Prediction of COVID-19 Active, Recovered, and Death Cases Using Artificial Neural Network and Grey Wolf Optimization

Abstract

The 2019 novel corona virus was declared a global pandemic by the World Health Organization (WHO) on March 11th, 2020. The world is stressed out because of this disease's high infectiousness and transmission mode. A predictive model of the COVID-19 outbreak is developed for India using state-of-the-art neural network models. The chapter evaluates the key features to predict the patterns, potential infection rate, and death of the present COVID-19 outbreak in India. In this chapter, machine learning methods such as artificial neural network (ANN) optimized by a bio-inspired optimization algorithm that is grey wolf optimization (GWO) and particle swarm optimization (PSO) have been implemented for the prediction of infection rate and mortality rate for the 5 days, 15 days, and 30 days ahead. The prediction of various parameters obtained by the proposed approach is effective within a certain specific range and would be a useful tool for administration and healthcare providers.