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

School of Digital Creation and Animation, Shenzhen Polytechnic, Shenzhen 518055, China
School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
School of Computer Science and Technology, Jiangsu Normal University, Xuzhou 221116, China
Author to whom correspondence should be addressed.
Academic Editor: Javier Del Ser Lorente
Algorithms 2015, 8(4), 951-964;
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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