74234

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

4

Параметры публикации
Тип публикации: 
Статья в журнале/сборнике
Название: 
Short-Term Covid-19 Incidence Prediction in Countries Using Clustering and Regression Analysis
ISBN/ISSN: 
2194-5357
DOI: 
10.1007/978-3-031-16684-6
Наименование источника: 
Advances in Intelligent Systems and Computing
Обозначение и номер тома: 
Vol 1435: Intelligent Methods Systems and Applications in Computing, Communications and Control. ICCCC 2022
Город: 
Cham, Switzerland
Издательство: 
Springer Nature
Год издания: 
2023
Страницы: 
333-342
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 method-ology 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 // Advances in Intelligent Systems and Computing. 2023. Vol 1435: Intelligent Methods Systems and Applications in Computing, Communications and Control. ICCCC 2022. С. 333-342.