By Topic

Importance sampling based defuzzification for general type-2 fuzzy sets

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)
Linda, O. ; Comput. Sci. Dept., Univ. of Idaho, Idaho Falls, ID, USA ; Manic, M.

General type-2 fuzzy logic systems (T2 FLS) constitute a powerful tool for coping with ubiquitous uncertainty in many engineering applications. However, the immense computational complexity associated with defuzzification of general T2 fuzzy sets still remains an unresolved issue and prohibits its practical use. This paper proposes a novel importance sampling based defuzzification method for general T2 FLS. Here, a subset from the domain of all embedded fuzzy sets is randomly sampled using a specific probability distribution function. The algorithm is compared with the previously published uniform sampling defuzzification method. Experimental results demonstrate that importance sampling substantially reduces the variance of the sampling defuzzification method. Comparison of T2FLS output surfaces showed that smoother and more stable response can be achieved with the proposed importance sampling based defuzzification method.

Published in:

Fuzzy Systems (FUZZ), 2010 IEEE International Conference on

Date of Conference:

18-23 July 2010