Noble Machine Learning Approaches for Lock Downing Area during Coronavirus (COVID-19) Pandemic Waves

Novel coronavirus has become a pandemic worldwide since December, 2019. All ongoing plans have been propounded due to COVID-19. Areas with large number of infected and death patients have been taken under lockdown. Continuous locking down areas have created a huge impact on economy especially for the under developed and developing countries. But most of the countries are locking down their areas without any assumption. In this situation, this paper proposes a model to determine which area of a country should be taken under lockdown immediately. The proposed work uses dataset containing the information of different region of the world with their infected, death, recovered patients, and area of the region, population and successfully presence of lockdown. Finally, Machine Learning algorithms have been applied to determine the area to lockdown with the highest accuracy of 95.185%.

Author(s): Motaleb Hossen Manik

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