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Two-step residual-error based approach for anomaly detection in engineering systems using variational autoencoders

dc.contributor.authorGonzález Muñiz, Ana 
dc.contributor.authorDíaz Blanco, Ignacio 
dc.contributor.authorCuadrado Vega, Abel Alberto 
dc.contributor.authorGarcía Pérez, Diego 
dc.contributor.authorPérez, D.
dc.date.accessioned2023-02-01T11:51:48Z
dc.date.available2023-02-01T11:51:48Z
dc.date.issued2022
dc.identifier.citationComputers and Electrical Engineering, 101 (2022); doi:10.1016/j.compeleceng.2022.108065
dc.identifier.issn0045-7906
dc.identifier.urihttp://hdl.handle.net/10651/66145
dc.description.sponsorshipThis work has been financed by the Spanish National Research Agency (under grant number PID2020-115401GB-I00/AEI/ 10.13039/501100011033 ). The authors would also like to thank the financial support provided by the Principado de Asturias government, Spain through the predoctoral grant “Severo Ochoa”.
dc.language.isoeng
dc.relation.ispartofComputers and Electrical Engineering
dc.rights© 2022 Los autores. Publicado por Elsevier Ltd.
dc.rightsCC Reconocimiento - No Comercial - Sin Obra Derivada 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85130587157&doi=10.1016%2fj.compeleceng.2022.108065&partnerID=40&md5=58262f51a6ce612dbc3e6ca73765e65b
dc.titleTwo-step residual-error based approach for anomaly detection in engineering systems using variational autoencoders
dc.typejournal article
dc.identifier.doi10.1016/j.compeleceng.2022.108065
dc.local.notesOA ATUO22
dc.relation.projectIDAEI/PID2020-115401GB-I00
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.compeleceng.2022.108065
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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© 2022 Los autores. Publicado por Elsevier Ltd.
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