Pasquale D’Alterio
Exploring Constrained Type-2 fuzzy sets
D’Alterio, Pasquale; Garibaldi, Jonathan M.; Pourabdollah, Amir
Authors
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) |
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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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