Optimization of a subset of features based on fuzzy genetic algorithm

摘要：

To overcome global situation problem tradition genetic algorithm has very strong robustness in finding the solution, but crossover probability and mutation probability is fixed and invariable, it caused premature convergence and running inefficient to the solution on complicated problem at later evolution process of tradition genetic algorithm. To this problem the paper proposed a new algorithm with varying population size based on lifetimes of the chromosomes to realize population size adjust adaptively and crossover probability adjust adaptively and mutation probability adjust adaptively, which called fuzzy genetic algorithm. Compare to tradition genetic algorithm, experiment results show that the approach proposed is effective in the capability of global optimization and significantly improves the convergence rate.

作者: LIU Peiyu ZHU Zhenfang XU Liancheng CHI Xuezhi

作者单位: School of Information Science and Technology, Shandong Normal University, JiNan 250014, China School of Computer,Shandong Police college, JiNan 250014, China

会议类型: 国际会议

会议名称: 2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)

会议地点: 济南

会议语种:英文

页码: 933-937

在线出版日期: 2009-08-14（万方平台首次上网日期，不代表论文的发表时间）