Numerical learning approximation of time-fractional sub diffusion model on a semi-infinite domain

Zeinab Hajimohammadi and Kourosh Parand

Chaos, Solitons & Fractals, 2021, vol. 142, issue C

Abstract: The propose of this research is to apply a novel numerical learning approximation of time-fractional sub diffusion model on a semi-infinite domain. This model is a nonlinear fractional differential equation in two unbounded dimensions. Combination of Least Squares Support Vector Regression (LSSVR) based on generalized Laguerre Functions kernel and collocation/Galerkin method is applied to obtain the solutions. The marching in time technique is applied for time discretization. Numerical results verify that proposed methods have high convergence and performance.

Keywords: Time-fractional sub diffusion model; Least squares support vector regression; Generalized Laguerre functions; Collocation method; Galerkin method (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920308274

DOI: 10.1016/j.chaos.2020.110435

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