A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy
AbstractAs 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
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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.
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(4):951-964.Chicago/Turabian Style
Li, Zhi-Yong; Yi, Jiao-Hong; Wang, Gai-Ge. 2015. "A New Swarm Intelligence Approach for Clustering Based on Krill Herd with Elitism Strategy." Algorithms 8, no. 4: 951-964.