Title :
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
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;
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
DOI :
10.1109/ETTandGRS.2008.314
