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Annals of Mathematical Sciences and Applications
Volume 9 (2024)
Number 2
Uncertainty analysis of the tumour population logistic model in a fuzzy context
Pages: 309 – 339
DOI: https://dx.doi.org/10.4310/AMSA.2024.v9.n2.a2
Authors
Abstract
This research depicts the tumour logistic equation in an uncertain environment, with the tumour inception, growth rate, both the inception and growth rate being fuzzy, and all the parameters beingfuzzy determinants to minimise tumour ambiguity and get the degree of accuracy. The author here perceives the cumulative tumour at a specific time as fuzzy, with the possibility distribution function(PDF) being analysed by the tumour inception $(n_0)$ growth rate $(\gamma)$, and threshold $(K)$. Additionally, this work indicates the tumour’s anticipated cell population in the maximal time interval. Finally, numerically simulated results relying on the logistic tumour growth model in an uncertain environment are been acquired using MATLAB and illustrated to verify the model’s accuracy.
Keywords
tumour modelling, fuzzy mathematics, fuzzy logistic growth equation, possibility distribution function
2010 Mathematics Subject Classification
Primary 34A07, 90Cxx, 93A30. Secondary 00A71, 03E72.
Received 5 April 2023
Accepted 15 May 2023
Published 15 August 2024