Health in Emergencies and Disasters Quarterly
فصلنامه سلامت در حوادث و بلایا
Health in Emergencies and Disasters Quarterly
Medical Sciences
http://hdq.uswr.ac.ir
1
admin
2345-4210
2345-4210
10.32598/hdq
en
jalali
1401
4
1
gregorian
2022
7
1
7
4
online
1
fulltext
fa
Using an Artificial Neural Network Model to Predict the Number of COVID-19 Cases in Iran
عمومى
General
پژوهشي
Research
<strong>Background: </strong>Forecasting methods are used in various fields including the health problems. This study aims to use the Artificial Neural Network (ANN) method for predicting coronavirus disease 2019 (COVID-19) cases in Iran.<br>
<strong>Materials and Methods:</strong> This is a descriptive, analytical, and comparative study to predict the time series of COVID-19 cases in Iran from May 2020 to May 2021. An ANN model was used for forecasting, which had three Input, output, and intermediate layers. The network training was conducted by the Levenberg-Marquardt algorithm. The forecasting accuracy was measured by calculating the mean absolute percentage error.<br>
<strong>Results:</strong> The mean absolute error of the designed ANN model was 6 and its accuracy was 94%.<br>
<strong>Conclusion:</strong> The ANN has high accuracy in forecasting the number of COVID-19 cases in Iran. The outputs of this model can be used as a basis for decisions in controlling the COVID-19.
COVID-19, forecasting, Artificial neural network, Time series
177
182
http://hdq.uswr.ac.ir/browse.php?a_code=A-10-222-14&slc_lang=fa&sid=1
Nabi
Omidi
mromid_91@yahoo.com
10031947532846007218
10031947532846007218
Yes
Department of Management, Payam Noor University, Tehran, Iran.
Mohammad Reza
Omidi
mromid_91@yahoo.com
10031947532846007219
10031947532846007219
No
Department of Industrial Engineering, Payam Noor University, Tehran, Iran.