The Using Artificial Neural Network Model to Prediction the Number of Peoples Afflicted by the Epidemic of (COVID-19) in Iraq - Mohammed Habeb AlSharoot; Noor Chyad Alisawi (Al-Qadisiyah Journal of Pure Science, 2020)
Time-series prediction is an important statistical topic to help researchers in planning and making the right decisions, so this study deals with modern prediction methods, represented by the Artificial Neural Network models, specifically the multi-layered neural network, and the back propagation algorithm has been relied upon several times for training and less selection. A value for error to obtain the best model for describing the data, as well as classic prediction methods such as Box- Jenkins’ models, the model was applied to real data represented by the number of people infected with Coronavirus (Covid-19) in Iraq for the period from 2/24/2020 until 3/5/ 2020 On a daily basis, the results showed that future predictions for the number of people infected with Coronavirus began to decline and then stabilized in the period (30-67). The data were analyzed and the results were extracted depending on the statistical program R.