COVID-19 time series prediction

Oliveira, Leonardo Sestrem de; Gruetzmacher, Sarah; Teixeira, João Paulo

http://hdl.handle.net/10198/24672

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
COVID19_Sarah_Leonardo_Teixeira_Published.pdf		1.05 MB	Adobe PDF	Download

Send Feedback

Authors

Oliveira, Leonardo Sestrem de

Gruetzmacher, Sarah

Teixeira, João Paulo

Abstract(s)

The Artificial Neural Network (ANN) is a computer technique that uses a mathematical model to represent a simpler form of the biologic neural structure. It is formed by many processing units and its intelligent behavior comes from the iterations between these units. One application of the ANN is for time series prediction algorithms, where the network learns the behavior of time dependent data and it is able to predict future values. In this work, the ANN is applied in predicting the number of COVID-19 confirmed cases and deaths and also the future seven days for the time series of Brazil, Portugal and the United States. From the simulations it is possible to conclude that the prediction of confirmed cases and deaths from COVID-19 have been successfully made by the ANN. Overall, the ANN with a specific test set had a Mean Squared Error (MSE) 50% higher than the ANN with a random test set. The combination of the sigmoidal and linear activation functions and the Levenberg-Marquardt training function had the lowest MSE for all cases

Keywords

Brazil covid 19 prediction Covid 19 prediction Portugal covid 19 prediction Time series USA covid 19 prediction

URI

http://hdl.handle.net/10198/24672

Citation

Oliveira, Leonardo Sestrem de; Gruetzmacher, Sarah Beatriz; Teixeira, João Paulo (2021). COVID-19 time series prediction. In International Conference on ENTERprise Information Systems (CENTERIS), International Conference on Project MANagement (ProjMAN), International Conference on Health and Social Care Information Systems and Technologies (HCist). Procedia Computer Science. ISSN 1877-0509. p. 973-980.