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 (Bulletin of Electrical Engineering and Informatics, 2021)
The world is currently facing a strong epidemic and pandemic of coronavirus. This motivates establishing our paper, where this virus pushes researchers to study, investigate, observe, analyse and try solving its related issues. In this work, an artificial neural network (ANN) model of backpropagation neural network (BNN) with two hidden layers is proposed for expecting confirmed cases 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. This paper may implicate establishing further researches that consider other parameters and other countries over the world. It is worth mentioning that the suggested ANN model may help decision maker people in taking quarantine movements against the strong epidemic and pandemic of covid-19.