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A comparative study between discrete stochastic arithmetic and floating-point arithmetic to validate the results of fractional order model of malaria infection

  • Samad Noeiaghdam*
  • , Aliona Dreglea
  • , Hüseyin Işık
  • , Muhammad Suleman
  • *Corresponding author for this work
  • South Ural State University
  • Irkutsk National Research Technical University
  • Bandırma Onyedi Eylül University
  • COMSATS University Islamabad

Research output: Contribution to journalArticlepeer-review

Abstract

The researchers aimed to study the nonlinear fractional order model of malaria infection based on the Caputo-Fabrizio fractional derivative. The homotopy analysis transform method (HATM) is applied based on the floating-point arithmetic (FPA) and the discrete stochastic arithmetic (DSA). In the FPA, to show the accuracy of the method we use the absolute error which depends on the exact solution and a positive value ε. Because in real life problems we do not have the exact solution and the optimal value of ε, we need to introduce a new condition and arithmetic to show the efficiency of the method. Thus the CESTAC (Controle et Estimation Stochastique des Arrondis de Calculs) method and the CADNA (Control of Accuracy and Debugging for Numerical Applications) library are applied. The CESTAC method is based on the DSA. Also, a new termination criterion is used which is based on two successive approximations. Using the CESTAC method we can find the optimal approximation, the optimal error and the optimal iteration of the method. The main theorem of the CESTAC method is proved to show that the number of common significant digits (NCSDs) between two successive approximations are almost equal to the NCSDs of the exact and approximate solutions. Plotting several graphs, the regions of convergence are demonstrated for different number of iterations k = 5, 10. The numerical results based on the simulated data show the advantages of the DSA in comparison with the FPA.

Original languageEnglish
Article number1435
JournalMathematics
Volume9
Issue number12
DOIs
StatePublished - 2 Jun 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • CADNA library (Control of Accuracy and Debugging for Numerical Applications)
  • CESTAC method (Controle et Estimation Stochastique des Arrondis de Calculs)
  • Caputo-Fabrizio derivative
  • Homotopy analysis transform method (HATM)
  • Model of malaria infection

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