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A generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysis

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dc.contributor.authorFumanal Idocin, Javier
dc.contributor.authorTakáč, Zdenko
dc.contributor.authorHoranská, Lubomíra
dc.contributor.authorDa Cruz Asmus, Tiago
dc.contributor.authorPereira Dimuro, Graçaliz
dc.contributor.authorVidaurre Arbizu, Carmen
dc.contributor.authorFernández Fernández, Francisco Javier
dc.contributor.authorBustince Sola, Humberto
dc.contributor.departmentInstitute of Smart Cities - ISCen
dc.date.accessioned2023-05-11T08:28:56Z
dc.date.issued2022
dc.date.updated2023-05-11T08:19:34Z
dc.description.abstractIntervals are a popular way to represent the uncertainty related to data, in which we express the vagueness of each observation as the width of the interval. However, when using intervals for this purpose, we need to use the appropriate set of mathematical tools to work with. This can be problematic due to the scarcity and complexity of interval-valued functions in comparison with the numerical ones. In this work, we propose to extend a generalization of the Sugeno integral to work with interval-valued data. Then, we use this integral to aggregate interval-valued data in two different settings: first, we study the use of intervals in a brain-computer interface; secondly, we study how to construct interval-valued relationships in a social network, and how to aggregate their information. Our results show that interval-valued data can effectively model some of the uncertainty and coalitions of the data in both cases. For the case of brain-computer interface, we found that our results surpassed the results of other interval-valued functions.en
dc.description.sponsorshipThis work was supported by the Spanish Ministry of Economy and Competitiveness through the Spanish National Research (project PID2019-108392GB-I00/ financed by MCIN/AEI/10.13039/501100011033 and the grant VEGA 1/0267/21 ).en
dc.embargo.inicio2023-05-11
dc.embargo.lift2024-12-21
dc.embargo.terms2024-12-21
dc.format.mimetypeapplication/pdfen
dc.identifier.citationFumanal-Idocin, J., Takác, Z., Horanská, L., da Cruz Asmus, T., Dimuro, G., Vidaurre, C., Fernandez, J., Bustince, H. (2022) A generalization of the Sugeno integral to aggregate interval-valued data: An application to brain computer interface and social network analysis. Fuzzy Sets and Systems, 451, 320-341. https://doi.org/10.1016/j.fss.2022.10.003.en
dc.identifier.doi10.1016/j.fss.2022.10.003
dc.identifier.issn0165-0114
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/45285
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofFuzzy Sets and Systems, 451 (2022) 320-341en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/en
dc.relation.publisherversionhttps://doi.org/10.1016/j.fss.2022.10.003
dc.rights© 2022 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAggregation functionen
dc.subjectBrain computer interfaceen
dc.subjectGeneralized Sugeno integralen
dc.subjectSocial networken
dc.subjectSugeno integralen
dc.titleA generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysisen
dc.typeinfo:eu-repo/semantics/article
dc.type.versionVersión aceptada / Onetsi den bertsioaes
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dspace.entity.typePublication
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