A support vector-based interval type-2 fuzzy system

Uslan, V.; Seker, H.; John, Robert

Abstract

In this paper, a new fuzzy regression model that is supported by support vector regression is presented. Type-2 fuzzy systems are able to tackle applications that have significant uncertainty. However general type-2 fuzzy systems are more complex than type-1 fuzzy systems. Support vector machines are similar to fuzzy systems in that they can also model systems that are non-linear in nature. In the proposed model the consequent parameters of type-2 fuzzy rules are learnt using support vector regression and an efficient closed-form type reduction strategy is used to simplify the computations. Support vector regression improved the generalisation performance of the fuzzy rule-based system in which the fuzzy rules were a set of interpretable IF-THEN rules. The performance of the proposed model was demonstrated by conducting case studies for the non-linear system approximation and prediction of chaotic time series. The model yielded promising results and the simulation results are compared to the results published in the area.

Citation

Uslan, V., Seker, H., & John, R. (2014). A support vector-based interval type-2 fuzzy system.

• Conference Name: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• Publication Date: Jul 1, 2014
• Deposit Date: Feb 2, 2015
• Publicly Available Date: Feb 2, 2015
• Peer Reviewed: Peer Reviewed
• Keywords: fuzzy set theory;regression analysis;support vector machines;IF-THEN rules;efficient closed-form type reduction strategy;fuzzy regression model;generalisation performance;nonlinear system approximation;support vector machines;support vector regression;sup
• Public URL: https://nottingham-repository.worktribe.com/output/995538
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6891813
• Additional Information: Published in: 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. ISBN: 978-1-4799-2073-0, pp. 2396-2401, doi: 10.1109/FUZZ-IEEE.2014.6891813