Prediction of COVID-19 Active, Recovered, and Death Cases Using Artificial Neural Network and Grey Wolf Optimization
Advances in Healthcare Information Systems and AdministrationHandbook of Research on Mathematical Modeling for Smart Healthcare Systems(2022)
摘要
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.
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关键词
wolf,prediction,death cases,artificial neural network
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