Abstract: The so called “Plural Uncertainty Model” is considered, in which statistical, maxmin, interval and Fuzzy model of uncertainty are embedded. For the last case external and internal contradictions of the theory are investigated and the modified definition of the Fuzzy Sets is proposed to overcome the troubles of the classical variant of Fuzzy Subsets by L. Zadeh. The general variants of logit- and probit- regression are the model of the modified Fuzzy Sets. It is possible to say about observations within the modification of the theory. The conception of the “situation” is proposed within modified Fuzzy Theory and the classifying problem is considered. The algorithm of the classification for the situation is proposed being the analogue of the statistical MLM(maximum likelihood method). The example related possible observing the distribution from the collection of distribution is considered

Keywords: Uncertainty, Fuzzy subset, membership function, classification, clusterization.

ACM Classification keywords: I.5.1.Pattern Recognition: Models Fuzzy sets; G.3. Probability and Statistics: Stochastic processes; H.1.m. Models and Principles: miscellaneous

Link:

UNCERTAINTY AND FUZZY SETS: CLASSIFYING THE SITUATION

Volodymyr Donchenko

http://www.foibg.com/ijita/vol14/ijita14-1-p08.pdf