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基于自适应蚁群算法的粗糙集属性约简
引用本文:姚跃华,洪杉.基于自适应蚁群算法的粗糙集属性约简[J].计算机工程,2011,37(3):198-200.
作者姓名:姚跃华  洪杉
作者单位:长沙理工大学计算机与通信工程学院,长沙,410114
摘    要:定义粗糙集理论的近似精度,引入信息索交流机制和交流概率,通过自适应调节每组蚂蚁间的信息素浓度改进传统蚁群算法,并将其应用于粗糙集属性约简算法中.实验结果表明,相比其他属性约简算法,该算法提高了获得最小属性约简的可能性,具有较好的收敛速度且不易陷入局部最优解.

关 键 词:粗糙集  最小属性约简  蚁群算法

Rough Set Attribute Reduction Based on Adaptive Ant Colony Algorithm
YAO Yue-hua,HONG Shan.Rough Set Attribute Reduction Based on Adaptive Ant Colony Algorithm[J].Computer Engineering,2011,37(3):198-200.
Authors:YAO Yue-hua  HONG Shan
Affiliation:(Institute of Computer and Communication Engineering,Changsha University of Science & Technology,Changsha 410114,China)
Abstract:This paper defines the approximation of rough set theory, introduces pheromone exchange mechanism and exchange rate. It improves traditional Ant Colony Algorithm(ACA) by self-adapting each group of ants between pheromone strength, applies to the rough set attribute reduction algorithm. Experimental results show that the algorithm can improve minimum attribute reduction of posslbilities, and it has good convergence speed and local optimal solution compared to other attribute reduction algorithms.
Keywords:rough set  minimum attribute reduction  Ant Colony Algorithm(ACA)
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