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Application of Fuzzy Rule Base Design Method
Journal
Handbook of Fuzzy Sets Comparison - Theory, Algorithms and Applications
ISSN
2241-9063
Date Issued
2016
DOI
10.15579/gcsr.vol6.ch7
Abstract
In many classification tasks the final goal is usually to determine classes of objects. The final goal of fuzzy clustering is also the distribution of elements with highest membership functions into classes. The key issue is the possibility of extracting fuzzy rules that describe clustering results. The paper develops a method of fuzzy rule base designing for the numerical data, which enables extracting fuzzy rules in the form IFTHEN. To obtain the membership functions, the fuzzy c-means clustering algorithm is employed. The described methodology of fuzzy rule base designing allows one to classify the data. The practical part contains implementation examples.