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A New Heuristic Algorithm of Possibilistic Clustering Based on Intuitionistic Fuzzy Relations

  • Janusz KacprzykEmail author
  • Jan W. Owsiński
  • Dmitri A. Viattchenin
  • Stanislau Shyrai
Conference paper
  • 424 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 401)

Abstract

This paper introduces a novel intuitionistic fuzzy set-based heuristic algorithm of possibilistic clustering. For the purpose, some remarks on the fuzzy approach to clustering are discussed and a brief review of intuitionistic fuzzy set-based clustering procedures is given, basic concepts of the intuitionistic fuzzy set theory and the intuitionistic fuzzy generalization of the heuristic approach to possibilistic clustering are considered, a general plan of the proposed clustering procedure is described in detail, two illustrative examples confirm good performance of the proposed algorithm, and some preliminary conclusions are formulated.

Keywords

Intuitionistic fuzzy set Intuitionistic fuzzy tolerance Similarity measure Clustering 

Notes

Acknowledgements

The authors are grateful to Prof. Eulalia Szmidt for her useful remarks and fruitful discussions during the paper preparation.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Janusz Kacprzyk
    • 1
    Email author
  • Jan W. Owsiński
    • 1
  • Dmitri A. Viattchenin
    • 2
  • Stanislau Shyrai
    • 2
  1. 1.Systems Research Institute Polish Academy of SciencesWarsawPoland
  2. 2.Department of Software Information Technology, Belarusian State University of Informatics and Radio-ElectronicsMinskBelarus

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