Time Series Forecasting of COVID-19 Infections in United Arab Emirates using ARIMA
2020Vol. 13, pp. 801–806
Citations Over Time
Abstract
Machine learning time series models have been used to predict COVID-19 pandemic infections. Based on the public dataset from Johns Hopkins, we present a novel framework for forecasting COVID-19 infections. We implement our framework for the United Arab Emirates (UAE) and develop autoregressive integrated moving average (ARIMA) time series forecast model. To the best of our knowledge, this is the only study to forecast the infections in UAE using the time series model.
Related Papers
- → And now for something completely different: from 2019-nCoV and COVID-19 to 2020-nMan(2020)27 cited
- → Time Series Forecasting of COVID-19 Infections in United Arab Emirates using ARIMA(2020)8 cited
- → Confirmation of SARS-CoV-2 airborne dissemination indoors using “COVID-19 traps”(2021)4 cited
- → ОПЫТ ИССЛЕДОВАНИЯ СЕРОПРЕВАЛЕНТНОСТИ К ВИРУСУ SARS-CoV-2 НАСЕЛЕНИЯ ИРКУТСКОЙ ОБЛАСТИ В ПЕРИОД ВСПЫШКИ COVID-19(2020)2 cited