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In this work, we have discussed about SIR model with model using Michaelis – Menten Functional response and explained the deviations in the infections and the recovery from COVID-19 for the non-diabetic and diabetic patients. We also discussed about the uncertainty rate of change variables, so by using the concept of Fuzzy I have reduced the uncertainty and found a better model using Trapezoidal Fuzzy Numbers (TFN) and Basic Defuzzification Method (BDM). Also I have discussed about the equilibrium points and stability of the model and compared the variation between the crisp model and the Fuzzy model by using Matlab Software.
Keywords:
SIR model –TFN - BDM – Stability – Diabetics.
Cite Article:
"The Impact of Fuzzy Uncertainty On The Diabetic And Non Diabetic Covid Model", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 2, page no.276 - 282, February-2023, Available :http://www.ijrti.org/papers/IJRTI2302046.pdf
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000205153
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator