Exploring Constrained Type-2 fuzzy sets

D’Alterio, Pasquale; Garibaldi, Jonathan M.; Pourabdollah, Amir

Abstract

Fuzzy logic has been widely used to model human reasoning thanks to its inherent capability of handling uncertainty. In particular, the introduction of Type-2 fuzzy sets added the possibility of expressing uncertainty even on the definition of the membership functions. Type-2 sets, however, don’t pose any restrictions on the continuity or convexity of their embedded sets while these properties may be desirable in certain contexts. To overcome this problem, Constrained Type-2 fuzzy sets have been proposed. In this paper, we focus on Interval Constrained Type-2 sets to see how their unique structure can be exploited to build a new inference process. This will set some ground work for future developments, such as the design of a new defuzzification process for Constrained Type-2 fuzzy systems.

Citation

D’Alterio, P., Garibaldi, J. M., & Pourabdollah, A. Exploring Constrained Type-2 fuzzy sets. Presented at 2018 IEEE World Congress on Computational Intelligence (WCCI 2018)

• Conference Name: 2018 IEEE World Congress on Computational Intelligence (WCCI 2018)
• End Date: Jul 13, 2018
• Acceptance Date: Jun 30, 2018
• Publication Date: Jul 8, 2018
• Deposit Date: Jul 4, 2018
• Publicly Available Date: Jul 8, 2018
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/945786
• Contract Date: Jul 4, 2018