A Fuzzy C-means Type Clustering Algorithm on Triangular Fuzzy Numbers

  • Authors:
  • Rong Lan;Jiu-lun Fan

  • Affiliations:
  • -;-

  • Venue:
  • FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
  • Year:
  • 2009
  • Vector fuzzy C-means

    Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning

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Abstract

Fuzzy number type data is a typical class of fuzzy data, and it can be regarded as a general form of the interval data and the crisp data. This paper studies fuzzy clustering algorithm for triangular fuzzy numbers. First of all, we give a novel distance between triangular fuzzy numbers by using three parameters interval number, and prove that the proposed distance is a complete metric on the set of triangular fuzzy numbers. And then, based on this novel distance, we propose two fuzzy c-means type clustering algorithms for dealing with triangular fuzzy numbers. Finally, some numerical examples are provided to illustrate the algorithm’s effectiveness.