72401

Автор(ы): 
Алескеров Ф. Т. (ИПУ РАН, Лаборатория 25)
Автор(ов): 

4

Параметры публикации
Тип публикации: 
Доклад
Название: 
Short-Term Covid-19 Incidence Prediction in Countries Using Clustering and Regression Analysis
ISBN/ISSN: 
Print ISSN 2194-5357
DOI: 
10.1007/978-3-031-16684-6_29
Наименование конференции: 
9th International Conference on Computers Communications and Control (ICCCC 2022)
Наименование источника: 
Proceedings of the 9th International Conference on Computers Communications and Control (Advances in Intelligent Systems and Computing)
Обозначение и номер тома: 
Vol.1435
Город: 
Cham
Издательство: 
Springer
Год издания: 
2023
Страницы: 
333-342 https://link.springer.com/chapter/10.1007/978-3-031-16684-6_29
Аннотация
As of February 07, 2022, more than 395 million cases of COVID-19 had been identified in the world, with 5.74 million deaths. The paper considers methodology for predicting the number of cases in the short term using a preliminary assessment of countries based on three indicators: expert assessments of the law-abiding population, the level of education and restrictive measures taken in the country. The description and composition of the groups obtained are given. An assessment of the accuracy of the forecast results is made. A comparison of the considered models of 2020 with 2022 is given.
Библиографическая ссылка: 
Алескеров Ф.Т., Демин С.С., Мячин А.Л., Якуба В.И. Short-Term Covid-19 Incidence Prediction in Countries Using Clustering and Regression Analysis / Proceedings of the 9th International Conference on Computers Communications and Control (Advances in Intelligent Systems and Computing). Cham: Springer, 2023. Vol.1435. С. 333-342 https://link.springer.com/chapter/10.1007/978-3-031-16684-6_29.