A Physics-Informed Neural Network model combined Pell–Lucas polynomials for solving the Lane–Emden type equation

This publication has 27 references indexed in Scilit:

• Physics-informed neural networks with parameter asymptotic strategy for learning singularly perturbed convection-dominated problem
  Computers & Mathematics with Applications, 2023
• Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients
  Journal of Computational and Applied Mathematics, 2023
• A New Constructing Rational Functions Method For Solving Lane−Emden Type Equations
  Neural Processing Letters, 2022
• A novel sequential method to train physics informed neural networks for Allen Cahn and Cahn Hilliard equations
  Computer Methods in Applied Mechanics and Engineering, 2022
• Application of Legendre Neural Network for solving ordinary differential equations
  Applied Soft Computing, 2016
• Unsupervised kernel least mean square algorithm for solving ordinary differential equations
  Neurocomputing, 2011
• A comprehensive survey on functional link neural networks and an adaptive PSO–BP learning for CFLNN
  Neural Computing and Applications, 2009
• An analytic algorithm of Lane–Emden type equations arising in astrophysics using modified Homotopy analysis method
  Computer Physics Communications, 2009
• Series approach to the Lane–Emden equation and comparison with the homotopy perturbation method
  Chaos, Solitons & Fractals, 2008
• Permanence of species in nonautonomous discrete Lotka–Volterra competitive system with delays and feedback controls
  Journal of Computational and Applied Mathematics, 2008