Solving Fractional Differential Equations Using Differential Transform Method and Fermat Collocation Method: Formulation Convergence and Error Analysis

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
A. S. Mohamed
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引用次数: 0

Abstract

This paper shows how to solve fractional differential equations (FDEs) with two methods: the differential transform method (DTM) and the Fermat collocation method (FCM). Provides a comprehensive overview of the formulation and features of both algorithms. The first method turns the differential equation and its boundary conditions into a series using a step-by-step process, then obtains the exact solution. The second method converts the equation into a set of simpler equations for the coefficients. We used Fermat polynomials (FPs) as the basis functions and evaluated the coefficients using matrix techniques. The paper also looks at how well these methods work and what kind of errors to expect. An analysis of the convergence behavior and the associated computational complexity is also presented in the paper. We solved many test problems using our methods and compared the errors with those obtained from other methods. The results of this comparison highlight the superior accuracy and effectiveness of the proposed techniques over alternative methods.

用微分变换法和费马配点法求解分数阶微分方程:公式收敛与误差分析
本文用微分变换法(DTM)和费马配点法(FCM)两种方法求解分数阶微分方程。提供了两个算法的公式和特点的全面概述。第一种方法是将微分方程及其边界条件逐步转化为级数,然后求出精确解。第二种方法将方程转换成一组更简单的系数方程。我们使用费马多项式(FPs)作为基函数,并使用矩阵技术评估系数。这篇论文还研究了这些方法的效果,以及预期会出现什么样的错误。本文还分析了该算法的收敛性和计算复杂度。我们用我们的方法解决了许多测试问题,并与其他方法得到的误差进行了比较。这一比较的结果突出了优越的准确性和有效性所提出的技术优于替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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