Predicting COVID-19 trends in Canada: a tale of four models

Predicting COVID-19 trends in Canada: a tale of four models

This study aims to offer multiple-model informed predictions of COVID-19 in Canada, specifically through the use of deep learning strategy and mathematical prediction models including long-short term memory network, logistic regression model, Gaussian model, and susceptible-infected-removed model. U...

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Bibliographic Details
Main Authors: Wandong Zhang, W.G. (Will) Zhao, Dana Wu, Yimin Yang
Format: Article
Language:English
Published: Wiley 2020-05-01
Series:Cognitive Computation and Systems
Subjects:
diseases
logistics
learning (artificial intelligence)
regression analysis
health care
multiple-model informed predictions
tale
covid-19 trends
canada
infective cases
daily increased number
susceptible-infected-removed model
gaussian model
logistic regression model
long-short term memory network
mathematical prediction models
deep learning strategy
Online Access:https://digital-library.theiet.org/content/journals/10.1049/ccs.2020.0017

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