• DocumentCode
    230148
  • Title

    Multi-central general fuzzy clustering model

  • Author

    Mohamadi Golsefid, Samira Malek ; Zarandi, Mohammad Fazel

  • Author_Institution
    Dept. of Ind. Eng., Amirkabir Univ. of Technol., Tehran, Iran
  • fYear
    2014
  • fDate
    24-26 June 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a new model for general fuzzy type-2 clustering called Multi Central General Fuzzy Type-2 Clustering that is an extension of possibilistic c-means (PCM). We mainly focus on uncertainty associated with the cluster centers and define a set of points as the center for each cluster. In our model the degree of belonging is defined as general type-2 fuzzy and there is not any type reduction or defuzzification in the new clustering algorithm. Numerical examples demonstrate the proposed model performance.
  • Keywords
    fuzzy set theory; pattern clustering; possibility theory; PCM; multicentral general fuzzy type-2 clustering; possibilistic c-means; Clustering algorithms; Educational institutions; Fuzzy sets; Industrial engineering; Pattern recognition; Phase change materials; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Norbert Wiener in the 21st Century (21CW), 2014 IEEE Conference on
  • Conference_Location
    Boston, MA
  • Type

    conf

  • DOI
    10.1109/NORBERT.2014.6893905
  • Filename
    6893905