Publication:
Two new methods to construct fuzzy metrics from metrics

dc.contributor.authorGrigorenko, Olga
dc.contributor.authorMiñana, Juan-José
dc.contributor.authorValero, Oscar
dc.date.accessioned2024-10-09T06:36:31Z
dc.date.available2024-10-09T06:36:31Z
dc.date.issued2023
dc.description.abstractIn the last years, the interest in the notion of fuzzy metric has been growing in such a way that many works have focused their efforts on the study of their topological properties and their applications to Engineering problems. However, the applicability of fuzzy metrics is limited due to lack of examples in the literature. Motivated, on the one hand, by these facts and, on the other hand, by the fact that most of the instances of fuzzy metrics in the literature are constructed from classical metrics, in this paper we introduce two new techniques which allow us to construct systematically fuzzy metrics from metrics in such a way that the celebrated classical method for constructing indistinguishability operators from metrics is retrieved as a particular case. Hence, we construct strong fuzzy metrics from a given classical one considering continuous Archimedean t-norms and the pseudo-inverse of their additive generators acting on the metric modified by a positive real function. Moreover, we extend this technique tackling the particular case of the minimum t-norm, which is continuous but non-Archimedean. In such a construction, two non-negative real functions are now involved in order to modify the classical metric and one of them must be superadditive. In this case, the fuzzy metric obtained is not strong in general. Furthermore, the new methods are illustrated by means of different examples which, in addition, show that some celebrated examples of fuzzy metrics can be retrieved as a particular case through them. Finally, in the light of the developed theory, an open problem about strong fuzzy metrics is solved completing the partial solutions that can be found in the literature.en
dc.description.sponsorshipThis research was funded by Proyecto PGC2018-095709-B-C21 financiado por MCIN/AEI/10.13039/501100011033 y FEDER Una manera de hacer Europa and from project BUGWRIGHT2. This last project has received funding from the European Union´s Horizon 2020 research and innovation programme under grant agreements No. 871260. 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.es_ES
dc.format.page108483es_ES
dc.format.volume467es_ES
dc.identifier.citationGrigorenko O, Miñana J-J, Valero O. Two new methods to construct fuzzy metrics from metrics. Fuzzy Sets Syst. 2023 Sep;467:108483.en
dc.identifier.doi10.1016/j.fss.2023.02.004
dc.identifier.issn0165-0114
dc.identifier.journalFuzzy Sets and Systemses_ES
dc.identifier.otherhttps://hdl.handle.net/20.500.13003/19181
dc.identifier.scopus2-s2.0-85150379601
dc.identifier.urihttps://hdl.handle.net/20.500.12105/23794
dc.identifier.wos1012826200001
dc.language.isoengen
dc.publisherElsevier
dc.relation.publisherversionhttps://doi.org/10.1016/j.fss.2023.02.004en
dc.rights.accessRightsopen accessen
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleTwo new methods to construct fuzzy metrics from metricsen
dc.typeresearch articleen
dspace.entity.typePublication
relation.isPublisherOfPublication7d471502-7bd5-4f7a-90a4-8274382509ef
relation.isPublisherOfPublication.latestForDiscovery7d471502-7bd5-4f7a-90a4-8274382509ef

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