Forecasting COVID-19 cases: A comparative analysis between recurrent and convolutional neural networks

• Published in: Results in physics Vol. 24; p. 104137
• Main Authors: Nabi, Khondoker Nazmoon, Tahmid, Md Toki, Rafi, Abdur, Kader, Muhammad Ehsanul, Haider, Md. Asif
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.05.2021; The Author(s). Published by Elsevier B.V; Elsevier
• Subjects: Convolutional neural network (CNN); Deep learning; Long short term memory (LSTM); Time series analysis; Deep learning; Long short term memory (LSTM); Convolutional neural network (CNN); Time series analysis

•Four deep learning models: LSTM, GRU, CNN and MCNN have been studied in this paper.•Prediction accuracy of LSTM algorithm has been found to be poor in analyzing COVID-19 datasets.•Univariate and Multivariate CNNs have outperformed RNN. Though many countries have already launched COVID-19 mass vacci...