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  • 标题:An Improved Teaching-Learning Based Optimization Approach for Fuzzy Clustering
  • 本地全文:下载
  • 作者:Parastou Shahsamandi E. ; Soheil Sadi-nezhad
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2014
  • 卷号:4
  • 期号:11
  • 页码:43-50
  • DOI:10.5121/csit.2014.41105
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Fuzzy clustering has been widely studied and applied in a variety of key areas of science andengineering. In this paper the Improved Teaching Learning Based Optimization (ITLBO)algorithm is used for data clustering, in which the objects in the same cluster are similar. Thisalgorithm has been tested on several datasets and compared with some other popular algorithmin clustering. Results have been shown that the proposed method improves the output ofclustering and can be efficiently used for fuzzy clustering.
  • 关键词:Meta-heuristic algorithm; Improved teaching-learning-based optimization; Fuzzy clustering
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