Author: Ismail, L.; Alhmoudi, S.; Alkatheri, S.
Title: Time Series Forecasting of COVID-19 Infections in United Arab Emirates using ARIMA Cord-id: hx3j8v1r Document date: 2020_1_1
ID: hx3j8v1r
Snippet: 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. © 2020 IEEE.
Document: 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. © 2020 IEEE.
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