Rule base simplification in fuzzy systems by aggregation of inconsistent rules
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11124118
- Type
- D - Journal article
- DOI
-
10.3233/IFS-141418
- Title of journal
- Journal of Intelligent & Fuzzy Systems
- Article number
- IFS1418
- First page
- 1331
- Volume
- 28
- Issue
- 3
- ISSN
- 1064-1246
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- 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
-
2
- Research group(s)
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B - Computational Intelligence
- Citation count
- 10
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Rule inconsistency is typically removed by re-examining the existing or collecting additional data or expert knowledge, which may be time-consuming or even impossible. The proposed novel method uses rule aggregation to resolve inconsistency efficiently and with better performance. The method is widely applicable and has been used by others for modelling control systems, data based spatio-temporal modelling, energy efficiency and fuzzy systems.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -