Title: COVID-19 outbreak in Orissa: MLR and H-SVR-based modelling and forecasting
Authors: Satyabrata Dash; Hemraj Saini; Sujata Chakravarty
Addresses: Department of Computer Science and Engineering, Ramachandra College of Engineering, Eluru, Andhra Pradesh, India ' Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India ' Department of Computer Science and Engineering, Centurion University of Technology Management, Bhubaneswar, Orissa, India
Abstract: WHO has declared COVID-19 as the pandemic in early March and now in June it became a severe threat to the human community in almost all the countries. The present situation throughout the world is too tensed and puts everyone at a high risk of novel corona virus and this further leads to the high mortality rate due to mass reaction to it. Everyone of the related research community is using technology and trying to identify the time at which it stops and make the world healthy again. Therefore, in this study, an attempt has been made to analyse and predict COVID-19 outbreak using Multiple Linear Regression and Support Vector Regression. In this comparative analysis, Multiple Linear Regression outperforms Support Vector Regression. Hence, MLR can be used to predict COVID-19 outbreak in the real-life application.
Keywords: novel coronavirus; COVID-19; linear multiple regression; support vector regression.
International Journal of Computer Applications in Technology, 2021 Vol.66 No.3/4, pp.401 - 414
Received: 18 Jun 2020
Accepted: 29 Nov 2020
Published online: 21 Jan 2022 *