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Application of Machine Learning for Solving Problems of Nuclear Power Plant Operation

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dc.contributor.authorVolodin, V. S.
dc.contributor.authorTolokonskij, A. O.
dc.contributor.authorТолоконский, Андрей Олегович
dc.date.accessioned2024-12-26T10:48:02Z
dc.date.available2024-12-26T10:48:02Z
dc.date.issued2022
dc.description.abstract© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Nowadays, the industry is actively introducing technologies based on machine learning: predictive analytics, computer vision, industrial robots, etc. In this article authors discuss the possible application of machine learning to improve the operation of nuclear power plant (NPP) power units: diagnostics of the state of equipment (both technological equipment of normal operation systems and equipment of safety systems); definition of irrelevant alarm; determination of the state of the reactor plant; application of machine learning in equipment control algorithms. The report also examines the existing difficulties in introducing machine learning into NPP operation: issues of stability of control systems based on machine learning; the issue of interpretability of solutions issued by systems based on machine learning; small data set size for training machine learning models.
dc.format.extentС. 585-589
dc.identifier.citationVolodin, V. S. Application of Machine Learning for Solving Problems of Nuclear Power Plant Operation / Volodin, V.S., Tolokonskij, A.O. // Studies in Computational Intelligence. - 2022. - 1032 SCI. - P. 585-589. - 10.1007/978-3-030-96993-6_65
dc.identifier.doi10.1007/978-3-030-96993-6_65
dc.identifier.urihttps://www.doi.org/10.1007/978-3-030-96993-6_65
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dc.identifier.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000833484200065
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/28959
dc.relation.ispartofStudies in Computational Intelligence
dc.titleApplication of Machine Learning for Solving Problems of Nuclear Power Plant Operation
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume1032 SCI
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