A simulated annealing algorithm with a dual perturbation method for clustering

•Existing partitional clustering algorithms still settle upon local optima.•We propose a new simulated annealing algorithm with two perturbation methods.•We compare our algorithm with existing simulated annealing clustering algorithms.•We show our new algorithm produces clusters of higher quality mo...

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Bibliographic Details

Published in:	Pattern recognition Vol. 112; p. 107713
Main Authors:	Lee, Julian, Perkins, David
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.04.2021
Subjects:	K-means Partitional clustering Simulated annealing Sum of squared error criterion K-means Sum of squared error criterion Partitional clustering Simulated annealing
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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