Conference Proceeding

T-S fuzzy modeling by FCRM clustering

Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
11/2005; DOI:10.1109/ICSMC.2005.1571584 ISBN: 0-7803-9298-1 pp.2861 - 2866 Vol. 3 In proceeding of: Systems, Man and Cybernetics, 2005 IEEE International Conference on, Volume: 3
Source: IEEE Xplore

ABSTRACT This paper presents an algorithm to establish the T-S fuzzy model. The algorithm using fuzzy C-regression models (FCRM) clustering to find the functional relationships in the product space of the input-output data. We propose a novel cluster validity criterion to calculate overall compactness and separateness of the FCRM results and then determine an appropriate number of regression Junctions. Besides, the repartition of overlapped antecedent fuzzy set is considered. Thus, an efficient T-S fuzzy model with fewer IF-THEN rules can be generated systematically. A simulation example is provided to demonstrate the accuracy and effectiveness of our algorithm.

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Keywords

appropriate number
 
calculate
 
efficient T-S fuzzy model
 
FCRM
 
FCRM results
 
functional relationships
 
fuzzy C-regression models
 
novel cluster validity criterion
 
overlapped antecedent fuzzy
 
product space
 
regression Junctions
 
T-S fuzzy model