- -

Aggregation of fuzzy quasi-metrics

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Aggregation of fuzzy quasi-metrics

Mostrar el registro sencillo del ítem

Ficheros en el ítem

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


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem