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To broaden the range of applicability of variable-order fractional differential models, reliable numerical approaches are needed to solve the model equation. In this paper, we develop Laguerre spectral collocation methods for solving…

Numerical Analysis · Mathematics 2018-04-05 M. A. Zaky , E. H. Doha , T. M. Taha , D. Baleanu

In this paper, using a pseudospectral approach, we develop operational matrices based on the shifted Chebyshev polynomials to approximate numerically Caputo fractional derivatives and Riemann-Liouville fractional integrals. In order to make…

Numerical Analysis · Mathematics 2025-11-17 Francisco de la Hoz , Peru Muniain

A framework for Chebyshev spectral collocation methods for the numerical solution of functional and delay differential equations (FDEs and DDEs) is described. The framework combines interpolation via the barycentric resampling matrix with a…

Numerical Analysis · Mathematics 2024-08-15 Nicholas Hale

We present numerical solutions for differential equations by expanding the unknown function in terms of Chebyshev polynomials and solving a system of linear equations directly for the values of the function at the extrema (or zeros) of the…

Computational Physics · Physics 2009-10-31 Bogdan Mihaila , Ioana Mihaila

In this work we study a multi-step scheme on time-space grids proposed by W. Zhao et al. [28] for solving backward stochastic differential equations, where Lagrange interpolating polynomials are used to approximate the time-integrands with…

Numerical Analysis · Mathematics 2018-09-05 Long Teng , Aleksandr Lapitckii , Michael Günther

This paper presents a novel approach for numerical solution of a class of fourth order time fractional partial differential equations (PDE's). The finite difference formulation has been used for temporal discretization, whereas, the space…

Numerical Analysis · Mathematics 2018-09-18 Muhammad Abbas

In this paper, the boundary element method is combined with Chebyshev operational matrix technique to solve two-dimensional multi-order time-fractional partial differential equations; nonlinear and linear in respect to spatial and temporal…

Analysis of PDEs · Mathematics 2020-03-31 Moein Khalighi , Mohammad Amirian Matlob , Alaeddin Malek

In this paper invariant subspace method has been employed for solving linear and non-linear fractional partial differential equations involving Caputo derivative. A variety of illustrative examples are solved to demonstrate the…

Analysis of PDEs · Mathematics 2017-04-18 Sangita Choudhary , Varsha Daftardar-Gejji

A spectral decomposition method is used to obtain solutions to a class of nonlinear differential equations. We extend this approach to the analysis of the fractional form of these equations and demonstrate the method by applying it to the…

Mathematical Physics · Physics 2015-08-14 Malgorzata Turalska , Bruce J. West

A method for the numerical solution of variable order (VO) fractional differential equations (FDE) is presented. The method applies to linear as well as to nonlinear VO-FDEs. The Caputo type VO fractional derivative is employed. First, an…

Numerical Analysis · Mathematics 2018-05-08 John T. Katsikadelis

In this paper, we study a fast and linearized finite difference method to solve the nonlinear time-fractional wave equation with multi fractional orders. We first propose a discretization to the multi-term Caputo derivative based on the…

Numerical Analysis · Mathematics 2019-02-22 Pin Lyu , Yuxiang Liang , Zhibo Wang

We study an approximation method to solve nonlinear multi-term fractional differential equations with initial conditions or boundary conditions. First, we transform the nonlinear multi-term fractional differential equations with initial…

Mathematical Physics · Physics 2013-03-21 Hui-Chol Choe , Yong-Suk Kang

In the paper titled "New numerical approach for fractional differential equations" by A. Atangana and K.M. Owolabi [Math. Model. Nat. Phenom., 13(1), 2018], it is presented a method for the numerical solution of some fractional differential…

Numerical Analysis · Mathematics 2019-02-27 Roberto Garrappa

An adaptive finite difference scheme for variable-order fractional-time subdiffusion equations in the Caputo form is studied. The fractional time derivative is discretized by the L1 procedure but using nonhomogeneous timesteps. The size of…

Numerical Analysis · Mathematics 2024-09-20 Joaquín Quintana-Murillo , Santos Bravo Yuste

We introduce a new numerical method, based on Bernoulli polynomials, for solving multiterm variable-order fractional differential equations. The variable-order fractional derivative was considered in the Caputo sense, while the…

Numerical Analysis · Mathematics 2021-11-18 Somayeh Nemati , Pedro M. Lima , Delfim F. M. Torres

This paper presents a class of Two-Step General Linear Methods for the numerical solution of Retarded Functional Differential Equations. Explicit methods up to order five are constructed. To avoid order reduction for mildly stiff problems…

Numerical Analysis · Mathematics 2017-04-18 Anton Tuzov

This paper presents a class of Two-Step General Linear Methods for the numerical solution of Retarded Functional Differential Equations. Explicit methods up to order five are constructed. To avoid order reduction for mildly stiff problems…

Numerical Analysis · Mathematics 2009-01-30 Anton Tuzov

In this paper, a non-polynomial spectral Petrov-Galerkin method and associated collocation method for substantial fractional differential equations (FDEs) are proposed, analyzed, and tested. We extend a class of generalized Laguerre…

Numerical Analysis · Mathematics 2014-08-27 Can Huang , Qingshuo Song , Zhimin Zhang

The multi-term time-fractional mixed diffusion-wave equations (TFMDWEs) are considered and the numerical method with its error analysis is presented in this paper. First, a $L2$ approximation is proved with first order accuracy to the…

Numerical Analysis · Mathematics 2016-07-26 Zhao-peng Hao , Guang Lin

In this paper, a new deep-learning architecture for solving the non-linear Falkner-Skan equation is proposed. Using Legendre and Chebyshev neural blocks, this approach shows how orthogonal polynomials can be used in neural networks to…

Machine Learning · Computer Science 2023-08-08 Alireza Afzal Aghaei , Kourosh Parand , Ali Nikkhah , Shakila Jaberi