Constrained interval type-2 fuzzy sets
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11 - 1287294
- Type
- D - Journal article
- DOI
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10.1109/tfuzz.2020.2970911
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- -
- First page
- 00
- Volume
- 00
- Issue
- -
- ISSN
- 1063-6706
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
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A - Computing and Informatics Research Centre
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- As a collaboration between NTU and University of Nottingham, this paper presents a new concept of constrained type-2 fuzzy sets (CT2FS). The significance of this paper is it is the first in fully covering the CT2FS theory, operations and applications. Since early 2020, it has led to follow-up studies in developing Explainable AI (XAI) (https://doi.org/10.1109/FUZZ48607.2020.9177671) and software development (https://doi.org/10.1109/FUZZ48607.2020.9177553). The significant inference outperformance of CT2FS compared to other type-2 sets (https://doi.org/10.1109/TFUZZ.2020.3018379) shows the CT2FS future potentials in utilising CT2FS for real-world applications, particularly in uncertain decision-support systems.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
