Time Series Forecasting of COVID-19 Cases in Brazil with GNN and Mobility Networks-Reference-Cited by-同舟云学术

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Time Series Forecasting of COVID-19 Cases in Brazil with GNN and Mobility Networks

Published:2023 Issue: Volume: Page:361-375
ISSN:0302-9743
Container-title:Intelligent Systems
language:
Short-container-title:

Author:

Duarte Fernando Henrique Oliveira^ORCID,Moreira Gladston J. P.^ORCID,Luz Eduardo J. S.^ORCID,Santos Leonardo B. L.^ORCID,Freitas Vander L. S.^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-45392-2_24

Reference28 articles.

1. Cumulative cases of covid-19 in Brazil (2023). https://covid.saude.gov.br//. Accessed 06 May 2023

2. Berlin, D.A., Gulick, R.M., Martinez, F.J.: Severe covid-19. N. Engl. J. Med. 383(25), 2451–2460 (2020)

3. Chen, J., Wang, X., Xu, X.: Gc-lstm: graph convolution embedded lstm for dynamic network link prediction. Appl. Intell. 52(7), 7513–7528 (2022)

4. Cota, W.: Monitoring the number of covid-19 cases and deaths in brazil at municipal and federative units level. SciELO Preprints (2020)

5. DASA: Cumulative cases of covid-19 in the world (2023). https://dadoscoronavirus.dasa.com.br/. Accessed 06 May 2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review of Graph Neural Networks in Epidemic Modeling;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. A Deep Graph Neural Network Approach for Assessing Origin Destination Traffic Flow Estimates Based on COVID-19 Data;IEEE Access;2024

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