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Forecasting the Novel Coronavirus(COVID-19) using Time Series Model

Chudasama, Harsh (2020) Forecasting the Novel Coronavirus(COVID-19) using Time Series Model. Masters thesis, Dublin, National College of Ireland.

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Abstract

The 2019 novel coronavirus (COVID-19), which originated from China, has spread quickly among individuals living in different nations and spreading quickly throughout the globe with nearly 20 million cases overall as indicated by the insights of the European Center for Disease Prevention and Control. Researchers from all over the world are working together to develop the vaccine as this virus is highly contagious which spreads through human contact and while taking into account the high pace of the disease spread and the critical number of fatalities. Scientists have made good progress in developing the vaccines which are at the early stages of the clinical trials1 and hoping soon for a cure, but in the meantime death toll is increasing day by day. This research primarily focusses on the forecasting of confirmed, death, and recovered cases using the time series model. In this research, various models were used namely LSTM, Prophet, ARMA, and ARIMA for forecasting the spread of virus-based in India, and results were evaluated. LSTM outperformed the other three models based on the evaluation matrix with least MAPE of 1.18 % and R2 of 0.9997.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

R Medicine > RA Public aspects of medicine
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 20 Jan 2021 13:41
Last Modified: 20 Jan 2021 13:41
URI: http://norma.ncirl.ie/id/eprint/4391

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