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一种使用积分变换和残差函数来求解含卡普托导数的非线性偏分数阶微分方程的新技术。

A novel technique using integral transforms and residual functions for nonlinear partial fractional differential equations involving Caputo derivatives.

作者信息

Khan Zareen A, Riaz Muhammad Bilal, Liaqat Muhammad Imran, Akgül Ali

机构信息

Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

IT4Innovations, VSB-Technical University of Ostrava, Ostrava, Czech Republic.

出版信息

PLoS One. 2024 Dec 19;19(12):e0313860. doi: 10.1371/journal.pone.0313860. eCollection 2024.

Abstract

Fractional nonlinear partial differential equations are used in many scientific fields to model various processes, although most of these equations lack closed-form solutions. For this reason, methods for approximating solutions that occasionally yield closed-form solutions are crucial for solving these equations. This study introduces a novel technique that combines the residual function and a modified fractional power series with the Elzaki transform to solve various nonlinear problems within the Caputo derivative framework. The accuracy and effectiveness of our approach are validated through analyses of absolute, relative, and residual errors. We utilize the limit principle at zero to identify the coefficients of the series solution terms, while other methods, including variational iteration, homotopy perturbation, and Adomian, depend on integration. In contrast, the residual power series method uses differentiation, and both approaches encounter difficulties in fractional contexts. Furthermore, the effectiveness of our approach in addressing nonlinear problems without relying on Adomian and He polynomials enhances its superiority over various approximate series solution techniques.

摘要

分数阶非线性偏微分方程在许多科学领域中用于对各种过程进行建模,尽管这些方程中的大多数都缺乏封闭形式的解。因此,偶尔能产生封闭形式解的近似解方法对于求解这些方程至关重要。本研究引入了一种新颖的技术,该技术将残差函数和修正的分数幂级数与埃尔扎基变换相结合,以在卡普托导数框架内解决各种非线性问题。我们通过分析绝对误差、相对误差和残差误差来验证方法的准确性和有效性。我们利用零处的极限原理来确定级数解项的系数,而其他方法,包括变分迭代、同伦摄动和阿多米安方法,都依赖于积分。相比之下,残差幂级数方法使用微分,并且这两种方法在分数阶情况下都会遇到困难。此外,我们的方法在不依赖阿多米安多项式和何多项式的情况下解决非线性问题的有效性增强了其相对于各种近似级数解技术的优越性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b0/11658600/78f70297c46e/pone.0313860.g001.jpg

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