• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (2): 397-401.

• 论文 • Previous Articles     Next Articles

A GA-PSO based attribute reduction algorithm for rough set

DAI Shangping,LIU Sujun,ZHENG Sufei   

  1. (School of Computer Science,Central China Normal University,Wuhan 430079,China)
  • Received:2014-06-03 Revised:2014-08-03 Online:2015-02-25 Published:2015-02-25

Abstract:

Attribute reduction is one of the main contents in rough set theory study.In order to achieve attribute reduction effectively,a GAPSO based attribute reduction algorithm for rough set is proposed.According to the dependability of the decision attributes to the condition attributes,the proposed algorithm can calculate the core attributes.All the condition attributes except the core attributes are added to the initial population of the PSO (Particle Swarm Optimization) algorithm,and then the crossover and mutation operations of the genetic algorithm are performed on the particles that do not meet the fitness conditions.Experimental results show that the algorithm can enhance the local search ability as well as maintain the feature of global optimization,and calculate the minimum relative attribute set quickly and effectively.

Key words: rough set;attribute reduction;GA-PSO;core