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Rapid Prediction and Evaluation of COVID-19 Epidemic in the United States Based on Feature Selection and Improved ARIMAX Model

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Zhouqiang XiongAuthors Info & Claims

ICAIIS 2021: 2021 2nd International Conference on Artificial Intelligence and Information Systems

Article No.: 299, Pages 1 - 8

https://doi.org/10.1145/3469213.3471327

Published: 18 August 2021 Publication History

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Rahman MChowdhury A(2022)A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological driversPLOS ONE10.1371/journal.pone.027331917:9(e0273319)Online publication date: 13-Sep-2022
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ICAIIS 2021: 2021 2nd International Conference on Artificial Intelligence and Information Systems

May 2021

2053 pages

ISBN:9781450390200

DOI:10.1145/3469213

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ICAIIS 2021: 2021 2nd International Conference on Artificial Intelligence and Information Systems

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Rahman MChowdhury A(2022)A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological driversPLOS ONE10.1371/journal.pone.027331917:9(e0273319)Online publication date: 13-Sep-2022
https://doi.org/10.1371/journal.pone.0273319
Hasib KSakib SMahmud JMithu KRahman MAlam M(2022)COVID-19 Prediction based on Infected Cases and Deaths of Bangladesh using Deep Transfer Learning2022 IEEE World AI IoT Congress (AIIoT)10.1109/AIIoT54504.2022.9817160(296-302)Online publication date: 6-Jun-2022
https://doi.org/10.1109/AIIoT54504.2022.9817160
Ma LLiao YZhou BXi W(2022)PerHeFed: A general framework of personalized federated learning for heterogeneous convolutional neural networksWorld Wide Web10.1007/s11280-022-01119-x26:4(2027-2049)Online publication date: 12-Dec-2022
https://dl.acm.org/doi/10.1007/s11280-022-01119-x

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Analysis and prediction of COVID-19 trends in the United States

Evaluation and Prediction of COVID-19 Based on Time-Varying SIR Model

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