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 possibilities, and it has good convergence speed and local optimal solution compared to other attribute reduction algorithms.

Key words: rough set, minimum attribute reduction, Ant Colony Algorithm(ACA)

摘要： 定义粗糙集理论的近似精度，引入信息素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

CLC Number: 

• TP181