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Open AccessArticle

A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy

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School of Digital Creation and Animation, Shenzhen Polytechnic, Shenzhen 518055, China
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School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
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School of Computer Science and Technology, Jiangsu Normal University, Xuzhou 221116, China
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Author to whom correspondence should be addressed.
Academic Editor: Javier Del Ser Lorente
Algorithms 2015, 8(4), 951-964; https://doi.org/10.3390/a8040951
Received: 4 August 2015 / Revised: 20 September 2015 / Accepted: 15 October 2015 / Published: 22 October 2015
(This article belongs to the Special Issue Clustering Algorithms)
As one of the most popular and well-recognized clustering methods, fuzzy C-means (FCM) clustering algorithm is the basis of other fuzzy clustering analysis methods in theory and application respects. However, FCM algorithm is essentially a local search optimization algorithm. Therefore, sometimes, it may fail to find the global optimum. For the purpose of getting over the disadvantages of FCM algorithm, a new version of the krill herd (KH) algorithm with elitism strategy, called KHE, is proposed to solve the clustering problem. Elitism tragedy has a strong ability of preventing the krill population from degrading. In addition, the well-selected parameters are used in the KHE method instead of originating from nature. Through an array of simulation experiments, the results show that the KHE is indeed a good choice for solving general benchmark problems and fuzzy clustering analyses. View Full-Text
Keywords: clustering; krill herd; elitism strategy; swarm intelligence clustering; krill herd; elitism strategy; swarm intelligence
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Li, Z.-Y.; Yi, J.-H.; Wang, G.-G. A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy. Algorithms 2015, 8, 951-964.

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