Abstract
A new tabu clustering method called ITCA is developed for the minimum sum of squares clustering problem, where DHB operation and mergence and partition operation are introduced to fine-tune the current solution and create the neighborhood, respectively. Compared with some known clustering methods, ITCA can obtain better performance, which is extensively demonstrated by experimental simulations. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Liu, Y., Zheng, D., Li, S., Wang, L., & Chen, K. (2005). A tabu clustering method with DHB operation and mergence and partition operation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3735 LNAI, pp. 380–382). https://doi.org/10.1007/11563983_36
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