Original scientific paper
Designing Gaussian Membership Functions for Fuzzy Classifier Generated by Heuristic Possibilistic Clustering
Dmitri A. Viattchenin
; United Institute of Informatics Problems, National Academy of Science of Belarus, Minsk, Belarus
Reyhane Tati
; Department of Computer, Islamic Azad University, Doroud Branch, Lorestan, Iran
Aliaksandr Damaratski
; United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Belarus
Abstract
The paper deals with the problem of constructing Gaussian membership functions of fuzzy sets for fuzzy rules derived from the data by using heuristic algorithms of possibilistic clustering. Basic concepts of the heuristic approach to possibilistic clustering are reminded and the extended technique of constructing membership functions of fuzzy sets is proposed. An illustrative example is given and preliminary conclusions are made.
Keywords
fuzzy cluster; fuzzy rule; antecedent; consequent; Gaussian membership function
Hrčak ID:
111883
URI
Publication date:
10.12.2013.
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