JSW 2012 Vol.7(11): 2640-2648 ISSN: 1796-217X
doi: 10.4304//jsw.7.11.2640-2648
doi: 10.4304//jsw.7.11.2640-2648
An Attribute Reduction Algorithm Based on Genetic Algorithm and Discernibility Matrix
Wu Zhengjiang, Zhang Jingmin and Gao Yan
School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
Abstract—In order to effectively solve the problem between genetic algorithm convergence and a local optimal solution, this paper presents an attribute reduction algorithm based on genetic algorithm with improved selection operator and discernibility matrix. In the algorithm, from the point of view of granular computing, rough set decision tables based on partition and covering are researched by measuring granularity again. The practical results show that the average convergence generation of modified algorithm is obviously superior to not modified algorithm, which is generally applicable in rough set decision tables based on partition and covering
Index Terms—rough set, genetic algorithm, discernibility matrix, selection operator, attribute reduction
Abstract—In order to effectively solve the problem between genetic algorithm convergence and a local optimal solution, this paper presents an attribute reduction algorithm based on genetic algorithm with improved selection operator and discernibility matrix. In the algorithm, from the point of view of granular computing, rough set decision tables based on partition and covering are researched by measuring granularity again. The practical results show that the average convergence generation of modified algorithm is obviously superior to not modified algorithm, which is generally applicable in rough set decision tables based on partition and covering
Index Terms—rough set, genetic algorithm, discernibility matrix, selection operator, attribute reduction
Cite: Wu Zhengjiang, Zhang Jingmin and Gao Yan, "An Attribute Reduction Algorithm Based on Genetic Algorithm and Discernibility Matrix," Journal of Software vol. 7, no. 11, pp. 2640-2648, 2012.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
-
Mar 01, 2024 News!
Vol 19, No 1 has been published with online version [Click]
-
Jan 04, 2024 News!
JSW will adopt Article-by-Article Work Flow
-
Apr 01, 2024 News!
Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec) [Click]
-
Apr 01, 2024 News!
Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP [Click]
-
Nov 02, 2023 News!
Vol 18, No 4 has been published with online version [Click]