By Topic

A multi-objective approach to design of interval type-2 fuzzy logic systems

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

1 Author(s)
Rezaee, B. ; Dept. of Ind. Eng., Bojnord Univ., Bojnord, Iran

One of the main advantages of interval type-2 fuzzy logic systems is their ability to produce prediction intervals as a by-product of the type reduction process. This is especially useful for the design of interval type-2 fuzzy logic systems, where the data are corrupted by noise, in such cases; a model that provides a granular output is more appreciable. Nevertheless, the methods have been proposed in the literature to design type-2 fuzzy logic systems only focused on optimizing a final performance measure, i.e., minimizing error of crisp output of system. This paper presents a multi-objective approach to derive interval type-2 fuzzy logic system used as predictive systems, in which there are three objective functions, such as minimization of the crisp output error and interval output errors. To assess the potentiality of the approach, it has been applied to two synthetic datasets showing very promising results. The results show that the proposed multi-objective outperforms single-objective approach in terms of the crisp and interval output quality.

Published in:

Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on

Date of Conference:

10-15 June 2012