A New Hybrid Ant Colony Algorithm for Clustering Problem

Author

Shang, Gao ; Zaiyue, Zhang ; Xiaoru, Zhang ; Cungen, Cao

Author_Institution

Sch. of Comput. Sci. & Eng., Jiangsu Univ. of Sci. & Technol., Zhenjiang

Volume

1

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

645

Lastpage

648

Abstract

The known mathematical model for clustering problems is given in this paper. With the K-Means algorithm, the simulated annealing algorithm and a novel hybrid ant colony algorithm is integrated with the K-means algorithm to solve clustering problems. The advantages and shortages of K-Means algorithm, simulated annealing algorithm and the hybrid ant colony algorithm are then analyzed, so that effectiveness of the hybrid ant colony algorithm would be illustrated through results.

Keywords

pattern clustering; simulated annealing; K-means algorithm; ant colony algorithm; clustering problem; mathematical model; simulated annealing algorithm; Algorithm design and analysis; Ant colony optimization; Clustering algorithms; Computer science education; Distributed computing; Educational technology; Feedback; Iterative algorithms; Mathematical model; Simulated annealing; ant colony algorithm; clustering problems; simulated annealing algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3563-0

Type

conf

DOI

10.1109/ETTandGRS.2008.314

Filename

5070239