Title :
Fuzzy rule clustering
Author_Institution :
Departamento das Engenharias, Univ. de Tras-os-Montes e Alto Douro, Quinta dos Prados, Portugal
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;
Conference_Titel :
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-7087-2
DOI :
10.1109/ICSMC.2001.972920
