摘要
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.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2008年第4期440-444,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(60475023)
教育部高等学校博士学科点专项科研基金资助项目(20050698023)
关键词
蚁群优化
决策表
属性约简
ant colony optimization
decision table
attribute reduction
