A Heuristic Approach to Possibilistic Clustering for Fuzzy Data

  • Dmitri A. Viattchenin Senior Researcher
Keywords: possibilistic clustering, fuzzy tolerance, allotment among fuzzy clusters, typical point, vector of fuzzy numbers


The paper deals with the problem of the fuzzy data clustering. In other words, objects attributes can be represented by fuzzy numbers or fuzzy intervals. A direct algorithm of possibilistic clustering is the basis of an approach to the fuzzy data clustering. The paper provides the basic ideas of the method of clustering and a plan of the direct possibilistic clustering algorithm. Definitions of fuzzy intervals and fuzzy numbers are presented and distances for fuzzy numbers are considered. A concept of a vector of fuzzy numbers is introduced and the fuzzy data preprocessing methodology for constructing of a fuzzy tolerance matrix is described. A numerical example is given and results of application of the direct possibilistic clustering algorithm to a set of vectors of triangular fuzzy numbers are considered in the example. Some preliminary conclusions are stated.

Author Biography

Dmitri A. Viattchenin, Senior Researcher
Laboratory of Image Recognition and Processing