A New Approach for Transformation-Based Fuzzy Rule Interpolation
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 30593761
- Type
- D - Journal article
- DOI
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10.1109/TFUZZ.2019.2949767
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- -
- 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
-
4
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First paper to improve the automation level of fuzzy rule interpolation in a data-driven manner. IEEE TFS is one of the top-rated outlets across all areas of computer science and informatics (JCR-Clarivate). This paper is selected by IEEE Computational Intelligence Society as one of the two TFS Publication Spotlight articles, recommended by the editors as introduced in the 2021 May issue of IEEE Computational Intelligence Magazine.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -