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dc.creatorLucca, Giancarloes_ES
dc.creatorSanz Delgado, José Antonioes_ES
dc.creatorPereira Dimuro, Graçalizes_ES
dc.creatorBedregal, Benjamines_ES
dc.creatorBustince Sola, Humbertoes_ES
dc.date.accessioned2021-03-04T13:30:44Z
dc.date.available2021-03-04T13:30:44Z
dc.date.issued2020
dc.identifier.issn1572-9796 (Electronic)
dc.identifier.urihttps://hdl.handle.net/2454/39283
dc.description.abstractIn this paper, we consider the concept of extended Choquet integral generalized by a copula, called CC-integral. In particular, we adopt a CC-integral that uses a copula defined by a parameter α, which behavior was tested in a previous work using different fixed values. In this contribution, we propose an extension of this method by learning the best value for the parameter α using a genetic algorithm. This new proposal is applied in the fuzzy reasoning method of fuzzy rule-based classification systems in such a way that, for each class, the most suitable value of the parameter α is obtained, which can lead to an improvement on the system's performance. In the experimental study, we test the performance of 4 different so called CαC-integrals, comparing the results obtained when using fixed values for the parameter α against the results provided by our new evolutionary approach. From the obtained results, it is possible to conclude that the genetic learning of the parameter α is statistically superior than the fixed one for two copulas. Moreover, in general, the accuracy achieved in test is superior than that of the fixed approach in all functions. We also compare the quality of this approach with related approaches, showing that the methodology proposed in this work provides competitive results. Therefore, we demonstrate that CαC-integrals with α learned genetically can be considered as a good alternative to be used in fuzzy rule-based classification systems.en
dc.description.sponsorshipThe authors would like to thank the Brazilian National Counsel of Technological and Scientific Development CNPq (Proc. 233950/2014-1, 481283/2013-7, 306970/ 2013-9, 307681/2012-2) and the Spanish Ministry of Science and Technology under project TIN2016-77356-P (AEI/FEDER, UE). G.P. Dimuro is also supported by Caixa and Fundación Caja Navarra of Spain.en
dc.format.extent12 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringeren
dc.relation.ispartofNatural Computing, 2020, 19(3), 533-546en
dc.rights© Springer Science+Business Media B.V., part of Springer Nature 2018en
dc.subjectAggregation functionsen
dc.subjectChoquet integralen
dc.subjectFuzzy rule-based classification systemsen
dc.subjectFuzzy reasoning methoden
dc.subjectGenetic algorithmsen
dc.subjectEvolutionary fuzzy systemsen
dc.titleA proposal for tuning the α parameter in CαC-integrals for application in fuzzy rule-based classification systemsen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticases_ES
dc.contributor.departmentUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa. ISC - Institute of Smart Citieses_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Sailaeu
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.identifier.doi10.1007/s11047-018-9678-x
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-Pen
dc.relation.publisherversionhttps://doi.org/10.1007/s11047-018-9678-x
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.type.versionVersión aceptada / Onetsi den bertsioaes


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