GEPINN: An innovative hybrid method for a symbolic solution to the Lane–Emden type equation based on grammatical evolution and physics-informed neural networks-Reference-Cited by-同舟云学术

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GEPINN: An innovative hybrid method for a symbolic solution to the Lane–Emden type equation based on grammatical evolution and physics-informed neural networks

Published:2024-07 Issue: Volume:48 Page:100846
ISSN:2213-1337
Container-title:Astronomy and Computing
language:en
Short-container-title:Astronomy and Computing

Author:

Dana Mazraeh Hassan,Parand Kourosh^ORCID

Publisher

Elsevier BV

Reference90 articles.

1. On the analytic solution of the Lane-Emden equation;Adomian;Found. Phys. Lett.,1995

2. Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model;Ahmad;Neural Comput. Appl.,2017

3. Bio-inspired computational heuristics to study Lane–Emden systems arising in astrophysics model;Ahmad;SpringerPlus,2016

4. Solutions of the Singular IVPs of Lane-Emden type equations by combining Laplace transformation and perturbation technique;Aminikhah;Nonlinear Eng.,2018

5. Machine learning through physics–Informed neural networks: Progress and challenges;Antonion;Acad. J. Sci. Technol.,2024

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