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Direct Heuristic Algorithms of Possibilistic Clustering Based on Transitive Approximation of Fuzzy Tolerance

Listed author(s):
  • Dmitri A. VIATTCHENIN

    ()

  • Aliaksandr DAMARATSKI

    ()

Registered author(s):

    This paper deals with the problem of a heuristic approach to possibilistic clustering. The approach is based on the concept of allotment among fuzzy clusters. The paper provides the description of basic concepts of the heuristic approach to possibilistic clustering. Plans of direct prototype-based heuristic algorithms of possibilistic clustering based on a transitive approximation of a fuzzy tolerance are described in detail. An illustrative example of application of the basic version of the proposed algorithms to Sneath and Sokal's two- dimensional data set is considered. Preliminary conclusions are formulated.

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    Article provided by Academy of Economic Studies - Bucharest, Romania in its journal Informatica Economica.

    Volume (Year): 17 (2013)
    Issue (Month): 3 ()
    Pages: 5-15

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    Handle: RePEc:aes:infoec:v:17:y:2013:i:3:p:5-15
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