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

#### Yıldıran YILMAZ [1] , Selim BUYRUKOĞLU [2]

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.
Covid-19, Neural Network, ARIMA, Time Series, Correlated Additive Model
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Primary Language en Engineering Research Article Orcid: 0000-0002-5337-6090Author: Yıldıran YILMAZ (Primary Author)Institution: Recep Tayyip Erdogan UniversityCountry: Turkey Orcid: 0000-0001-7844-3168Author: Selim BUYRUKOĞLUInstitution: Çankırı Karatekin ÜniversitesiCountry: Turkey Application Date : January 15, 2021 Acceptance Date : May 18, 2021 Publication Date : June 30, 2021
 Bibtex @research article { hjse861988, journal = {Hittite Journal of Science and Engineering}, issn = {}, eissn = {2148-4171}, address = {Hitit Üniversitesi Mühendislik Fakültesi Kuzey Kampüsü Çevre Yolu Bulvarı 19030 Çorum / TÜRKİYE}, publisher = {Hitit University}, year = {2021}, volume = {8}, pages = {123 - 131}, doi = {10.17350/HJSE19030000222}, title = {Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries}, key = {cite}, author = {Yılmaz, Yıldıran and Buyrukoğlu, Selim} } APA Yılmaz, Y , Buyrukoğlu, 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 . DOI: 10.17350/HJSE19030000222 MLA Yılmaz, Y , Buyrukoğlu, 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 (2021 ): 123-131 Chicago Yılmaz, Y , Buyrukoğlu, 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 (2021 ): 123-131 RIS TY - JOUR T1 - Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries AU - Yıldıran Yılmaz , Selim Buyrukoğlu Y1 - 2021 PY - 2021 N1 - doi: 10.17350/HJSE19030000222 DO - 10.17350/HJSE19030000222 T2 - Hittite Journal of Science and Engineering JF - Journal JO - JOR SP - 123 EP - 131 VL - 8 IS - 2 SN - -2148-4171 M3 - doi: 10.17350/HJSE19030000222 UR - https://doi.org/10.17350/HJSE19030000222 Y2 - 2021 ER - EndNote %0 Hittite Journal of Science and Engineering Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries %A Yıldıran Yılmaz , Selim Buyrukoğlu %T Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries %D 2021 %J Hittite Journal of Science and Engineering %P -2148-4171 %V 8 %N 2 %R doi: 10.17350/HJSE19030000222 %U 10.17350/HJSE19030000222 ISNAD Yılmaz, Yıldıran , Buyrukoğlu, 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 (June 2021): 123-131 . https://doi.org/10.17350/HJSE19030000222 AMA Yılmaz Y , Buyrukoğlu S . Hybrid Machine Learning Model Coupled with School Closure For Forecasting COVID-19 Cases in the Most Affected Countries. Hittite J Sci Eng. 2021; 8(2): 123-131. Vancouver Yılmaz Y , Buyrukoğlu 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. IEEE Y. Yılmaz and S. Buyrukoğlu , "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, pp. 123-131, Jun. 2021, doi:10.17350/HJSE19030000222

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