Forecasting of COVID-19 Epidemic Process in Ukraine and Neighboring Countries by Gradient Boosting Method
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-35467-0_30
Reference21 articles.
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2. Izonin, I., et al.: Predictive modeling based on small data in clinical medicine: RBF-based additive input-doubling method. Math. Biosci. Eng. 18(3), 2599–2613 (2021). https://doi.org/10.3934/mbe.2021132
3. Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proc. R. Soc. A: Math. Phys. Eng. Sci. 115(772), 700–721 (1927). https://doi.org/10.1098/rspa.1927.0118
4. ud Din, R., Algehyne, E.A.: Mathematical analysis of COVID-19 by using SIR model with convex incidence rate. Results Phys. 23, 103970 (2021). https://doi.org/10.1016/j.rinp.2021.103970
5. Ajbar, A., Alqahtani, R.T., Boumaza, M.: Dynamics of an SIR-based COVID-19 model with linear incidence rate, nonlinear removal rate, and public awareness. Front. Phys. 9, 634251 (2021). https://doi.org/10.3389/fphy.2021.634251
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