Predicting COVID-19 Transmission in Southern California with Machine Learning Methods-Reference-Cited by-同舟云学术

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Predicting COVID-19 Transmission in Southern California with Machine Learning Methods

Published:2024-03-16 Issue: Volume: Page:1-10
ISSN:
Container-title:2024 9th International Conference on Big Data Analytics (ICBDA)
language:
Short-container-title:

Author:

Li Han¹,Wei Ran²,Wang Wenyu³,Yu Nanpeng³

Affiliation:

1. School of Computer Science and Engineering, University of California, Riverside,Riverside,USA

2. School of Public Policy, University of California, Riverside,Riverside,USA

3. University of California, Riverside,Department of Electrical and Computer Engineering,Riverside,USA

Funder

National Institutes of Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10607152/10607161/10607162.pdf?arnumber=10607162

Reference20 articles.

1. Comparing the accuracy of several network-based COVID-19 prediction algorithms

2. A model based study on the dynamics of COVID-19: Prediction and control

3. Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model

4. SEIR modeling of the COVID-19 and its dynamics

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