Prediction of Infection and Death Ratio of COVID-19 Virus in Turkey by Using Artificial Neural Network (ANN)

Title:Prediction of Infection and Death Ratio of COVID-19 Virus in Turkey by Using Artificial Neural Network (ANN)

Volume: 2 Issue: 1

Author(s): Andaç Batur Çolak*

Affiliation:

• Department of Mechanical Engineering, Nigde Omer Halisdemir University, Nigde 51240,Turkey

Keywords: CoVID-19, Turkey, Wuhan, artificial neural network, viral transmission, pandemic, SARS-CO-V-2.

Abstract:

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.

Cite this article as:

Çolak Batur Andaç*, Prediction of Infection and Death Ratio of COVID-19 Virus in Turkey by Using Artificial Neural Network (ANN), Coronaviruses 2021; 2 (1) . https://dx.doi.org/10.2174/2666796701999200915142539