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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM25055
Volume:
7 |
8 |
Aug 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This is based on COVID 19 patients data on accessible big-data systems that include a set of tools and technique to load, extract, and improve dissimilar data while leveraging the immensely parallel processing power to perform complex transformations and analysis. In this paper, we have mainly focused on the R programming along with the logistic and the exponential models at each state (restricting to only those states with enough data for prediction). The R programming takes into account the possibility that an infected individual can return to the susceptible class on recovery because the disease confers no long-standing immunity against reinfection.
KEYWORDS
Publication Date
5/7/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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