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COVID-19 Pandemic Prediction for Hungary: A Hybrid Machine Learning Approach
[post]
2020
unpublished
Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to a high level of uncertainty or even lack of essential data, the standard epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant
doi:10.20944/preprints202005.0031.v1
fatcat:54gmap25qveuhffgmkl6horiie