Examining vortex-induced vibration through convolutional neural networks

dc.contributor.author	Bublík, O.
dc.contributor.author	Heidler, V.
dc.contributor.author	Pecka, A.
dc.contributor.author	Vimmr, J.
dc.contributor.editor	Adámek, Vítězslav
dc.contributor.editor	Jonášová, Alena
dc.contributor.editor	Plánička, Stanislav
dc.date.accessioned	2023-11-26T13:59:25Z
dc.date.available	2023-11-26T13:59:25Z
dc.date.issued	2023
dc.description.sponsorship	This research is supported by the projects GA21-31457S ”Fast flow-field prediction using deep neural networks for solving fluid-structure interaction problems”.	en
dc.format	4 s.	cs
dc.format.mimetype	application/pdf
dc.identifier.citation	Computational mechanics 2023: book of extended abstracts: 38th conference with international participation, p. 5-8.	en
dc.identifier.isbn	978-80-261-1177-1
dc.identifier.uri	http://hdl.handle.net/11025/54830
dc.language.iso	en	en
dc.publisher	University of West Bohemia	en
dc.rights	© 2023 University of West Bohemia, Plzeň, Czech Republic	en
dc.rights.access	openAccess	en
dc.subject	konvoluční neuronové sítě	cs
dc.subject	výpočetní dynamika tekutin	cs
dc.subject	dataset	cs
dc.subject	vibrace	cs
dc.subject.translated	convolutional neural networks	en
dc.subject.translated	computational fluid dynamics	en
dc.subject.translated	dataset	en
dc.subject.translated	vibration	en
dc.title	Examining vortex-induced vibration through convolutional neural networks	en
dc.type	konferenční příspěvek	cs
dc.type	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en

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