Forecasting novel COVID-19 confirmed cases in India using Machine Learning Methods - Date, Saroj S; Deshmukh, Sachin N (International Journal of Computer Sciences and Engineering, 2020)
Nowadays, there is a very adverse impact on economic, cultural, social and almost all fields in the world because of Covid-19. The Covid-19 term is described as -'CO' for corona, 'VI' for virus, and 'D' for disease. It is an infectious disease caused by severe acute respiratory syndrome which is transmitted through respiratory droplets and contact routes. Since December 2019, corona-virus disease (COVID-19) has out-broke from the country China. Till now, more than 78, 23, 289 people are infected and more than 4 Lakhs of deaths have been caused worldwide. Unfortunately, the number of infections and deaths are still increasing rapidly which has put the world in a different state. Artificial Intelligence can play a key role to infection forecasting in national and provincial levels in many countries. The objective of this study is to use machine learning methods to forecast the number of cases for the next 2 weeks, i.e. till 30th June 2020. The data was collected from 22nd January to 15th June 2020 by nationally recognized sources. The data file contains the cumulative count of confirmed, death and recovered cases of COVID-19 from different countries from the date 22nd January 2020.In this study, the outbreak of this disease has been analyzed for India till 15th June 2020 and predictions have been made for the number of cases for the next two weeks.