Title: An Improved Hybrid Genetic Clustering Algorithm
Abstract: In this paper, a new genetic clustering algorithm called IHGA-clustering is proposed to deal with the clustering problem under the criterion of minimum sum of squares clustering. In IHGA-clustering, DHB operation is developed to improve the individual and accelerate the convergence speed, and partition-mergence mutation operation is designed to reassign objects among different clusters. Equipped with these two components, IHGA-clustering can stably output the proper result. Its superiority over HGA-clustering, GKA, and KGA-clustering is extensively demonstrated for experimental data sets.
Publication Year: 2006
Publication Date: 2006-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 3
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