Broad-deep network-based fuzzy emotional inference model with personal information for intention understanding in human–robot interaction

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dc.contributor.authorLi, M.
dc.contributor.authorChen, L.
dc.contributor.authorWu, M.
dc.contributor.authorHirota, K.
dc.contributor.authorPedrycz, W.
dc.date.accessioned2024-05-19T14:33:32Z
dc.date.available2024-05-19T14:33:32Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractA broad-deep fusion network-based fuzzy emotional inference model with personal information (BDFEI) is proposed for emotional intention understanding in human–robot interaction. It aims to understand students’ intentions in the university teaching scene. Initially, we employ convolution and maximum pooling for feature extraction. Subsequently, we apply the ridge regression algorithm for emotional behavior recognition, which effectively mitigates the impact of complex network structures and slow network updates often associated with deep learning. Moreover, we utilize multivariate analysis of variance to identify the key personal information factors influencing intentions and calculate their influence coefficients. Finally, a fuzzy inference method is employed to gain a comprehensive understanding of intentions. Our experimental results demonstrate the effectiveness of the BDFEI model. When compared to existing models, namely FDNNSA, ResNet-101+GFK, and HCFS, the BDFEI model achieved superior accuracy on the FABO database, surpassing them by 12.21%, 1.89%, and 0.78%, respectively. Furthermore, our self-built database experiments yielded an impressive 82.00% accuracy in intention understanding, confirming the efficacy of our emotional intention inference model. © 2024 Elsevier Ltden_US
dc.identifier.doi10.1016/j.arcontrol.2024.100951
dc.identifier.issn1367-5788
dc.identifier.scopus2-s2.0-85188549256en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.arcontrol.2024.100951
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4263
dc.identifier.volume57en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofAnnual Reviews in Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBroad Learningen_US
dc.subjectConvolution Neural Networksen_US
dc.subjectEmotional İntentionen_US
dc.subjectHuman-Robot İnteractionen_US
dc.titleBroad-deep network-based fuzzy emotional inference model with personal information for intention understanding in human–robot interactionen_US
dc.typeArticleen_US

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