A Regression Model for Short-Term COVID-19 Pandemic Assessment

Liu, X orcid.org/0000-0001-6354-2067, Li, K orcid.org/0000-0001-6657-0522, Yang, Z et al. (1 more author) (2021) A Regression Model for Short-Term COVID-19 Pandemic Assessment. In: Communications in Computer and Information Science. 6th International Conference on Life System Modeling and Simulation, LSMS 2020, and 6th International Conference on Intelligent Computing, 25 Oct 2020, Hangzhou, China. Springer Nature . ISBN 978-981-33-6377-9

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Copyright, Publisher and Additional Information: © Springer Nature Singapore Pte Ltd. 2020. This is an author produced version of an article published in Communications in Computer and Information Science. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: COVID-19; Regression model; FRA; Data driven
Dates:
  • Published: January 2021
  • Accepted: 1 June 2020
  • Published (online): 12 January 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 04 Jan 2021 13:11
Last Modified: 01 Feb 2021 12:37
Status: Published
Publisher: Springer Nature
Identification Number: https://doi.org/10.1007/978-981-33-6378-6_38

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