求解分数物理模型的 "Sumudu Transform Pade "近似法

Hamdy Abdl-Rahim
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引用次数: 0

摘要

本研究提供了一种名为 "Sumudu Transform Pade' Approximation Method (STPAM) "的最新技术来处理分数物理模型。它由 Pade'近似法(PAM)和 Sumudu 变换法(STM)组成。Sumudu 变换 Pade'近似法(STPAM)通过在 Sumudu 变换法链解中对 Pade'方法进行分层,提高了截断 Maclaurin 数列的累积率。采用了卡普托分数导数。这对于模拟具有非局部特征的问题和考虑过去相互作用的现象是必要的。卡普托分数算子的分析适应性更强,可以处理初值和边界值问题。本研究的主要目的是使用苏姆杜变换帕德近似法(STPAM)来求解物理学中出现的分数模型。我们使用苏姆杜变换法(STM)求解分数物理模型,并将结果与精确解和近似帕德近似法(PAM)进行比较,以评估苏姆杜变换帕德近似法(STPAM)的质量。研究结果凸显了 STPAM 的优势,包括易用性、有效性、通用性、简洁性、可打包性、质量和清晰度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sumudu Transform Pade' Approximation Method for Solving Fractional Physical Models
:This study offers a recent technique named the Sumudu Transform Pade' Approximation Method (STPAM) to treat fractional physical models. It comprises the Pade' Approximation Method (PAM) and the Sumudu Transform Method (STM).The Sumudu Transform Pade' Approximation Method (STPAM) enhances the accumulation rate of the truncated Maclaurin series by stratifying the Pade' method in the Sumudu transform method chain solution. The Caputo's fractional derivative was employed. It is necessary for simulating issues with non-local features and phenomena that account for interactions in the past. The Caputo fractional operator is more adaptable for analysis and can handle initial and boundary value issues. The principal objective of the study is to use the Sumudu Transform Pade' Approximation Method (STPAM) to solve fractional models that arise in physics. We solved fractional physical models using the Sumudu transform method (STM) and compared the results to the exact solutions and the approximate Pade' approximation method (PAM) to assess the quality of the Sumudu Transform Pade' Approximation Method (STPAM). The findings highlight STPAM's advantages, including its ease of use, effectiveness, universality, cleanliness, packability, quality, and clarity.
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