2018
DOI: 10.1002/num.22253
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A local radial basis function collocation method to solve the variable‐order time fractional diffusion equation in a two‐dimensional irregular domain

Abstract: The local radial basis function (RBF) method is a promising solver for variable‐order time fractional diffusion equation (TFDE), as it overcomes the computational burden of the traditional global method. Application of the local RBF method is limited to Fickian diffusion, while real‐world diffusion is usually non‐Fickian in multiple dimensions. This article is the first to extend the application of the local RBF method to two‐dimensional, variable‐order, time fractional diffusion equation in complex shaped dom… Show more

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Cited by 30 publications
(16 citation statements)
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References 39 publications
(70 reference statements)
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“…Spectral methods have also been applied to VO-FDEs which have smooth exact solutions and the classical Jacobi polynomials (typically Legendre or Chebyshev polynomials) were used as approximation bases [99][100][101][102][103][104][105][106][107]. Weighted Jacobi polynomials of the form (1 ± x) μ P a,b j (x) and…”
Section: (C) Solution Methods For Variable-order Fractional Differential Equationsmentioning
confidence: 99%
“…Spectral methods have also been applied to VO-FDEs which have smooth exact solutions and the classical Jacobi polynomials (typically Legendre or Chebyshev polynomials) were used as approximation bases [99][100][101][102][103][104][105][106][107]. Weighted Jacobi polynomials of the form (1 ± x) μ P a,b j (x) and…”
Section: (C) Solution Methods For Variable-order Fractional Differential Equationsmentioning
confidence: 99%
“…Fu et al [38] applied the method of approximate particular solutions for fractional diffusion model. Wei et al [121] employed the local radial basis function method to solve the VO time fractional diffusion equation. Li and Wu [63] proposed a reproducing kernel method; afterward, they solved VO fractional boundary value problems for fractional differential equations based on the reproducing kernel theory.…”
Section: Numerical Methods For Time Fdesmentioning
confidence: 99%
“…Meanwhile, although computation power has grown exponentially and mathematical models are much more complex than those in early work, the basic problems of considering strict constraints and unreliable assumptions still remain. To solve these problems, multidisciplinary efforts are needed, such as efficient solution schemes for FADEs on which efforts have been devoted by many experts (Baeumer et al, 2018; Cartalade et al, 2019; Hajipour et al, 2019; Hussain & Haq, 2019; Jannelli et al, 2019; X. T. Liu, Sun, Zhang, & Fu, 2019; X. T. Liu, Sun, Zhang, Zheng, & Yu, 2019; Wei, Chen, Zhang, Wei, & Garrard, 2018; Yi & Sun, 2019; Yu et al, 2018).…”
Section: Challenges and Suggestions For Future Workmentioning
confidence: 99%