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Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
- 1.0559701 - ÚTIA 2023 RIV NL eng J - Journal Article
Asmus, T. C. - Dimuro, G. P. - Bedregal, B. - Sanz, J. A. - Mesiar, Radko - Bustince, H.
Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions.
Fuzzy Sets and Systems. Roč. 441, č. 1 (2022), s. 130-168. ISSN 0165-0114. E-ISSN 1872-6801
Institutional support: RVO:67985556
Keywords : Aggregation functions * Overlap functions * Interval-valued aggregation functions * Interval-valued overlap functions * Admissible orders
OECD category: Applied mathematics
Impact factor: 3.9, year: 2022
Method of publishing: Limited access
http://library.utia.cas.cz/separaty/2022/E/mesiar-0559701.pdf https://www.sciencedirect.com/science/article/pii/S0165011421003353?via%3Dihub
Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. They have been successfully applied as a fuzzy conjunction operation in several problems in which associativity is not required, such as image processing and classification. Interval-valued overlap functions were defined as an extension to express the overlapping of interval valued data, and they have been usually applied when there is uncertainty regarding the assignment of membership degrees, as in interval-valued fuzzy rule-based classification systems. In this context, the choice of a total order for intervals can be significant, which motivated the recent developments on interval-valued aggregation functions and interval-valued overlap functions that are increasing to a given admissible order, that is, a total order that refines the usual partial order for intervals. Also, width preservation has been considered on these recent works, in an intent to avoid the uncertainty increase and guarantee the information quality, but no deeper study was made regarding the relation between the widths of the input intervals and the output interval, when applying interval-valued functions, or how one can control such uncertainty propagation based on this relation.
Permanent Link: https://hdl.handle.net/11104/0333422
Number of the records: 1