DocumentCode
2102872
Title
A New Hybrid Ant Colony Algorithm for Clustering Problem
Author
Shang, Gao
Author_Institution
Sch. of Comput. Sci. & Eng., Jiangsu Univ. of Sci. & Technol., Zhenjiang
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
28
Lastpage
31
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
combinatorial mathematics; pattern clustering; simulated annealing; clustering problem; hybrid ant colony algorithm; k-means algorithm; mathematical model; simulated annealing algorithm; Algorithm design and analysis; Clustering algorithms; Cooling; Crystalline materials; Crystals; Information technology; Mathematical model; Simulated annealing; Solid modeling; Temperature; ant colony algorithm; clustering problems; simulated annealing algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3505-0
Type
conf
DOI
10.1109/IITA.Workshops.2008.257
Filename
4731873
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