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Exploring Constrained Type-2 fuzzy sets

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

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Authors

Pasquale D’Alterio

Amir Pourabdollah



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. (2018). Exploring Constrained Type-2 fuzzy sets.

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 Mar 28, 2024
Peer Reviewed Peer Reviewed
Public URL https://nottingham-repository.worktribe.com/output/945786

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