Back to Search
Start Over
A New Uncertainty Measure of Covering-Based Rough Interval-Valued Intuitionistic Fuzzy Sets
- Source :
- IEEE Access, Vol 7, Pp 53213-53224 (2019)
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Since some existing uncertainty measurement of covering-based rough intuitionistic fuzzy sets (CRIFSs) are unreasonable in some cases, an extended uncertainty measure criterion of CRIFSs is proposed. The discussion of the monotonicity of the criterion is further refined and more in line with the actual problem description. Taken into account this a modified roughness method is introduced, which is an uncertainty measure of CRIFSs satisfying the extended criterion. Furthermore, the criterion is extended to covering-based rough interval-valued intuitionistic fuzzy sets (CRIVIFSs), and the modified roughness method is proposed to measure the uncertainty of CRIVIFSs. Finally, the example is presented to illustrate the application of the modified roughness to attribute reductions. These conclusions provide a theoretical basis for the rationality (or irrationality) of existing uncertainty measures and also promote the application of CRIVIFSs.
- Subjects :
- 0209 industrial biotechnology
General Computer Science
Fuzzy set
Intuitionistic fuzzy
Monotonic function
02 engineering and technology
Measure (mathematics)
covering approximation space
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
Applied mathematics
General Materials Science
Mathematics
Basis (linear algebra)
General Engineering
Covering-based rough intuitionistic fuzzy set (CRIFS)
extended uncertainty measure criterion
attribute reduction
modified roughness
Line (geometry)
Measurement uncertainty
covering-based rough interval-valued intuitionistic fuzzy set (CRIVIFS)
020201 artificial intelligence & image processing
lcsh:Electrical engineering. Electronics. Nuclear engineering
Rough set
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....67d13b7b6f64854e56b7ee6c51e87234