Constrained interval type-2 fuzzy sets

D'Alterio, P., Garibaldi, J.M., John, R.I. and Pourabdollah, A. ORCID: 0000-0001-7737-1393, 2020. Constrained interval type-2 fuzzy sets. IEEE Transactions on Fuzzy Systems. ISSN 1063-6706

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Abstract

In many contexts, type-2 fuzzy sets are obtained from a type-1 fuzzy set to which we wish to add uncertainty. However, in the current type-2 representation there is no restriction on the shape of the footprint of uncertainty and the embedded sets that can be considered acceptable. This leads, usually, to the loss of the semantic relationship between the type-2 fuzzy set and the concept it models. As a consequence, the interpretability of some of the embedded sets and the explainability of the uncertainty measures obtained from them can decrease. To overcome these issues, constrained type-2 fuzzy sets have been proposed. However, no formal definitions for some of their key components (e.g. acceptable embedded sets) and constrained operations have been given. The goal of this paper is to provide some theoretical underpinning for the definition of constrained type-2 sets, their inferencing and defuzzification method. To conclude, the constrained inference framework is presented, applied to two real world cases and briefly compared to the standard interval type-2 inference and defuzzification method.

Item Type: Journal article
Publication Title: IEEE Transactions on Fuzzy Systems
Creators: D'Alterio, P., Garibaldi, J.M., John, R.I. and Pourabdollah, A.
Publisher: Institute of Electrical and Electronics Engineers
Date: 31 January 2020
ISSN: 1063-6706
Identifiers:
NumberType
10.1109/tfuzz.2020.2970911DOI
1287288Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 05 Feb 2020 09:45
Last Modified: 05 Feb 2020 09:45
URI: http://irep.ntu.ac.uk/id/eprint/39166

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