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dc.contributor.author | Llamazares Rodríguez, Bonifacio | |
dc.date.accessioned | 2019-06-08T04:20:19Z | |
dc.date.available | 2019-06-08T04:20:19Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | International Journal of Intelligent Systems, 2019, vol. 34, n. 5, p. 790-818. | es |
dc.identifier.issn | 1098-111X | es |
dc.identifier.uri | http://uvadoc.uva.es/handle/10324/36220 | |
dc.description | Producción Científica | es |
dc.description.abstract | SUOWA operators are a particular case of Choquet integral that simultaneously generalize weighted means and OWA operators. Because they are constructed by using normalized capacities, they possess properties such as continuity, monotonicity, idempotency, compensativeness, and homogeneity of degree 1. Besides these ones, some articles published in recent years have shown that SUOWA operators also exhibit other interesting properties. So, we think that the time has come to summarize existing knowledge of these operators. The aim of this paper is to collect the main results obtained so far on SUOWA operators. Moreover, we also introduce some new results and illustrate the usefulness of SUOWA operators by using an example given by Beliakov (2018). | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | spa | es |
dc.publisher | Wiley | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.subject.classification | SUOWA operators | es |
dc.subject.classification | Choquet integral | es |
dc.title | SUOWA operators: A review of the state of the art | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | 10.1002/int.22076 | es |
dc.relation.publisherversion | https://onlinelibrary.wiley.com/doi/abs/10.1002/int.22076 | es |
dc.identifier.publicationfirstpage | 790 | es |
dc.identifier.publicationissue | 5 | es |
dc.identifier.publicationlastpage | 818 | es |
dc.identifier.publicationtitle | International Journal of Intelligent Systems | es |
dc.identifier.publicationvolume | 34 | es |
dc.peerreviewed | SI | es |
dc.description.project | MEC-FEDER Grant ECO2016‐77900‐P | es |