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

Yıldıran YILMAZ; Selim BUYRUKOĞLU

doi:https://doi.org/10.17350/HJSE19030000222

Makale detayları

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

Yazarlar:

Yıldıran YILMAZ | Selim BUYRUKOĞLU

Yayıncı:

Hitit University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Hittite Journal of Science and Engineering 2021 Vol.8 Issue 2, pp.123-131

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000451280

Sıklık:

Üç Aylık

eISSN:

2148-4171

DOI:

https://doi.org/10.17350/HJSE19030000222

Özet:

 

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.

Makale detayları

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

Yazarlar: Yıldıran YILMAZ | Selim BUYRUKOĞLU

Yayıncı: Hitit University

Ana Başlıklar: Uygulamalı fizik

Dergi: Hittite Journal of Science and Engineering 2021 Vol.8 Issue 2, pp.123-131

Belge Tipi: Makale

Yayın Tarihi: 6/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000451280

Sıklık: Üç Aylık

eISSN: 2148-4171

DOI: https://doi.org/10.17350/HJSE19030000222

Sayı

Yazarlar:

Yıldıran YILMAZ | Selim BUYRUKOĞLU

Yayıncı:

Hitit University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Hittite Journal of Science and Engineering 2021 Vol.8 Issue 2, pp.123-131

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000451280

Sıklık:

Üç Aylık

eISSN:

2148-4171

DOI:

https://doi.org/10.17350/HJSE19030000222