Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models
Forecasting in pandemics and disasters is one of the means that contribute to reducing the damage of this pandemic, and the Corona virus is reportedly the most dangerous pandemic that the entire world is suffering from. As a result, we aim to use a deep learning algorithm to predict confirmed and ne...
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my.uniten.dspace-345562024-10-14T11:20:38Z Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models Hasan R.A. Jamaluddin J.E. 58487876600 37080724200 Covid-19 Deep Learning GRU LSTM Malaysia Prediction Forecasting in pandemics and disasters is one of the means that contribute to reducing the damage of this pandemic, and the Corona virus is reportedly the most dangerous pandemic that the entire world is suffering from. As a result, we aim to use a deep learning algorithm to predict confirmed and new cases of Covid-19 in our study. This paper identifies the most essential deep learning techniques. Long short-term memory (LSTM) and gated recurrent unit (GRU) were shown to forecast verified Covid-19 fatalities in Malaysia, Egypt, and the U.S. using time series data from 1 January 2021 to 14 May 2022. The first section of this study examines a comparison of prediction models, while the second section examines how prediction and performance analysis may be enhanced using mean absolute error (MAE), mean absolute error percentage (MAPE), and root mean squared error (RMSE) Metrics. On the basis of the regression curves of two two-layer models, the data were split into training sets of 80% and test sets of 20%. The conclusion is that the outputs of the training model and the original data greatly converged. The findings of the study indicated that, for predicting Covid-19 cases, the GRU model in the three nations is superior than the LSTM model. �Copyright Hasan. Final 2024-10-14T03:20:38Z 2024-10-14T03:20:38Z 2023 Article 10.11113/mjfas.v19n3.2992 2-s2.0-85164772690 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164772690&doi=10.11113%2fmjfas.v19n3.2992&partnerID=40&md5=f27a04f1303d224247761af19f4e6c2c https://irepository.uniten.edu.my/handle/123456789/34556 19 3 417 428 All Open Access Gold Open Access Penerbit UTM Press Scopus |
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Covid-19 Deep Learning GRU LSTM Malaysia Prediction |
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Covid-19 Deep Learning GRU LSTM Malaysia Prediction Hasan R.A. Jamaluddin J.E. Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
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Forecasting in pandemics and disasters is one of the means that contribute to reducing the damage of this pandemic, and the Corona virus is reportedly the most dangerous pandemic that the entire world is suffering from. As a result, we aim to use a deep learning algorithm to predict confirmed and new cases of Covid-19 in our study. This paper identifies the most essential deep learning techniques. Long short-term memory (LSTM) and gated recurrent unit (GRU) were shown to forecast verified Covid-19 fatalities in Malaysia, Egypt, and the U.S. using time series data from 1 January 2021 to 14 May 2022. The first section of this study examines a comparison of prediction models, while the second section examines how prediction and performance analysis may be enhanced using mean absolute error (MAE), mean absolute error percentage (MAPE), and root mean squared error (RMSE) Metrics. On the basis of the regression curves of two two-layer models, the data were split into training sets of 80% and test sets of 20%. The conclusion is that the outputs of the training model and the original data greatly converged. The findings of the study indicated that, for predicting Covid-19 cases, the GRU model in the three nations is superior than the LSTM model. �Copyright Hasan. |
| author2 |
58487876600 |
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58487876600 Hasan R.A. Jamaluddin J.E. |
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Article |
| author |
Hasan R.A. Jamaluddin J.E. |
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Hasan R.A. |
| title |
Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
| title_short |
Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
| title_full |
Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
| title_fullStr |
Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
| title_full_unstemmed |
Prediction of Covid-19 Cases for Malaysia, Egypt, and USA using Deep Learning Models |
| title_sort |
prediction of covid-19 cases for malaysia, egypt, and usa using deep learning models |
| publisher |
Penerbit UTM Press |
| publishDate |
2024 |
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1814061184955973632 |
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13.222552 |