Abstract: By use of searching technique of ant colony algorithm, a rough set attribute reduction method based on ACA was proposed. The core was joined in initial pheromone in order to accelerate convergence. Dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating based on the distribution of the solutions, the algorithm can advance global capability. Experimental results show that the algorithm is effective, and has better convergence speed and stability.

Key words: Rough set , Ant colony algorithm , Attribute reduction

摘要： 利用蚁群算法的搜索技术,提出了一种基于蚁群算法的粗糙集属性约简方法。该算法将核引入初始
信息素分布中,以加快算法的收敛。同时为提高全局搜索能力,根据蚂蚁在搜索过程中所得解的分布状况动态地调
解蚂蚁的路径策略和信息量更新策略。实验证明该算法是有效的,具有较好的收敛速度和稳定性。

关键词: 粗糙集 , 蚁群算法 ,  属性约简