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Deep Learning and Holt-Trend Algorithms for Predicting Covid-19 Pandemic

Deep Learning and Holt-Trend Algorithms for Predicting Covid-19 Pandemic

Authors :
Ahmed H. Alahmadi
Mohammed Alzahrani
Mosleh Hmoud Al-Adaileh
Theyazn H. H. Aldhyani
Melfi Alrasheed
Ahmed Abdullah Alqarni
Source :
Computers, Materials & Continua. 67:2141-2160
Publication Year :
2021
Publisher :
Computers, Materials and Continua (Tech Science Press), 2021.

Abstract

The Covid-19 epidemic poses a serious public health threat to the world, where people with little or no pre-existing human immunity can be more vulnerable to its effects Thus, developing surveillance systems for predicting the Covid-19 pandemic at an early stage could save millions of lives In this study, a deep learning algorithm and a Holt-trend model are proposed to predict the coronavirus The Long-Short Term Memory (LSTM) and Holt-trend algorithms were applied to predict confirmed numbers and death cases The real time data used has been collected from the World Health Organization (WHO) In the proposed research, we have considered three countries to test the proposed model, namely Saudi Arabia, Spain and Italy The results suggest that the LSTM models show better performance in predicting the cases of coronavirus patients Standard measure performance Mean squared Error (MSE), Root Mean Squared Error (RMSE), Mean error and correlation are employed to estimate the results of the proposed models The empirical results of the LSTM, using the correlation metrics, are 99 94%, 99 94% and 99 91% in predicting the number of confirmed cases in the three countries As far as the results of the LSTM model in predicting the number of death of Covid-19, they are 99 86%, 98 876% and 99 16% with respect to Saudi Arabia, Italy and Spain respectively Similarly, the experiment's results of the Holt-Trend model in predicting the number of confirmed cases of Covid-19, using the correlation metrics, are 99 06%, 99 96% and 99 94%, whereas the results of the Holt-Trend model in predicting the number of death cases are 99 80%, 99 96% and 99 94% with respect to the Saudi Arabia, Italy and Spain respectively The empirical results indicate the efficient performance of the presented model in predicting the number of confirmed and death cases of Covid-19 in these countries Such findings provide better insights regarding the future of Covid-19 this pandemic in general The results were obtained by applying time series models, which need to be considered for the sake of saving the lives of many people

Details

ISSN :
15462226
Volume :
67
Database :
OpenAIRE
Journal :
Computers, Materials & Continua
Accession number :
edsair.doi...........a1c850d90dab096aaf0e118a29e79d6e
Full Text :
https://doi.org/10.32604/cmc.2021.014498