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Forecast and evaluation of COVID-19 spreading in USA with reduced-space Gaussian process regression
In this report, we analyze historical and forecast infections for COVID-19 death based on Reduced-Space Gaussian Process Regression associated to chaotic Dynamical Systems with information obtained in 82 days with continuous learning, day by day, from January 21(th), 2020 to April 12(th). According...
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| Publicado no: | Chaos Solitons Fractals |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Elsevier Ltd.
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7242925/ https://ncbi.nlm.nih.gov/pubmed/32501372 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.chaos.2020.109924 |
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