Please use this identifier to cite or link to this item: http://repo.knmu.edu.ua/handle/123456789/30051
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChumachenko, Dmytro-
dc.contributor.authorChumachenko, Tatyana-
dc.contributor.authorЧумаченко, Тетяна Олександрівна-
dc.contributor.authorЧумаченко, Татьяна Александровна-
dc.contributor.authorMeniailov, Ievgen-
dc.contributor.authorMuradyan, Olena-
dc.contributor.authorZholtkevych, Grigoriy-
dc.date.accessioned2021-12-02T13:53:37Z-
dc.date.available2021-12-02T13:53:37Z-
dc.date.issued2021-11-29-
dc.identifier.citationForecasting of COVID-19 Epidemic Process by Lasso Regression / D. Chumachenko, T. Chumachenko, Ie. Meniailov, O. Muradyan, G. Zholtkevych // 2021 IEEE Fifth International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo), 29 November – 02 December 2021, Kyiv, Ukraine. – Kyiv, 2021. – P. 80–83.en_US
dc.identifier.urihttps://repo.knmu.edu.ua/handle/123456789/30051-
dc.language.isoenen_US
dc.subjectepidemic modelen_US
dc.subjectCOVID-19en_US
dc.subjectmachine learningen_US
dc.subjectlasso regressionen_US
dc.subjectinfectious diseases forecastingen_US
dc.titleForecasting of COVID-19 Epidemic Process by Lasso Regressionen_US
dc.typeArticleen_US
Appears in Collections:Наукові праці. Кафедра епідеміології

Files in This Item:
File Description SizeFormat 
D.Chumachenko_T.Chumachenko_Meniailov_Muradyan_Zholtkevych.pdf3,43 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.