Abstract
First known case of Covid-19 was found out in Wuhan, China in December, 2019. The virus itself is a novel virus, its harshness is unpredictable, its transmission ability is extremely powerful and its incubation period is comparatively larger. Covid-19 pandemic affected world health and socio-economy severely. So, it is required to know earlier whether the condition is continuing to get worse or how to scale up medical facilities like tracing, testing, treatment, quarantine etc. to fight against it. Early outbreak data for Novel Corona virus attack in India has been considered for this work. The trend of confirmed cases, recovery cases and deceased cases using deep neural network (DNN) and support vector regression (SVR) using Gaussian and exponential kernel functions are modeled. A comparative view of the prediction analysis is also considered.
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Pal, M.N., Roy, S., Kundu, S., Choudhury, S.S. (2020). Visualization and Prediction of Trends of Covid-19 Pandemic During Early Outbreak in India Using DNN and SVR. In: Hassanien, AE., Dey, N., Elghamrawy, S. (eds) Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach. Studies in Big Data, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-55258-9_4
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DOI: https://doi.org/10.1007/978-3-030-55258-9_4
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