Analysis, Visualization and Prediction of COVID-19 Pandemic Spread Using Machine Learning-Reference-Cited by-同舟云学术

Analysis, Visualization and Prediction of COVID-19 Pandemic Spread Using Machine Learning

Published:2021 Issue: Volume: Page:597-603
ISSN:2367-3370
Container-title:Innovations in Computer Science and Engineering
language:
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Author:

Sen Snigdha,Thejas B. K.,Pranitha B. L.,Amrita I.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-33-4543-0_63

Reference10 articles.

1. WHO corona viruses (COVID-19). Retrieved June 10, 2020 from https://www.who.int/emergencies/diseases/novel-coronavirus-2019

2. Benvenuto, D., Giovanetti, M., Vassallo, L., Angeletti, S., Ciccozzi, M.: Application of the ARIMA model on the COVID-2019 epidemic dataset. Data Brief 105340 (2020)

3. Punn, N.S., Sonbhadra, S.K., Agarwal, S.: COVID-19 epidemic analysis using machine learning and deep learning algorithms. Preprint https://doi.org/10.1101/2020.04.08.20057679 (2020)

4. Deb, S., Majumdar, M.: A time series method to analyze incidence pattern and estimate reproduction number of COVID-19. arXiv preprint arXiv:2003.10655 (2020)

5. Kucharski, A.J., Russell, T.W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Eggo, R.M., et al.: Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect. Dis. (2020)

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