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Decomposition theorems and extension principles for hesitant fuzzy sets
BORDA Research Unit and Multidisciplinary Institute of Enterprise (IME), University of Salamanca, Salamanca, Spain.
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0002-0368-8037
2018 (Engelska)Ingår i: Information Fusion, ISSN 1566-2535, E-ISSN 1872-6305, Vol. 41, s. 48-56Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

We prove a decomposition theorem for hesitant fuzzy sets, which states that every typical hesitant fuzzy set on a set can be represented by a well-structured family of fuzzy sets on that set. This decomposition is expressed by the novel concept of hesitant fuzzy set associated with a family of hesitant fuzzy sets, in terms of newly defined families of their cuts. Our result supposes the first representation theorem of hesitant fuzzy sets in the literature. Other related representation results are proven. We also define two novel extension principles that extend crisp functions to functions that map hesitant fuzzy sets into hesitant fuzzy sets.

Ort, förlag, år, upplaga, sidor
Elsevier, 2018. Vol. 41, s. 48-56
Nyckelord [en]
Hesitant fuzzy set, Cut set, Decomposition theorem, Representation theorem, Extension principle
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifikatorer
URN: urn:nbn:se:his:diva-14605DOI: 10.1016/j.inffus.2017.08.005ISI: 000417662100006Scopus ID: 2-s2.0-85027534671OAI: oai:DiVA.org:his-14605DiVA, id: diva2:1169548
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Tillgänglig från: 2017-12-28 Skapad: 2017-12-28 Senast uppdaterad: 2021-01-05Bibliografiskt granskad

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Torra, Vicenç

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