Advanced analytical treatment of fractional logistic equations based on residual error functions

Saleh Alshammari, Mohammed Al-Smadi, Mohammad Al Shammari, Ishak Hashim, Mohd Almie Alias

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this article, an analytical reliable treatment based on the concept of residual error functions is employed to address the series solution of the differential logistic system in the fractional sense. The proposed technique is a combination of the generalized Taylor series and minimizing the residual error function. The solution methodology depends on the generation of a fractional expansion in an effective convergence formula, as well as on the optimization of truncated errors, Resqjt, through the use of repeated Caputo derivatives without any restrictive assumptions of system nature. To achieve this, some logistic patterns are tested to demonstrate the reliability and applicability of the suggested approach. Numerical comparison depicts that the proposed technique has high accuracy and less computational effect and is more efficient.

Original languageEnglish
Article number7609879
JournalInternational Journal of Differential Equations
Volume2019
DOIs
Publication statusPublished - 1 Jan 2019

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Logistic Equation
Error function
Logistics
Fractional
Caputo Derivative
Taylor series
Series Solution
Numerical Comparisons
High Accuracy
Optimization
Methodology
Demonstrate
Derivatives
Concepts

ASJC Scopus subject areas

  • Analysis
  • Applied Mathematics

Cite this

Advanced analytical treatment of fractional logistic equations based on residual error functions. / Alshammari, Saleh; Al-Smadi, Mohammed; Al Shammari, Mohammad; Hashim, Ishak; Alias, Mohd Almie.

In: International Journal of Differential Equations, Vol. 2019, 7609879, 01.01.2019.

Research output: Contribution to journalArticle

Alshammari, Saleh ; Al-Smadi, Mohammed ; Al Shammari, Mohammad ; Hashim, Ishak ; Alias, Mohd Almie. / Advanced analytical treatment of fractional logistic equations based on residual error functions. In: International Journal of Differential Equations. 2019 ; Vol. 2019.
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