By Topic

The designing methodology of extenics-based fuzzy reasoning model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yo-Ping Huang ; Dept. of Comput. Sci. & Inf. Eng., Dayeh Univ., Changhwa, Taiwan ; Hung-Jin Chen

A novel extenics-based fuzzy modeling method, which differs from the traditional fuzzy inference, is proposed. In the parameter identification process, adjusting a membership function to satisfy one pattern may deteriorate the others' performance and result in a lengthy tuning process. This incompatible issue is solved by extension theory. We investigate how to define the extended relational functions and how to refine the roughly designed model to meet the system requirement. During the refining process, both the fired and the neighborhood of the fired membership functions are adjusted. On the basis of the gradient descent method, the parameters used to define the extended relational functions and fuzzy rules can be systematically adjusted. We also use the transformation technique to simplify fuzzy modeling. Simulation results from models of single-input single-output, double-input single-output and sigmoidal transformation functions verified that better results than the conventional methods have been obtained

Published in:

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on  (Volume:3 )

Date of Conference:

1999