Using Artificial Neural Network with Prey Predator Algorithm for Prediction of the COVID-19: The Case of Brazil and Mexico

Abstract

The spread of the COVID-19 epidemic worldwide has led to investigations in various aspects, including the estimation of expected cases. As it helps in identifying the need to deal with cases caused by the pandemic. In this study, we have used artificial neural networks (ANNs) to predict the number of cases of COVID-19 in Brazil and Mexico in the upcoming days. Prey predator algorithm (PPA), as a type of metaheuristic algorithm, is used to train the models. The proposed ANN models’ performance has been analyzed by the root mean squared error (RMSE) function and correlation coefficient (R). It is demonstrated that the ANN models have the highest performance in predicting the number of infections (active cases), recoveries, and deaths in Brazil and Mexico. The simulation results of the ANN models show very well predicted values. Percentages of the ANN’s prediction errors with metaheuristic algorithms are significantly lower than traditional monolithic neural networks. The study shows the expected numbers of infections, recoveries, and deaths that Brazil and Mexico will reach daily at the beginning of 2021.

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“… 10 Ünlü and Namlı [ 24 ] Predicting COVID-19 confirmed cases and deaths in seven countries Confirmed cases Deaths Applying e Support Vector Machines (SVM), Holt-Winters, Facebook's Prophet, and Long-Short Term Memory (LSTM) for forecasting Using only RMSE in the interpretation of results 11 Niazkar and Niazkar [ 25 ] Estimating the confirmed cases of COVID-19 in China, Japan, Singapore, Iran, Italy, South Africa, and the United States of America. Chronological data of confirmed and death cases Applying fourteen ANN-based models to predict the COVID-19 outbreak Using a limited number of data 12 Hamadneh et al [ 26 ] Forecasting the number of total confirmed cases, total recovered cases, and total deaths in Brazil and Mexico The requested data Using ANN to estimate the number of cases of COVID-19 with prey predator algorithm (PPA) There is no comparative analysis to compare the results 13 Toga et al [ 27 ] Predicting the infected cases, the number of deaths, and the recovered cases with ARIMA and ANN in Turkey Susceptible cases Days Curfews Laboratory tests Determining the susceptible case number for each day after the first recovered case 14 Kumari and Toshniwal [ 28 ] Forecasting the COVID-19 outbreak in India with ANN Cumulative confirmed, new, and cumulative deceased cases recorded daily Utilizing a mathematical curve fitting model to understand the performance of the proposed model Not conducting a comparative analysis 15 Conde-Gutiérrez et al [ 29 ] Estimating the cumulative number of deaths from COVID-19 in México Cumulative number of deaths Comparing ANN with Gompertz model in estimating the number of deaths 16 …”