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dc.contributor.authorJie, H
dc.contributor.authorSanjuán Martínez, Óscar
dc.contributor.authorGonzález-Crespo, Rubén
dc.date2021
dc.date.accessioned2022-02-24T11:30:28Z
dc.date.available2022-02-24T11:30:28Z
dc.identifier.issn13591789
dc.identifier.urihttps://reunir.unir.net/handle/123456789/12506
dc.description.abstractRegular proportions of insight for emotional intelligence– for example, the IQ test – commonly center around the rationale and thinking in regions like math. Understanding cognizance has been considered a prominent research area in the present era. The possibility of this type of thinking supports the general achievement in the work environment, which is more powerful, and positively appears to be natural: It quantifies the person's capacity to get a handle on and orchestrate realities in their environment. In late years, the possibility that there is just a solitary type of knowledge that has gone under expanding the investigation. In this paper, the tests, learning about feelings, the capacity to perform assignments are identified with the information using an Adaptive Mathematical Modeling of Emotions (AMME) that has been designed mathematically. The fundamental contention is how the individual ought to act in a sincerely loaded circumstance, which does not pursue the individual who could do the detailed conduct adequately investigated in this research. © 2020 Elsevier Ltdes_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;online
dc.relation.urihttps://www.sciencedirect.com/science/article/abs/pii/S1359178920302421?via%3Dihubes_ES
dc.rightsrestrictedAccesses_ES
dc.subjectcomputational modeles_ES
dc.subjectemotional intelligencees_ES
dc.subjectfeelingses_ES
dc.subjectScopuses_ES
dc.titleThe influence of employee emotional intelligence on enterprise innovation performance using an adaptive mathematical modeling of emotionses_ES
dc.typearticlees_ES
reunir.tag~ARIes_ES
dc.identifier.doihttp://doi.org/10.1016/j.avb.2020.101538


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