Anandan, R. and Nalini, T. and Chiwhane, Shwetambari and Shanmuganathan, M. and Radhakrishnan, P. (2023) COVID-19 outbreak data analysis and prediction. Measurement: Sensors, 25. p. 100585. ISSN 26659174
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Abstract
Covid-19 is a novel pandemic disease with no potential vaccine treatment or medicine, the world is facing
currently as of now. The death toll has increased to several lakhs and recovery rate is comparatively very less,
was initially spotted in Wuhan (China). This spreads through close contact with people and socializing. The
number of infected people varies with different parts of the world In our particular country India we are going
through the lock down period which is the only vaccine to promote “social distancing” The hurdle arose due to
the widespread of corona is major economy loss in combo with innocent lives. In this manuscript, we are
visualizing the dataset which is publicly available to map, differentiate and separate the data in order to
segregate the places that are most prone and perform basic regression to identify and predict the increasability of
the counts from the dataset.
Item Type: | Article |
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Subjects: | Computer Science Engineering > Computer Network |
Divisions: | Computer Science Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 20 Sep 2024 09:50 |
Last Modified: | 20 Sep 2024 09:50 |
URI: | https://ir.vistas.ac.in/id/eprint/6728 |