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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54294
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dc.contributor.authorMalugin, V.-
dc.contributor.authorSergeev, A.-
dc.contributor.authorSolomevich, A.-
dc.coverage.spatialМинскen_US
dc.date.accessioned2024-02-20T11:35:23Z-
dc.date.available2024-02-20T11:35:23Z-
dc.date.issued2023-
dc.identifier.citationMalugin, V. Multi-country analysis of the COVID-19 pandemic typology using machine learning and neural network algorithms / V. Malugin, A. Sergeev, A. Solomevich // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 209–211.en_US
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/54294-
dc.description.abstractThe paper presents the results of a multi-country analysis of the intensity typology of the COVID-19 pandemic in 30 countries of the European region based on publicly available and regularly updated panel data for the entire period 2020-2022 of high pandemic activity. In the generated space of classification features, using cluster analysis algorithms, all countries are divided into three classes, which differ in the intensity of the epidemic process. Based on the obtained country ratings, an integral statistical indicator of the COVID-19 pandemic is constructed. A set of discriminant analysis machine learning and neural network algorithms are used to estimate current as well predict the expected class of the epidemic state based on the newly acquiring data.en_US
dc.language.isoenen_US
dc.publisherBSUen_US
dc.subjectматериалы конференцийen_US
dc.subjectCOVID-19 typologyen_US
dc.subjectmulti-country analysisen_US
dc.subjectcountry ratingsen_US
dc.subjectintegral pandemic indicatoren_US
dc.subjectmachine learningen_US
dc.subjectneural networken_US
dc.titleMulti-country analysis of the COVID-19 pandemic typology using machine learning and neural network algorithmsen_US
dc.typeArticleen_US
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

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