DocumentCode
3145996
Title
An improved ant colony clustering algorithm
Author
Jiang, Hong ; Yu, Qingsong ; Gong, Yu
Author_Institution
Comput. Center, East China Normal Univ., Shanghai, China
Volume
6
fYear
2010
fDate
16-18 Oct. 2010
Firstpage
2368
Lastpage
2372
Abstract
Based on the basic model of ant colony clustering algorithm, LF, an improved ant colony clustering algorithm (IACC) is proposed. The constructing method, the colony similarity, and the behavior of the ant are redefined. A new adaptive parameter adjustment strategy is also presented in this paper. Experimental results on clustering benchmarks indicate that the proposed algorithm has better performance than LF. It overcomes LF´s shortcomings of lower convergence speed and longer iteration cycles.
Keywords
biocybernetics; data mining; particle swarm optimisation; pattern clustering; physiological models; ant colony clustering algorithm; ant colony optimization; artificial swarm intelligence; bionic algorithm; data mining; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Convergence; Data mining; Euclidean distance; Iris; LF algorithm; ant colony algorithm; ant colony clustering algorithm; clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4244-6495-1
Type
conf
DOI
10.1109/BMEI.2010.5639719
Filename
5639719
Link To Document