Fuzzy rule clustering

Author

Salgado, Paulo

Author_Institution

Departamento das Engenharias, Univ. de Tras-os-Montes e Alto Douro, Quinta dos Prados, Portugal

Volume

4

fYear

2001

fDate

2001

Firstpage

2421

Abstract

The concept of relevance has been proposed as a measure of the relative importance of sets of rules, allowing the development of a new methodology for organising the linguistic information: SLIM (Separation of Linguistic Information Methodology). Based on this concept and on this methodology, a new fuzzy clustering of fuzzy rules algorithm (FCFRA) is proposed and applied to organise fuzzy IF ... THEN rules. The proposed FCFRA algorithm has been successfully applied to illustrate a segmentation operation in the "fuzzy rules domain", using the Abington Cross image

Keywords

fuzzy systems; identification; image segmentation; nonlinear systems; pattern clustering; uncertainty handling; Abington Cross image; FCFRA; Fuzzy Clustering of Fuzzy Rules Algorithm; SLIM; Separation of Linguistic Information Methodology; complex nonlinear relations; function approximation; fuzzy IF... THEN rules; fuzzy rule clustering; fuzzy systems; hierarchical fuzzy model; linguistic information; pattern recognition; relevance; segmentation; similarity measure; universal approximator functions; Clustering algorithms; Data mining; Data processing; Function approximation; Fuzzy sets; Fuzzy systems; Image segmentation; Inference mechanisms; Pattern recognition; Personal communication networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2001 IEEE International Conference on

Conference_Location

Tucson, AZ

ISSN

1062-922X

Print_ISBN

0-7803-7087-2

Type

conf

DOI

10.1109/ICSMC.2001.972920

Filename

972920