Year: 2023
Author: Jianguo Huang, Shengbiao Ma, Haoqin Wang
East Asian Journal on Applied Mathematics, Vol. 13 (2023), Iss. 2 : pp. 420–434
Abstract
This paper is concerned with a hybrid method for three-dimensional semilinear elliptic equations, constructed by combining the ideas presented in [Huang et al., J. Comput. Phys. 419 (2020)] and [Zhang et al., Comput. Math. Appl. 80 (2020)]. The convergence rate analysis indicates that the method converges rapidly. Numerical examples support the theoretical results and show that the method proposed outperforms the purely deep learning-based and traditional iterative methods.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.2022-264.091122
East Asian Journal on Applied Mathematics, Vol. 13 (2023), Iss. 2 : pp. 420–434
Published online: 2023-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 15
Keywords: Deep learning iterative method semi-linear elliptic equations convergence rate analysis.