Forecasting of COVID-19 Cases in India: A Predictive Study

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.

Cite this article as:

Sharma Pooja , Sharma Tanu and Veer Karan *, Forecasting of COVID-19 Cases in India: A Predictive Study, Current Immunology Reviews (Discontinued) 2020; 16 (1) . https://dx.doi.org/10.2174/1573395516999201112092152