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Dynamics identification and forecasting of COVID-19 by switching Kalman filters
The COVID-19 pandemic has captivated scientific activity since its early days. Particular attention has been dedicated to the identification of underlying dynamics and prediction of future trend. In this work, a switching Kalman filter formalism is applied on dynamics learning and forecasting of the...
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| Gepubliceerd in: | Comput Mech |
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| Hoofdauteurs: | , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Springer Berlin Heidelberg
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7455787/ https://ncbi.nlm.nih.gov/pubmed/32904528 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00466-020-01911-4 |
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