Exploring Constrained Type-2 fuzzy sets

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 po...

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Main Authors: D’Alterio, Pasquale, Garibaldi, Jonathan M., Pourabdollah, Amir
Format: Conference or Workshop Item
Published: 2018
Online Access:https://eprints.nottingham.ac.uk/52775/
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author D’Alterio, Pasquale
Garibaldi, Jonathan M.
Pourabdollah, Amir
author_facet D’Alterio, Pasquale
Garibaldi, Jonathan M.
Pourabdollah, Amir
author_sort D’Alterio, Pasquale
building Nottingham Research Data Repository
collection Online Access
description 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.
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format Conference or Workshop Item
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institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T20:25:38Z
publishDate 2018
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spelling nottingham-527752020-05-04T19:45:37Z https://eprints.nottingham.ac.uk/52775/ Exploring Constrained Type-2 fuzzy sets D’Alterio, Pasquale Garibaldi, Jonathan M. Pourabdollah, Amir 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. 2018-07-08 Conference or Workshop Item PeerReviewed D’Alterio, Pasquale, Garibaldi, Jonathan M. and Pourabdollah, Amir (2018) Exploring Constrained Type-2 fuzzy sets. In: 2018 IEEE World Congress on Computational Intelligence (WCCI 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
spellingShingle D’Alterio, Pasquale
Garibaldi, Jonathan M.
Pourabdollah, Amir
Exploring Constrained Type-2 fuzzy sets
title Exploring Constrained Type-2 fuzzy sets
title_full Exploring Constrained Type-2 fuzzy sets
title_fullStr Exploring Constrained Type-2 fuzzy sets
title_full_unstemmed Exploring Constrained Type-2 fuzzy sets
title_short Exploring Constrained Type-2 fuzzy sets
title_sort exploring constrained type-2 fuzzy sets
url https://eprints.nottingham.ac.uk/52775/