The Extension-Based Ant Colony Optimization of Finding Rough Set Reducts

Author

Sujuan, Zhao ; Tao, Zeng ; Yu Yongquan

Author_Institution

Fac. of Comput., Guangdong Univ. of Technol., Guangzhou, China

Volume

3

fYear

2009

fDate

15-17 May 2009

Firstpage

43

Lastpage

45

Abstract

Ant colony algorithm is a simulated evolutionary algorithm, which shows many excellent characters and has succeeded in solving many difficult combinatorial optimization problems. However, it is not perfect now. Inspired by dependent function of extension theory, a new statue transition rule and local updating rule based on dependent function have been presented in this paper. And experimental results show that our algorithm is effective and useful.

Keywords

combinatorial mathematics; evolutionary computation; rough set theory; combinatorial optimization problem; extension theory dependent function; extension-based ant colony optimization; local updating rule; rough set reduct; simulated evolutionary algorithm; statue transition rule; Ant colony optimization; Application software; Computational modeling; Computer simulation; Evolutionary computation; Information technology; Ant colony algorithm; Dependent Function; local updating rule; rough set attributes reductions; statue transition rule;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and Applications, 2009. IFITA '09. International Forum on

Conference_Location

Chengdu

Print_ISBN

978-0-7695-3600-2

Type

conf

DOI

10.1109/IFITA.2009.336

Filename

5232055