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dc.creatorPapčo, Martines_ES
dc.creatorRodríguez Martínez, Iosues_ES
dc.creatorFumanal Idocin, Javieres_ES
dc.creatorAltalhi, A. H.es_ES
dc.creatorBustince Sola, Humbertoes_ES
dc.description.abstractIn this paper we propose an extension of the notion of deviation-based aggregation function tailored to aggregate multidimensional data. Our objective is both to improve the results obtained by other methods that try to select the best aggregation function for a particular set of data, such as penalty functions, and to reduce the temporal complexity required by such approaches. We discuss how this notion can be defined and present three illustrative examples of the applicability of our new proposal in areas where temporal constraints can be strict, such as image processing, deep learning and decision making, obtaining favourable results in the process.en
dc.description.sponsorshipThe research done by Humberto Bustince, Iosu Rodríguez Martínez and Javier Fumanal Idocin has been funded by the project PID2019-108392GB-I00: 3031138640/AEI/10.13039/501100011033. The work of Martin Papčo was supported by the Slovak Research and Development Agency under the contract No. APVV-16-0073.en
dc.format.extent30 p.
dc.relation.ispartofInformation Fusion, 71 (2021) 1-10en
dc.rights© 2021 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.1en
dc.subjectAggregation fusionen
dc.subjectModerate deviation functionen
dc.subjectMulti-valued data fusionen
dc.titleA fusion method for multi-valued dataen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
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.type.versionVersión aceptada / Onetsi den bertsioaes

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© 2021 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.1
Except where otherwise noted, this item's license is described as © 2021 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.1

El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
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