Improved Uncertainty Capture for Nonsingleton Fuzzy Systems
- Submitting institution
-
University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1318906
- Type
- D - Journal article
- DOI
-
10.1109/TFUZZ.2016.2540065
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- -
- First page
- 1513
- Volume
- 24
- Issue
- 6
- ISSN
- 1063-6706
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- 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)
-
-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper addresses a long-standing status quo in fuzzy systems and enables substantially improved modelling and inference performance. The contribution focuses on further developing the actual mathematical underpinnings of the non-singleton inference in fuzzy systems. This in turn enables resulting systems to more closely model uncertainty in system inputs, resulting in better performance. Importantly, the paper's contribution is highly generic, applicable to all non-singleton fuzzy systems and provides a fresh approach to an area which otherwise has seen little progress in recent years.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
