时间分数费雪方程的精确数值方法及其分析

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Soft Computing Pub Date : 2024-07-26 DOI:10.1007/s00500-024-09885-8
Pradip Roul, Vikas Rohil
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引用次数: 0

摘要

本文旨在开发一种近似非线性时间分数广义费雪方程(TFGF)解的最优超融合数值方法。模型问题中的时间分数导数是在 Caputo 的意义上考虑的,并使用 \(L2-1_{\sigma }\) 方案进行近似。空间离散化采用最优超收敛五次 B 样条(OSQB)技术。为了推导该方法,利用样条交替关系生成了原始问题半离散方程的高阶扰动。分析了该方法的收敛性和稳定性,证明该方法的收敛速度为 \(O(\Delta t^{2}+\Delta x^6)\),其中 \(\Delta x\) 和 \(\Delta t\) 分别是空间和时间上的步长。我们提供了三个数值示例来证明所提方法的鲁棒性。我们的方法与文献中的现有方法进行了比较,并提供了本方案的计算时间。
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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An accurate numerical method and its analysis for time-fractional Fisher’s equation

This article aims to develop an optimal superconvergent numerical method for approximating the solution of the nonlinear time-fractional generalized Fisher’s (TFGF) equation. The time-fractional derivative in the model problem is considered in the sense of Caputo and is approximated using the \(L2-1_{\sigma }\) scheme. Spatial discretization is performed using an optimal superconvergent quintic B-spline (OSQB) technique. To derive the method, a high-order perturbation of the semi-discretized equation of the original problem is generated using spline alternate relations. Convergence and stability of the method are analyzed, demonstrating that the method converges with \(O(\Delta t^{2}+\Delta x^6)\), where \(\Delta x\) and \(\Delta t\) are step sizes in space and time, respectively. Three numerical examples are provided to demonstrate the robustness of the proposed method. Our method is compared with an existing method in the literature and the elapsed computational time for the present scheme is provided.

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来源期刊
Soft Computing
Soft Computing 工程技术-计算机:跨学科应用
CiteScore
8.10
自引率
9.80%
发文量
927
审稿时长
7.3 months
期刊介绍: Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
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