Publication:
On the accuracy of Covid-19 forecasting methods in Russia for two years

Дата
2022
Авторы
Moloshnikov, I. A.
Sboev, A. G.
Naumov, A. V.
Zavertyaev, S. V.
Rybka, R. B.
Journal Title
Journal ISSN
Volume Title
Издатель
Научные группы
Организационные подразделения
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Организационная единица
Институт ядерной физики и технологий
Цель ИЯФиТ и стратегия развития - создание и развитие научно-образовательного центра мирового уровня в области ядерной физики и технологий, радиационного материаловедения, физики элементарных частиц, астрофизики и космофизики.
Выпуск журнала
Аннотация
The effectiveness of predicting the dynamics of the coronavirus pandemic for Russia as a whole and for Moscow is studied for a two-year period beginning March 2020. The comparison includes well-proven population models and statistic methods along with a new data-driven model based on the LSTM neural network. The latter model is trained on a set of Russian regions simultaneously, and predicts the total number of cases on the 14-day forecast horizon. Prediction accuracy is estimated by the mean absolute percent error (MAPE). The results show that all the considered models, both simple and more complex, have similar efficiency. The lowest error achieved is 18% MAPE for Moscow and 8% MAPE for Russia.
Описание
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Цитирование
On the accuracy of Covid-19 forecasting methods in Russia for two years / Moloshnikov, I. A. [et al.] // Procedia Computer Science. - 2022. - 213. - № C. - P. 428-434. - 10.1016/j.procs.2022.11.088
URI
https://www.doi.org/10.1016/j.procs.2022.11.088
 https://www.scopus.com/record/display.uri?eid=2-s2.0-85146113559&origin=resultslist
 https://openrepository.mephi.ru/handle/123456789/28284
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