74234 | ИПУ РАН

Автор(ы):

Автор(ов):

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.