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

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Novel Developments in Uncertainty Representation and Processing

Part of the book series: Advances in Intelligent Systems and Computing ((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.

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References

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Acknowledgements

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

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Authors and Affiliations

  1. Systems Research Institute Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk & Jan W. Owsiński

  2. Department of Software Information Technology, Belarusian State University of Informatics and Radio-Electronics, Minsk, Belarus

    Dmitri A. Viattchenin & Stanislau Shyrai

Authors
  1. Janusz Kacprzyk
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  2. Jan W. Owsiński
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  3. Dmitri A. Viattchenin
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  4. Stanislau Shyrai
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Corresponding author

Correspondence to Janusz Kacprzyk .

Editor information

Editors and Affiliations

  1. Inst. of Biophy. & Biomedical Eng., Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

  2. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Sys Res Intit of Polish Acad of Science, Intelligent Systems Laboratory, Warsaw, Poland

    Janusz Kacprzyk

  4. Warsaw School of Information Technology, Polish Academy of Sciences, Warsaw, Poland

    Maciej Krawczak

  5. Div of Gdu Stud,CalzTecn sn,Fra.TomAqu, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  6. Intelligent Systems Laboratory, Asen Zlatarov University, Bourgas, Bulgaria

    Sotir Sotirov

  7. Intelligent Systems Laboratory, “Prof. Dr. Asen Zlatarov” University, Burgas, Bulgaria

    Evdokia Sotirova

  8. Systems Research Institute, Polish Academy of Sciences, Warszawa, Poland

    Eulalia Szmidt

  9. Dept. of Tele. & Info. Processing, Ghent University, Gent, Belgium

    Guy De Tré

  10. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

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Kacprzyk, J., Owsiński, J.W., Viattchenin, D.A., Shyrai, S. (2016). A New Heuristic Algorithm of Possibilistic Clustering Based on Intuitionistic Fuzzy Relations. In: Atanassov, K., et al. Novel Developments in Uncertainty Representation and Processing. Advances in Intelligent Systems and Computing, vol 401. Springer, Cham. https://doi.org/10.1007/978-3-319-26211-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-26211-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26210-9

  • Online ISBN: 978-3-319-26211-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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