COVID-19 Future Predection Using ARIMA Modal

Project Code :TCMAPY416

Objective

The objective of this project is about novel coronavirus also known as COVID-19 predictions. The COVID-19 has proved a potential threat to human life. It causes tens of thousands of deaths and the death rate is increasing day by day throughout the globe. To contribute to this pandemic situation control, this study attempts to perform future forecasting on the death, recoveries and cases. Our model will help to create future predictions which reduce the burden to the people who are continuously working on covid predictions.

Abstract

Forecasting mechanisms have proved their significance to anticipate in adjective outcomes to improve the decision making on the future course of actions. The time series models have long been used in many application domains which needed the identification and prioritization of adverse factors for a threat. Several prediction methods are being popularly used to handle forecasting problems. This study demonstrates the capability of tsa models to forecast the number of upcoming patients affected by COVID-19 which is presently considered as a potential threat to mankind. Our proposed method integrates a numeral of approach, intended to advance the cooperativeness of the explore operation. In this work, we will show how our model can be able to predict future outcomes for SARS-COV2 using Auto Regressive Integrated Moving Averages.

KEYWORDS: Covid-19, ARIMA, Fatalities, and Recoveries.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.