Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (1): 53-56.

• 研究、探讨 • Previous Articles     Next Articles

Minimal attribute reduction algorithm based on GA-PSO

LV Zhenzhong, XUE Huifeng, ZHONG Ming, LIU Huan   

  1. College of Automation, Northwestern Polytechnical University, Xi’an 710072, China

  • Received:1900-01-01 Revised:1900-01-01 Online:2012-01-01 Published:2012-01-01


吕振中,薛惠锋,钟 明,刘 欢   

  1. 西北工业大学 自动化学院,西安 710072

Abstract: Attribute reduction is a key point of rough set theory. In order to get minimal subsets of attributes, this paper uses a GA-PSO mixed algorithm applying to attribute reduction. This algorithm in the premise of ensuring optimal ability, increases the diversity of population, and avoids being trapped in the local optimum, in the meantime, adds the penalty function in the fitness function. The experiment results show that it not only keeps the ability in getting reduction but also deduces the number of attribution, and it can obtain the prime effect.

Key words: rough set, attribute reduction, Genetic Algorithm-Particle Swarm Optimization(GA-PSO)



关键词: 粗糙集, 属性约简, 粒子群算法和遗传算法融合的混合算法(GA-PSO)