Ant Colony Optimization Approach to Attribute Reduction Problem

任志刚 1; 冯祖仁 1; 2; 柯良军 1; 2

您当前的位置：

首页 >

文章列表页 >

Ant Colony Optimization Approach to Attribute Reduction Problem

更新时间：2025-12-08

- Ant Colony Optimization Approach to Attribute Reduction Problem
- Vol. 42, Issue 4, Pages: 440-444(2008)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Online First：10 April 2008，
  
  Published：2008
- 稿件说明：
移动端阅览
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.
DOI：

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. DOI：

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.

Abstract

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.

关键词

Keywords

references

PAWLAK Z. Rough sets[J]. International Journal of Computer and Information Science, 1982,11(5):341-356.

PAWLAK Z. Rough set approach to multi-attribute decision analysis [J]. European Journal of Operational Research, 1994, 12(72):443-459.

WONG S K M, ZIARKO W. On optional decision rules in decision tables [J]. Bulletin of Polish Academy of Sciences, 1985, 33(11):693-696.

DORIGO M, MANIEZZO V, COLORNI A. Ant system: optimization by a colony of cooperating agents [J]. IEEE Trans on Systems, Man and Cybernetics: Part B, 1996, 26(1):29-41.

DORIGO M, GAMBARDELLA L M, Ant colony system: A cooperative learning approach to the traveling salesman problem [J]. IEEE Trans on Evolutionary Computation, 1997, 1(1):53-66.

STUTZLE T, HOOS H H. Max-min ant system [J]. Future Generation Computer Systems, 2000, 16(8):889-914.

JENSEN R, SHEN Q. Finding rough set reducts with ant colony optimization [C]//Proceeding of the 2003 UK Workshop on Computational Intelligence. Bristol, UK: University of Bristol, 2003:15-22.

王俊峰,朱庆保.基于蚁群算法的知识约简 [J].南京师范大学学报(工程技术版), 2005, 5(2):50-53.

WANG Junfeng, ZHU Qingbao. A knowledge reduction method based on ant colony algorithm [J]. Journal of Nanjing Normal University(Engineering and Technology), 2005, 5(2):50-53.

周江卫,冯博琴,刘洋.一种新的快速求核算法 [J].西安交通大学学报, 2007, 41(6):688-691.

ZHOU Jiangwei, FENG Boqin, LIU Yang. New algorithm for quick computing core [J]. Journal of Xi'an Jiaotong University, 2007, 41(6):688-691.

杨明.一种基于改进差别矩阵的核增量式更新算法 [J]. 计算机学报, 2006, 29(3): 57-63.

YANG Ming. An incremental updating algorithm of the computation of a core based on the improved discernibility matrix [J]. Chinese Journal of Computers, 2006, 29(3):57-63.

王国胤,于洪,杨大春.基于条件信息熵的决策表约简 [J].计算机学报, 2002, 25(7): 759-766.

WANG Guoyin, YU Hong, YANG Dachun. Decision table reduction based on conditional information entropy [J]. Chinese Journal of Computers, 2002, 25(7):759-766.

ASUNCION A, NEWMAN D J. UCI machine learning repository [ED/OL].(2006-10-28)[2007-04-01]. http://mlearn.ics.uci.edu/MLSummary.html.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Decision Table Simplification Algorithm Based on Attribute Single-Valued Representation and Attribute Core Calculation

A Route Restoration Algorithm for Sensor Network via Ant Colony Optimization

A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing

Efficient Genetic Reduction Algorithm for Rough Sets

An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function

Related Author

华成 1

徐光华 1

李淑智 1

寇晓丽 2

刘三阳 2

郑巍 1

冯博琴 2

Related Institution

School of Mechanical Engineering, Xi'an Jiaotong University

The Second Artillery Engineering Institute

School of Computer Science and Technology, Xidian University

School of Information Engineering, Zhengzhou University

Department of Computer Science and Technology, Xi'an Jiaotong University

⁰