossover operator and mutation operator.The sex feature,age feature and consanguinity feature of genetic individuals are considered.Two individuals with opposite sex can reproduce the next generation if they are distant consanguinity individuals and their age is allowable.Based on this genetic algorithm,an improved evolutionary neural network algorithm named HRGA-BP algorithm is formed.In HRGA-BP algorithm,HRGA is used firstly to evolve and design the structure,the initial weights and thresholds,the training ratio and momentum factor of neural network roundly.Then,training samples are used to search for the optimal solution by the evolutionary neural network.HRGA-BP algorithm is used in motor fault diagnosis.The illustrational results show that HRGA-BP algorithm is better than traditional neural network algorithms in both speed and precision of convergence,and its validity in fault diagnosis is proved.

Human reproduction mode Genetic algorithm Evolutionary neural network BP algorithm Motor fault diagnosis

YAN Tai-shan

School of Information and Communication Engineering, Hunan Institute of Science and Technology,China

国际会议

2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

西安

英文

1785-1789

2012-08-24(万方平台首次上网日期,不代表论文的发表时间)