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Research Article | Open Access

A novel numerical method for stochastic conformable fractional differential systems

Aisha F. Fareed1Emad A. Mohamed1Mokhtar Aly2Mourad S. Semary3,4( )
Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj 11942, Saudi Arabia
Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Bellavista 7, Santiago 8420524, Chile
Basic Sciences Department, Faculty of Engineering, Badr University in Cairo, Cairo 11829, Egypt
Basic Engineering Sciences Department, Benha Faculty of Engineering, Benha University, Benha 13512, Egypt
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Abstract

This study introduced the conformable fractional discrete Temimi–Ansari method (CFDTAM), a novel numerical framework designed to solve fractional stochastic nonlinear differential equations with enhanced efficiency and accuracy. By leveraging the conformable fractional derivative (CFD), the CFDTAM unifies classical and fractional-order systems while maintaining computational simplicity. The method's efficacy was demonstrated through applications to a stochastic population model and the Brusselator system, showcasing its ability to handle nonlinear dynamics with high precision. A comprehensive convergence analysis was also conducted to validate the reliability and stability of the proposed method. All computations were performed using Mathematica 12 software, ensuring accuracy and consistency in numerical simulations. CFDTAM sets a new benchmark in fractional stochastic modeling, paving the way for advancements in partial differential equations, delay systems, and hybrid models.

CLC number: 34A08, 65L05, 60H10

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AIMS Mathematics
Pages 7509-7525

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Cite this article:
Fareed AF, Mohamed EA, Aly M, et al. A novel numerical method for stochastic conformable fractional differential systems. AIMS Mathematics, 2025, 10(3): 7509-7525. https://doi.org/10.3934/math.2025345

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Received: 07 January 2025
Revised: 05 March 2025
Accepted: 07 March 2025
Published: 15 March 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)