Expecting Confirmed and Death Cases of COVID-19 in Iraq by Utilizing Backpropagation Neural Network

Moatasem Yaseen Al-Ridha, Ammar Sameer Anaz, Raid Rafi Omar Al-Nima


The world is currently facing a strong pandemic of Coronavirus. This virus pushes researchers to study, investigate and try solving its related issues. In this work, an artificial model of Backpropagation Neural Network (BNN) with two hidden layers is proposed for expecting confirmed and death cases of Coronavirus Disease 2019 (COVID-19). As a field of study, Iraq country has been considered in this paper. COVID-19 dataset from Our World in Data (OWID) is used here. Promising result is achieved where a very small error value of 0.0035 is reported in overall the evaluations.


Prediction, Covid-19, Backpropagation Neural Network



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DOI: https://doi.org/10.11591/eei.v10i4.2876


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