Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries

Yilmaz, Yildiran; Buyrukoglu, Selim

doi:10.17350/HJSE19030000222

Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries

Yıldıran Yılmaz, (Recep Tayyip Erdoğan Üniversitesi, Mühendislik Ve Mimarlık Fakültesi, Bilgisayar Mühendisliği Bölümü, Rize, Türkiye)

Selim Buyrukoğlu (Çankırı Karatekin Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Çankırı, Türkiye)

Hittite Journal of Science and Engineering

2 3

Yıl: 2021 Cilt: 8 Sayı: 2 Sayfa Aralığı: 123 - 131 Metin Dili: İngilizce DOI: 10.17350/HJSE19030000222 İndeks Tarihi: 29-07-2022

Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries

Öz:

Coronavirus disease (Covid-19) caused millions of confirmed cases and thousands of deaths worldwide since first appeared in China. Forecasting methods are essential to take precautions early and control the spread of this rapidly expanding pandemic. Therefore, in this research, a new customized hybrid model consisting of Back Propagation-Based Artificial Neural Network (BP-ANN), Correlated Additive Model (CAM) and Auto-Regressive Integrated Moving Average (ARIMA) models were developed to forecast of Covid-19 prevalence in Brazil, US, Russia and India. Covid-19 dataset is obtained from World Health Organization website from 22 January, 2020 to 6 January, 2021. Various parameters were tested to select the best ARIMA models for these countries based on the lowest MAPE values (5.21, 11.42, 1.45, 2.72) for Brazil, US, Russia and India, respectively. On the other hand, the proposed BP-ANN model itself provided less satisfactory MAPE values. Finally, the developed new customized hybrid model was achieved to obtain the best MAPE results (4.69, 6.4, 0.63, 2.25) for forecasting of Covid-19 prevalence in Brazil, US, Russia and India, respectively. Those results emphasize the validity of our hybrid model. Besides, the proposed prediction models can assist countries in terms of taking important precautions to control the spread of Covid-19 in the world.

Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

TRDizin Dışındaki Atıf Sayıları

OpenCitations: 4

OpenAlex: 8

Crossref: 6

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APA	Yilmaz Y, Buyrukoglu S (2021). Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. , 123 - 131. 10.17350/HJSE19030000222
Chicago	Yilmaz Yildiran,Buyrukoglu Selim Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. (2021): 123 - 131. 10.17350/HJSE19030000222
MLA	Yilmaz Yildiran,Buyrukoglu Selim Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. , 2021, ss.123 - 131. 10.17350/HJSE19030000222
AMA	Yilmaz Y,Buyrukoglu S Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. . 2021; 123 - 131. 10.17350/HJSE19030000222
Vancouver	Yilmaz Y,Buyrukoglu S Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. . 2021; 123 - 131. 10.17350/HJSE19030000222
IEEE	Yilmaz Y,Buyrukoglu S "Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries." , ss.123 - 131, 2021. 10.17350/HJSE19030000222
ISNAD	Yilmaz, Yildiran - Buyrukoglu, Selim. "Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries". (2021), 123-131. https://doi.org/10.17350/HJSE19030000222

APA	Yilmaz Y, Buyrukoglu S (2021). Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite Journal of Science and Engineering, 8(2), 123 - 131. 10.17350/HJSE19030000222
Chicago	Yilmaz Yildiran,Buyrukoglu Selim Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite Journal of Science and Engineering 8, no.2 (2021): 123 - 131. 10.17350/HJSE19030000222
MLA	Yilmaz Yildiran,Buyrukoglu Selim Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite Journal of Science and Engineering, vol.8, no.2, 2021, ss.123 - 131. 10.17350/HJSE19030000222
AMA	Yilmaz Y,Buyrukoglu S Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite Journal of Science and Engineering. 2021; 8(2): 123 - 131. 10.17350/HJSE19030000222
Vancouver	Yilmaz Y,Buyrukoglu S Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite Journal of Science and Engineering. 2021; 8(2): 123 - 131. 10.17350/HJSE19030000222
IEEE	Yilmaz Y,Buyrukoglu S "Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries." Hittite Journal of Science and Engineering, 8, ss.123 - 131, 2021. 10.17350/HJSE19030000222
ISNAD	Yilmaz, Yildiran - Buyrukoglu, Selim. "Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries". Hittite Journal of Science and Engineering 8/2 (2021), 123-131. https://doi.org/10.17350/HJSE19030000222