1. 西安交通大学系统工程研究所,西安,710049
2. 西安交通大学机械制造系统工程国家重点实验室,西安,710049
网络首发:2008-04-10,
纸质出版:2008
移动端阅览
任志刚 1, 冯祖仁 1, 2, 等. 蚁群优化属性约简算法[J]. 西安交通大学学报, 2008,42(4):440-444.
任志刚 1, 冯祖仁 1, 2, et al. Ant Colony Optimization Approach to Attribute Reduction Problem[J]. 2008, 42(4): 440-444.
为了获得决策表属性的最小约简
将信息论角度定义的属性重要性作为启发信息引入蚁群算法
提出了一种蚁群优化属性约简算法.该算法将属性核直接引入到蚂蚁构造的每一个解中
降低了问题规模
新定义的状态转移规则和信息素更新规则体现了约简中属性间的无序性特点
有利于在优解邻域内搜索.通过9个典型实例对算法进行了验证
结果与现有算法相比能够更容易找到最小约简
所需时间较短.
In order to obtain the minimal reduction of decision table attributes
an attribute reduction algorithm is proposed based on ant colony optimization. The significance of attributes defined from the viewpoint of information theory is used as the heuristic information. The algorithm directly imports the core into each solution constructed by ants and reduces the problem scale. The new state transition rule and pheromone updating rule reflects the orderless characteristic among attributes
and benefits the search in the neighborhood of good solutions. The algorithm is verified on nine typical instances. Experimental results show that
compared with the existing algorithms
the proposed algorithm can find the minimal reduction more easily with less time.
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