In this paper, we develop a novel coupled numerical method for time-fractional convection-diffusion equations. First, in the temporal dimension, a derivative-based linear interpolation is utilized to approximate the time partial derivative. Then, we construct a high-order approximate scheme for the temporal fractional derivative, which transforms the original partial differential equation into a semi-discrete ordinary differential system involving only spatial variables. In the spatial dimension, a standard orthogonal basis is constructed by using compressed Legendre polynomials. Combining the concept of $ \varepsilon $-approximate solutions, we derive the numerical solution of the semi-discrete scheme. Convergence analysis and numerical experiments demonstrate that the proposed algorithm achieves second-order convergence in time, and the spatial convergence accuracy improves as the Legendre polynomial degree and compression level increase.
Citation: Hui Zhu, Lei Yang, Ruimin Zhang, Yuntao Jia. A coupled numerical method for time-fractional convection-diffusion equations based on compressed Legendre polynomials[J]. AIMS Mathematics, 2026, 11(7): 19488-19515. doi: 10.3934/math.2026792
In this paper, we develop a novel coupled numerical method for time-fractional convection-diffusion equations. First, in the temporal dimension, a derivative-based linear interpolation is utilized to approximate the time partial derivative. Then, we construct a high-order approximate scheme for the temporal fractional derivative, which transforms the original partial differential equation into a semi-discrete ordinary differential system involving only spatial variables. In the spatial dimension, a standard orthogonal basis is constructed by using compressed Legendre polynomials. Combining the concept of $ \varepsilon $-approximate solutions, we derive the numerical solution of the semi-discrete scheme. Convergence analysis and numerical experiments demonstrate that the proposed algorithm achieves second-order convergence in time, and the spatial convergence accuracy improves as the Legendre polynomial degree and compression level increase.
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