Title :
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
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;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5362760