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Transfer Learning for COVID-19 cases and deaths forecast using LSTM network

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In this paper, Transfer Learning is used in LSTM networks to forecast new COVID cases and deaths. Models trained in data from early COVID infected countries like Italy and the… Click to show full abstract

In this paper, Transfer Learning is used in LSTM networks to forecast new COVID cases and deaths. Models trained in data from early COVID infected countries like Italy and the United States are used to forecast the spread in other countries. Single and multistep forecasting is performed from these models. The results from these models are tested with data from Germany, France, Brazil, India, and Nepal to check the validity of the method. The obtained forecasts are promising and can be helpful for policymakers coping with the threats of COVID-19.

Keywords: cases deaths; transfer learning; forecast using; covid cases; learning covid; deaths forecast

Journal Title: ISA Transactions
Year Published: 2021

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