Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules

This research introduces a novel and robust numerical approach, the stochastic improved Simpson Method, specifically developed to solve Itô and Stratonovich stochastic nonlinear system of differential equations with fractional order. By extending the classical Simpson’s one-third rule with the expli...

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Main Authors: Fareed Aisha F., Semary Mourad S.
Format: Article
Language:English
Published: De Gruyter 2025-02-01
Series:Nonlinear Engineering
Subjects:
Online Access:https://doi.org/10.1515/nleng-2024-0070
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author Fareed Aisha F.
Semary Mourad S.
author_facet Fareed Aisha F.
Semary Mourad S.
author_sort Fareed Aisha F.
collection DOAJ
description This research introduces a novel and robust numerical approach, the stochastic improved Simpson Method, specifically developed to solve Itô and Stratonovich stochastic nonlinear system of differential equations with fractional order. By extending the classical Simpson’s one-third rule with the explicit product integration rectangle rule, the proposed method efficiently handles fractional derivatives of orders between 0 and 1, based on the Caputo derivative. The novelty of this approach lies in its enhanced accuracy and stability in addressing the unique challenges posed by both Itô and Stratonovich systems, outperforming traditional numerical techniques. Rigorous order analysis, conducted with Mathematica 12 software, demonstrates the robustness and precision of the method. Its effectiveness is further validated through four distinct numerical case studies, highlighting its superior performance in solving stochastic nonlinear system of differential equations with fractional order.
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series Nonlinear Engineering
spelling doaj-art-d2bf940fc5ca46ee8404322923e5d55a2025-08-20T02:48:30ZengDe GruyterNonlinear Engineering2192-80292025-02-01141p. 12210.1515/nleng-2024-0070Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rulesFareed Aisha F.0Semary Mourad S.1Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj, 11942, Saudi ArabiaDepartment of Basic Engineering Sciences, Benha Faculty of Engineering, Benha University, Benha, EgyptThis research introduces a novel and robust numerical approach, the stochastic improved Simpson Method, specifically developed to solve Itô and Stratonovich stochastic nonlinear system of differential equations with fractional order. By extending the classical Simpson’s one-third rule with the explicit product integration rectangle rule, the proposed method efficiently handles fractional derivatives of orders between 0 and 1, based on the Caputo derivative. The novelty of this approach lies in its enhanced accuracy and stability in addressing the unique challenges posed by both Itô and Stratonovich systems, outperforming traditional numerical techniques. Rigorous order analysis, conducted with Mathematica 12 software, demonstrates the robustness and precision of the method. Its effectiveness is further validated through four distinct numerical case studies, highlighting its superior performance in solving stochastic nonlinear system of differential equations with fractional order.https://doi.org/10.1515/nleng-2024-0070stochastic differential equationswhite noisefractional-order systemssimpson’s rulecaputo derivative
spellingShingle Fareed Aisha F.
Semary Mourad S.
Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
Nonlinear Engineering
stochastic differential equations
white noise
fractional-order systems
simpson’s rule
caputo derivative
title Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
title_full Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
title_fullStr Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
title_full_unstemmed Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
title_short Stochastic improved Simpson for solving nonlinear fractional-order systems using product integration rules
title_sort stochastic improved simpson for solving nonlinear fractional order systems using product integration rules
topic stochastic differential equations
white noise
fractional-order systems
simpson’s rule
caputo derivative
url https://doi.org/10.1515/nleng-2024-0070
work_keys_str_mv AT fareedaishaf stochasticimprovedsimpsonforsolvingnonlinearfractionalordersystemsusingproductintegrationrules
AT semarymourads stochasticimprovedsimpsonforsolvingnonlinearfractionalordersystemsusingproductintegrationrules