An Inverse Random Source Problem for a Time Fractional Fourth‐Order Parabolic Equation Under Samarskii–Ionkin Boundary Condition

ABSTRACT This paper is devoted to solve an inverse random source problem for the fourth‐order partial differential equation under Samarskii–Ionkin boundary condition, where the source is driven by a fractional Brownian motion (fBm). The fractional time derivative is described in the Hilfer sense. The regularity of the direct problem, along with the uniqueness, instability, and conditional stability of the inverse source problem, is proved. To address this instability, we apply a generalized quasi‐reversibility regularization method (GQRRM), achieving stable numerical solutions and giving error estimates. Finally, numerical experiments demonstrate the effectiveness of the regularization method.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-09-03
DOI
https://doi.org/10.1002/mma.70076
Primary Topic
Fractional Differential Equations Solutions
Type
article
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article

An Inverse Random Source Problem for a Time Fractional Fourth‐Order Parabolic Equation Under Samarskii–Ionkin Boundary Condition

Jian Lu, Hao Cheng
Mathematical Methods in the Applied Sciences
Fractional Differential Equations Solutions
article

An Inverse Random Source Problem for a Time Fractional Fourth‐Order Parabolic Equation Under Samarskii–Ionkin Boundary Condition

Jian Lu, Hao Cheng
article en

Abstract

ABSTRACT This paper is devoted to solve an inverse random source problem for the fourth‐order partial differential equation under Samarskii–Ionkin boundary condition, where the source is driven by a fractional Brownian motion (fBm). The fractional time derivative is described in the Hilfer sense. The regularity of the direct problem, along with the uniqueness, instability, and conditional stability of the inverse source problem, is proved. To address this instability, we apply a generalized quasi‐reversibility regularization method (GQRRM), achieving stable numerical solutions and giving error estimates. Finally, numerical experiments demonstrate the effectiveness of the regularization method.

Mathematical Methods in the Applied SciencesVol. 48(17)
Jiangnan University (CN)
Openalex Percentile: Top 73%
Fractional Differential Equations Solutions
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