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Volume 21 Issue 3
May  1999
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Pel Jihong, Fan Jiulun, Xie Weixin. A NEW INITIALIZATION METHOD OF CLUSTER CENTERS[J]. Journal of Electronics & Information Technology, 1999, 21(3): 320-325.
Citation: Pel Jihong, Fan Jiulun, Xie Weixin. A NEW INITIALIZATION METHOD OF CLUSTER CENTERS[J]. Journal of Electronics & Information Technology, 1999, 21(3): 320-325.

A NEW INITIALIZATION METHOD OF CLUSTER CENTERS

  • Received Date: 1997-09-11
  • Rev Recd Date: 1998-07-01
  • Publish Date: 1999-05-19
  • The problems of parameter selections for potential function used to initialize cluster centers are discussed, and two methods are given for determining these parameters. Then a new density function to initialize cluster centers is also given which is computational effective. Finally, a set of compared experiments is presented to show the effectiveness of the proposed methods.
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  • Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum, 1981, 43-93.[2]Bezdek J C, Hathaway R, Sabin M, Tucker W. Convergence theory for fuzzy C-means: Coun-[3]terexample and repairs. IEEE Trans. on SMC., 1987, SMC-17(5): 873-877.[4]Yager R R, Filev D P. Approximate clustering via the mountain method. IEEE Trans. on SMC., 1994, SMC-24(8): 1279-1284.[5]Chiu S L. Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems, 1994, 2(3): 267-278.[6]Moser C A, Scott W. British Towns. Edinburgh: Oliver and Boyd, 1961.[7]裴继红.基于模糊信息处理的图像分割方法研究:[博士论文].西安电子科技大学,1998.
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