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dc.contributor.author | Pedraza Aguilera, Tatiana | es_ES |
dc.contributor.author | Rodríguez López, Jesús | es_ES |
dc.contributor.author | Valero, Óscar | es_ES |
dc.date.accessioned | 2022-07-18T18:05:29Z | |
dc.date.available | 2022-07-18T18:05:29Z | |
dc.date.issued | 2021-12 | es_ES |
dc.identifier.issn | 0020-0255 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/184368 | |
dc.description.abstract | [EN] In the last years fuzzy (quasi-)metrics and indistinguishability operators have been used as a mathematical tool in order to develop appropriate models useful in applied sciences as, for instance, image processing, clustering analysis and multi-criteria decision making. The both aforesaid similarities allow us to fuzzify the crisp notion of equivalence relation when a certain degree of similarity can be only provided between the compared objects. However, the applicability of fuzzy (quasi-)metrics is reduced because the difficulty of generating examples. One technique to generate new fuzzy binary relations is based on merging a collection of them into a new one by means of the use of a function. Inspired, in part, by the preceding fact, this paper is devoted to study which functions allow us to merge a collection of fuzzy (quasi-) metrics into a single one. We present a characterization of such functions in terms of *-triangular triplets and also in terms of isotonicity and *-supmultiplicativity, where * is a t-norm. We also show that this characterization does not depend on the symmetry of the fuzzy quasi-metrics. The same problem for stationary fuzzy (quasi-) metrics is studied and, as a consequence, characterizations of those functions aggregating fuzzy preorders and indistinguishability operators are obtained. | es_ES |
dc.description.sponsorship | J. Rodriguez-Lopez and O. Valero acknowledge financial support from FEDER/Ministerio de Ciencia, Innovacion y Universidades-Agencia Estatal de Investigacion Proyecto PGC2018-095709-B-C21. This work is also partially supported by Programa Operatiu FEDER 2014-2020 de les Illes Balears, by project PROCOE/4/2017 (Direccio General d'Innovacio i Recerca, Govern de les Illes Balears) and by projects ROBINS and BUGWRIGHT2. These two latest projects have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 779776 and No 871260, respectively. This publication reflects only the authors views and the European Union is not liable for any use that may be made of the information contained therein. The authors thank the anonymous referees who provided useful and detailed comments on the manuscript. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Information Sciences | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | T-norm | es_ES |
dc.subject | Fuzzy (quasi-) metric | es_ES |
dc.subject | *-triangular triplet | es_ES |
dc.subject | Functions preserving *-transitivity of fuzzy | es_ES |
dc.subject | Binary relations | es_ES |
dc.subject | Aggregation of fuzzy quasi-metrics | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Aggregation of fuzzy quasi-metrics | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.ins.2020.08.045 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095709-B-C21/ES/METRICAS DIFUSAS Y OPERADORES DE INDISTINGUIBILIDAD: APLICACIONES EN ROBOTICA/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/CAIB//PROCOE%2F4%2F2017/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/779776/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/871260/EU | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Pedraza Aguilera, T.; Rodríguez López, J.; Valero, Ó. (2021). Aggregation of fuzzy quasi-metrics. Information Sciences. 581:362-389. https://doi.org/10.1016/j.ins.2020.08.045 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.ins.2020.08.045 | es_ES |
dc.description.upvformatpinicio | 362 | es_ES |
dc.description.upvformatpfin | 389 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 581 | es_ES |
dc.relation.pasarela | S\417484 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Govern de les Illes Balears | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades | es_ES |