Bayesian Noise Modelling for State Estimation of the Spread of COVID-19 in Saudi Arabia with Extended Kalman Filters

The epistemic uncertainty in coronavirus disease (COVID-19) model-based predictions using complex noisy data greatly affects the accuracy of pandemic trend and state estimations. Quantifying the uncertainty of COVID-19 trends caused by different unobserved hidden variables is needed to evaluate the...

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Detalles Bibliográficos
Autores principales: Alyami, Lamia, Panda, Deepak Kumar, Das, Saptarshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223553/
https://www.ncbi.nlm.nih.gov/pubmed/37430648
http://dx.doi.org/10.3390/s23104734

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223553/
https://www.ncbi.nlm.nih.gov/pubmed/37430648
http://dx.doi.org/10.3390/s23104734

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