Forecasting The Impact of Vaccination on Daily Cases in Turkey for Covid-19

Autor:	Enes YILDIZ, Muhammed Mustafa KELEK, Fatih Onur HOCAOĞLU, Yüksel OĞUZ
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Computer Science Artifical Intelligence Bilgisayar Bilimleri Yapay Zeka Covid-19 Forecasting Artificial Intelligence Artificial Neural Networks (ANN) Daily Case Earth-Surface Processes
Zdroj:	Volume: 11, Issue: 1 19-26 Academic Platform Journal of Engineering and Smart Systems
ISSN:	2822-2385
Popis:	This study, it is aimed to investigate the effect of the vaccine on the cases in the fight against Covid-19, which threatens the whole world. The number of Covid-19 cases, which were tried to be reduced with various precautions worldwide and in Turkey, has become a new hope with the start of vaccination. The increase in the effect of the vaccination, which started in January 2021, brought the need to examine the vaccination rate in three groups as slow, medium, and fast. In this study, different scenarios were tried in the number of vaccinations applied in Turkey, and the daily number of cases until December 2021 was forecasted by Artificial Neural Networks (ANN). The effect of restrictions and vaccination on the number of Covid-19 cases was investigated. Different training algorithms were used, and the best success rate was found with the comparison method. Accurate forecasting of cases will let policymakers take precautions on time. Moreover, the effect of vaccination on cases should be investigated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7268334981bfb157ad84628bf2a2c11 https://dergipark.org.tr/tr/pub/apjess/issue/75064/1137177 Zobrazit plný text záznamu