Prediction of Infection and Death Ratio of COVID-19 Virus in Turkey by Using Artificial Neural Network (ANN)
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Bentham Science Publishers
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Background: For the first time in December 2019, as reported in the Wuhan city of China, COVID-19 deadly virus spread rapidly around the world and the first cases were seen in Turkey on March 11, 2020. On the same day, a pandemic was declared by the World Health Organization due to the rapid spread of the disease throughout the world. Methods: In this study, a multilayered perception feed-forward back propagation neural network has been designed for predicting the spread and mortality rate of the COVID-19 virus in Turkey. COVID-19 data from six different countries were used in the design of the artificial neural network, which has 15 neurons in its hidden layer. 70% of these optimized data were used for training, 20% for validation, and 10% for testing. Results: The simulation results showed that the COVID-19 virus in Turkey, between day 20 and 37, was the fastest to rise. The number of cases for the 20th day was predicted to be 13.845. Conclusion: As for the death rate, it was predicted that a rapid rise would start on the 20th day and a slowdown around the 43rd day and progress towards the zero case point. The death rate for the 20th day was predicted to be 170 and for the 43rd day it was 1,960s. © 2021 Bentham Science Publishers.
Açıklama
Anahtar Kelimeler
artificial neural network, CoVID-19, pandemic, SARS-CO-V-2, Turkey, viral transmission, Wuhan
Kaynak
Coronaviruses
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2
Sayı
1
