A New Approach for Transformation-based Fuzzy Rule Interpolation
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6
- Type
- D - Journal article
- DOI
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10.1109/TFUZZ.2019.2949767
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- 8886596
- First page
- 3330
- Volume
- 28
- Issue
- 12
- ISSN
- 1063-6706
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2019
- 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
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4
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in a Scimago Q1/ ERA2010 A* top-ranked IEEE journal, this is the first paper showing how to improve the automation of fuzzy rule interpolation (FRI) in a data-driven manner, making the interpolation process more robust and free of human intervention. This paper was selected by IEEE Computational Intelligence Society as one of the two TFS Publication Spotlight articles, as introduced in the 2021 May issue of IEEE Computational Intelligence Magazine. It led to one of the authors (Shen) giving a keynote speech “Transformation-based Fuzzy Rule Interpolation and its applications” at the World Congress on Computational Intelligence 2020 https://wcci2020.org/speaker/qiang-shen/.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -