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  Published Paper Details:

  Paper Title

THE IMPROVED MATHEMATICAL MODEL FOR CONTINUOUS FORECASTING OF THE EPIDEMIC

  Authors

  Manuraj V R,  Dr. S. Shankar,  Dr.S. Uma,  Priya S

  Keywords

Machine learning, Cloud computing

  Abstract


COVID-19 began in China in December 2019. As of January 2021, over a hundred million instances had been reported worldwide, leaving a deep socio-economic impact globally. Current investigation studies determined that artificial intelligence (AI) can play a key role in reducing the effect of the virus spread. The prediction of COVID-19 incidence in different countries and territories is important because it serves as a guide for governments, healthcare providers, and the general public in developing management strategies to battle the disease. The prediction proved beneficial in the early months of 2020 to alert nations and territories in danger of an outbreak, allowing them to take preventative measures. Despite the fact that the COVID-19 outbreak has expanded to practically every location on the planet, the prediction has value in terms of monitoring the intensity of the spread and recovery, as well as determining the likelihood of a sequel or tertiary epidemic. COVID-19, like influenza, could become a seasonal or recurring epidemic in the future. COVID-19 activity must so be predicted and monitored now and in the future.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT22A6223

  Paper ID - 221369

  Page Number(s) - b790-b792

  Pubished in - Volume 10 | Issue 6 | June 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Manuraj V R,  Dr. S. Shankar,  Dr.S. Uma,  Priya S,   "THE IMPROVED MATHEMATICAL MODEL FOR CONTINUOUS FORECASTING OF THE EPIDEMIC", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 6, pp.b790-b792, June 2022, Available at :http://www.ijcrt.org/papers/IJCRT22A6223.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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