Predictions and visualization for confirmed, recovered and deaths COVID-19 cases in Iraq - Wisam Dawood Abdullah; Abdulrahman Ahmed Jasim; Layth Rafea Hazim (Indonesian Journal of Electrical Engineering and Computer Science, 2022)
The 2019-2020 coronavirus pandemic is an emerging infectious disease that has been referred to as the "COVID-19", which results from the coronavirus "sars-cov-2" that started in Wuhan, China, in Dec. 2019 and then spread worldwide. In this paper, an attempt for compiling and analyzing the information of the epidemiological outbreaks on "COVID‐19" based upon datasets on "2019‐nCoV" has been presented. An empirical data analysis with the visualizations was conducted for understanding the numbers of the variety of the cases that have been reported (i.e. confirmed, deaths, and recoveries) in and outside of Iraq and carried out a dynamic map visualization of the "Covid-19" expansion in a global manner through the date wise and in Iraq. We an investigation has been carried out as well, which characterized the pandemic effects Iraq and the entire world, with the use of machine learning. A k nearest neighbors' (KNN) model and a linear regression (LR) model have been proposed.This paper included the precise analysis of the confirmed cases, as well as the recovered cases, deaths, predicting the pandemic viral attacks and how far it is expanding in Iraq and the world, the LR model got the highest results, reaching 100 percent.