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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

Sažetak

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.

Ključne riječi

fuzzy cluster; fuzzy rule; antecedent; consequent; Gaussian membership function

Hrčak ID:

111883

URI

https://hrcak.srce.hr/111883

Datum izdavanja:

10.12.2013.

Posjeta: 7.597 *