Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model
Novel coronavirus (COVID-19) was discovered in Wuhan, China in December 2019, and has affected millions of lives worldwide. On 29th April 2020, Malaysia reported more than 5,000 COVID-19 cases; the second highest in the Southeast Asian region after Singapore. Recently, a forecastingmodel was deve...
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Frontiers Media S.A.
2021
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my.iium.irep.905102021-07-16T07:50:17Z http://irep.iium.edu.my/90510/ Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model Shaharudin, Shazlyn Milleana Ismail, Shuhaida Hassan, Noor Artika Tan, Mou Leong Sulaiman, Nurul Ainina Filza GA Mathematical geography. Cartography HA154 Statistical data RA643 Communicable Diseases and Public Health T57 Applied mathematics. Quantitative methods. Operation research. System analysis Novel coronavirus (COVID-19) was discovered in Wuhan, China in December 2019, and has affected millions of lives worldwide. On 29th April 2020, Malaysia reported more than 5,000 COVID-19 cases; the second highest in the Southeast Asian region after Singapore. Recently, a forecastingmodel was developed tomeasure and predict COVID- 19 cases in Malaysia on daily basis for the next 10 days using previously-confirmed cases. A Recurrent Forecasting-Singular Spectrum Analysis (RF-SSA) is proposed by establishing L and ET parameters via several tests. The advantage of using this forecasting model is it would discriminate noise in a time series trend and produce significant forecasting results. The RF-SSA model assessment was based on the official COVID-19 data released by the World Health Organization (WHO) to predict daily confirmed cases between 30th April and 31st May, 2020. These results revealed that parameter L = 5 (T/20) for the RF-SSA model was indeed suitable for short-time series outbreak data, while the appropriate number of eigentriples was integral as it influenced the forecasting results. Evidently, the RF-SSA had over-forecasted the cases by 0.36%. This signifies the competence of RF-SSA in predicting the impending number of COVID- 19 cases. Nonetheless, an enhanced RF-SSA algorithm should be developed for higher effectivity of capturing any extreme data changes. Frontiers Media S.A. 2021-06-14 Article PeerReviewed application/pdf en http://irep.iium.edu.my/90510/7/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19%20cases%20in%20Malaysia%20using%20RF-SSA%20model.pdf application/pdf en http://irep.iium.edu.my/90510/13/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/90510/14/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19_WOS.pdf Shaharudin, Shazlyn Milleana and Ismail, Shuhaida and Hassan, Noor Artika and Tan, Mou Leong and Sulaiman, Nurul Ainina Filza (2021) Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model. Frontiers in Public Health, 9. pp. 1-14. E-ISSN 2296-2565 https://www.frontiersin.org/journals/public-health 10.3389/fpubh.2021.604093 |
| institution |
Universiti Islam Antarabangsa Malaysia |
| building |
IIUM Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
International Islamic University Malaysia |
| content_source |
IIUM Repository (IREP) |
| url_provider |
http://irep.iium.edu.my/ |
| language |
English English English |
| topic |
GA Mathematical geography. Cartography HA154 Statistical data RA643 Communicable Diseases and Public Health T57 Applied mathematics. Quantitative methods. Operation research. System analysis |
| spellingShingle |
GA Mathematical geography. Cartography HA154 Statistical data RA643 Communicable Diseases and Public Health T57 Applied mathematics. Quantitative methods. Operation research. System analysis Shaharudin, Shazlyn Milleana Ismail, Shuhaida Hassan, Noor Artika Tan, Mou Leong Sulaiman, Nurul Ainina Filza Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| description |
Novel coronavirus (COVID-19) was discovered in Wuhan, China in December 2019, and
has affected millions of lives worldwide. On 29th April 2020, Malaysia reported more
than 5,000 COVID-19 cases; the second highest in the Southeast Asian region after
Singapore. Recently, a forecastingmodel was developed tomeasure and predict COVID-
19 cases in Malaysia on daily basis for the next 10 days using previously-confirmed
cases. A Recurrent Forecasting-Singular Spectrum Analysis (RF-SSA) is proposed
by establishing L and ET parameters via several tests. The advantage of using this
forecasting model is it would discriminate noise in a time series trend and produce
significant forecasting results. The RF-SSA model assessment was based on the official
COVID-19 data released by the World Health Organization (WHO) to predict daily
confirmed cases between 30th April and 31st May, 2020. These results revealed that
parameter L = 5 (T/20) for the RF-SSA model was indeed suitable for short-time series
outbreak data, while the appropriate number of eigentriples was integral as it influenced
the forecasting results. Evidently, the RF-SSA had over-forecasted the cases by 0.36%.
This signifies the competence of RF-SSA in predicting the impending number of COVID-
19 cases. Nonetheless, an enhanced RF-SSA algorithm should be developed for higher
effectivity of capturing any extreme data changes. |
| format |
Article |
| author |
Shaharudin, Shazlyn Milleana Ismail, Shuhaida Hassan, Noor Artika Tan, Mou Leong Sulaiman, Nurul Ainina Filza |
| author_facet |
Shaharudin, Shazlyn Milleana Ismail, Shuhaida Hassan, Noor Artika Tan, Mou Leong Sulaiman, Nurul Ainina Filza |
| author_sort |
Shaharudin, Shazlyn Milleana |
| title |
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| title_short |
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| title_full |
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| title_fullStr |
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| title_full_unstemmed |
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model |
| title_sort |
short-term forecasting of daily confirmed covid-19 cases in malaysia using rf-ssa model |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
http://irep.iium.edu.my/90510/7/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19%20cases%20in%20Malaysia%20using%20RF-SSA%20model.pdf http://irep.iium.edu.my/90510/13/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19_SCOPUS.pdf http://irep.iium.edu.my/90510/14/90510_Short-term%20forecasting%20of%20daily%20confirmed%20COVID-19_WOS.pdf http://irep.iium.edu.my/90510/ https://www.frontiersin.org/journals/public-health |
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1706956581802868736 |
| score |
13.251813 |