From Interval-Valued Data to General Type-2 Fuzzy Sets
- Submitting institution
-
University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1318873
- Type
- D - Journal article
- DOI
-
10.1109/tfuzz.2014.2310734
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- -
- First page
- 248
- Volume
- 23
- Issue
- 2
- ISSN
- 1063-6706
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- 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
-
4
- Research group(s)
-
-
- Citation count
- 50
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper provides a completely novel approach to generating (fuzzy set) models from uncertain, interval-valued data. The approach enables efficient 'lossless' computation and systematic simultaneous representation of both intra- and inter-source uncertainty (uncertainty among experts and between experts) using this specific class of fuzzy set (general type-2 fuzzy sets). This approach is unique in the field, in avoiding outlier removal, using a 'non-parametric' approach, and not requiring assumptions such the selection of a predefined (e.g. Gaussian) model of the underlying data. Indirectly, the work led to EP/P011918/1 "Leveraging the Multi-Stakeholder Nature of Cyber Security" (GBP770k) and on-going research.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
