Attribute reduction algorithm based on genetic algorithm
The most issue is designing the fitness function of the chromosome when Generic algorithm is been used for gcaiculating the minimal attribute reduction in rough set theory.But with the existed fitness function of the chromosome,the one that the value of the fitness function is larger might not be an attribute reduction.So the optimization candidate attribute reduction might not be the minimal attribute reduction.What is more,during the crossover and mutation process,it could not delete the candidate attribute reduction which is not the minimal attribute reduction.To solve the mentioned problems and speed up the convergence speed.In this paper,a new fitness function is introduced,and proved that the optimization candidate attribute reduction must be an attribute reduction.It also can delete the candidate attribute reduction which is not the minimal attribute reduction in the crossover and mutation process.Then an efficient attribute reduction algorithm based on genetic algorithm is proposed.The results of experiment show that the new algorithm may find the minimal attribute areduction and has quick convergence speed.
rough set attribute reduction genetic algorithm new fitness function
Zhangyan Xu Dongyuan Gu Bo Yang
College of Computer Science & Information Engineering,Guangxi Normal University,Gulin 541004, China Postdoctoral Programme, Bank of Beijing, Beijing, 100081, China
国际会议
长沙
英文
169-172
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）