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Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells

K.E. ArunKumar, Dinesh V. Kalaga, Ch. Mohan Sai Kumar, Masahiro Kawaji, Timothy M. Brenza

2021Chaos Solitons & Fractals242 citationsDOIOpen Access PDF

Topics & Concepts

Recurrent neural networkCase fatality ratePandemicCoronavirus disease 2019 (COVID-19)PopulationComputer scienceDemographyGeographyArtificial neural networkArtificial intelligenceMedicineDiseaseEnvironmental healthPathologySociologyInfectious disease (medical specialty)COVID-19 epidemiological studiesCOVID-19 diagnosis using AIAnomaly Detection Techniques and Applications
Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells | Litcius