Predict the Risk Level in Iraqi Governorates According to the Spread of COVID-19 Using Data Mining

Authors

  • Ibtisam Abbas Othman
  • Ban Sharief Mustafa University of Mosul

DOI:

https://doi.org/10.56286/ntujps.v1i2.203

Keywords:

Covid-19, Covid-19 prediction tool, Iraq’s covid-19 dataset, LSTM.

Abstract

The massive spread of COVID-19 made it one of the biggest current pandemics in the world. Predicting the extent of the virus' spread is critical to containing the threat, because it helps to take appropriate measures and decisions at the state level as well as at the personal level, where it is possible to avoid travel to the places of spread and take the necessary measures to limit the spread of the virus. In this research, an intelligent model has been built to predict the extent of the spread of Covid-19 disease in the Iraqi governorates. COVID-19 data for Iraq's governorates was obtained from a website affiliated with the Iraqi Ministry of Health. The data was reconstructed according to a certain structure to be used in training the prediction model. The LSTM deep learning algorithm was adopted for its effective performance in predicting the direction of the recorded cases in the future. The results showed a high accuracy in the performance of the model.

Downloads

Published

2022-05-31

How to Cite

Abbas Othman, I., & Sharief Mustafa, B. . (2022). Predict the Risk Level in Iraqi Governorates According to the Spread of COVID-19 Using Data Mining. NTU Journal of Pure Sciences, 1(2), 22–28. https://doi.org/10.56286/ntujps.v1i2.203