Title:Forecasting of COVID-19 Cases in India: A Predictive Study
Volume: 16
Issue: 1
Author(s): Pooja Sharma, Tanu Sharma and Karan Veer*
Affiliation:
- Department Instrumentation & Control Engineering,Manipal Institute of Technology,Manipal,India
Keywords:
COVID-19, forecasting, linear regression, multilayer perceptron, sequential minimization optimization, world
health organization.
Abstract: An outbreak of new coronavirus (COVID-19) originated by SARS-CoV has reached
212 countries throughout the world. India is the second-highest populated country, so it is critical
to forecasting the confirmed cases and deaths due to pandemic. To fulfil the purpose, three machine
learning models Linear Regression, Multilayer Perceptron, and Sequential Minimal Optimization
Regression are used. The predictive data of three geographic regions (India, Maharashtra, and
Tamil Nadu) are compared with the data considered to be adequate in practice. The analysis concluded
that Sequential Minimal Optimization Regression can be adopted for possible pandemic predictions
such as COVID-19.
