DocumentCode
2051625
Title
Genetic fuzzy clustering for the definition of fuzzy sets
Author
Velasco, Juan R. ; López, Sergio ; Magdalena, Luis
Author_Institution
ETSI Telecomunicacion, Univ. Politecnica de Madrid, Spain
Volume
3
fYear
1997
fDate
1-5 Jul 1997
Firstpage
1665
Abstract
This paper presents a new algorithm for fuzzy clustering applied to the definition of fuzzy sets. The aim of this algorithm is to obtain a good fuzzy partition for a given variable. It will use a historic data file as input and uses genetic algorithms to evolve a population of fuzzy sets in order to obtain the best fuzzy partition. The main advantage of this algorithm is that it does not need previous knowledge on the number of fuzzy sets. This number is inferred by the algorithm itself. At the end of this paper, some results on real industrial data are presented
Keywords
fuzzy set theory; genetic algorithms; pattern classification; fuzzy partition; fuzzy sets; genetic fuzzy clustering; historic data file; Clustering algorithms; Clustering methods; Fuzzy control; Fuzzy sets; Genetic algorithms; Input variables; Iterative algorithms; Partitioning algorithms; Proposals; Telecommunications;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location
Barcelona
Print_ISBN
0-7803-3796-4
Type
conf
DOI
10.1109/FUZZY.1997.619790
Filename
619790
Link To Document