Long Short-Term Memory Prediction for COVID19 Time Series

ABSTRACT

Entire world has been dealing with the number of new Coronavirus 2 or COVID-19 cases. The spread of thissevere acute respiratory syndrome has produced manyconcerns worldwide. Having data related to coronavirusavailable for tests, novel models for forecasting the number ofnew cases can be developed. In this paper, a long short-termmemory (LSTM) based methodology is applied for suchprediction. Here, experimental analysis is performed with theparameters, such as the number of layers and units of thenetwork. The root mean squared error is calculated for datacorresponding to the Republic of Serbia, as well as perdifferent continents. The results show that LSTM model canbe useful for further analysis and time series prediction © 2021, Telfor Journal. All Rights Reserved.