• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 人工智能与数据挖掘 • 上一篇    下一篇

利用蚁群优化算法的粗糙集属性约简方法

吴尚智1,张文超2,佘志用1,张霞1,段超1   

  1. (1.西北师范大学计算机科学与工程学院 甘肃 兰州 730070;
    2.烟台黄金职业学院,山东 烟台 265401)
  • 收稿日期:2017-11-08 修回日期:2018-05-29 出版日期:2019-03-25 发布日期:2019-03-25
  • 基金资助:

    国家自然科学基金(61561043);甘肃省自然科学基金(1010RJZA011)

A rough set attribute reduction method
using ant colony optimization algorithm

WU Shangzhi1,ZHANG Wenchao2,SHE Zhiyong1,ZHANG Xia1,DUAN Chao1   

  1. (1.College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070;
    2.Yantai Gold College,Yantai 265401,China)

     
  • Received:2017-11-08 Revised:2018-05-29 Online:2019-03-25 Published:2019-03-25

摘要:

随着高维数据的扩散,特征选择成为学习过程中不可或缺的一项任务。属性约简是特征选择的重要方法,为了寻找有效的属性约简方法,将粗糙集与蚁群算法相结合,提出了利用蚁群优化算法的粗糙集属性约简方法。首先从信息素的更新开始,限制其信息素值的上、下限范围,然后根据寻址方式改进候选解的构造方案。实验表明,该方法具有一定的优越性。

关键词: 粗糙集, 蚁群算法, 属性约简, 信息素

Abstract:

With the proliferation of highdimensional data, feature selection has become an indispensable task in the learning process. Attribute reduction is an important feature selection method. To find effective attribute reduction, combining rough set with the ant colony algorithm, we propose a rough set attribute reduction method using the ant colony optimization algorithm. The method firstly updates pheromones, and sets the upper and lower limits for pheromone values. Then the construction scheme of candidate solution is improved according to the addressing mode. Experimental results show that the method has good superiority.

 

Key words: rough set, ant colony algorithm, attribute reduction, pheromone