Research on Fuzzy Data Mining Based on MAX-MIN Ant System

Author

Lin, Xiaowei ; Jia, Hongyu ; Song, Cuicui

Author_Institution

Sch. of Transp. Manage., Dalian Maritime Univ., Dalian, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

The application of intelligent optimization algorithm in data mining has become widespread already. However, it´s still a brand new research area in the application of Ant Colony Algorithm(ACA) in data mining. This paper thus proposes a fuzzy data mining algorithm which is based on MAX-MIN Ant System(MMAS). In this algorithm, the membership functions which are extracted from the classification rule are first encoded into binary bits and then imported to the MMAS to obtained the final set of membership functions, finally, this set was used to mine fuzzy association rule from the database by fuzzy mining algorithm. A numerical experiment is given to demonstrate the effectiveness of this algorithm.

Keywords

data mining; fuzzy set theory; optimisation; MAX-MIN ant system; ant colony algorithm; classification rule; fuzzy association rule; fuzzy data mining; fuzzy set; intelligent optimization algorithm; membership functions; Ant colony optimization; Association rules; Clustering algorithms; Data mining; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Itemsets; Transaction databases; Transportation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5362760

Filename

5362760