A Radial Basis Neural Network Approximation with Extended Precision for Solving Partial Differential Equations
DOI10.1007/978-3-030-76620-7_17OpenAlexW3170929185MaRDI QIDQ5014572
Thi Thuy van le, K. Le-Cao, Hieu Duc-Tran
Publication date: 8 December 2021
Published in: Soft Computing: Biomedical and Related Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-76620-7_17
Artificial neural networks and deep learning (68T07) Spectral, collocation and related methods for boundary value problems involving PDEs (65N35) Numerical computation of matrix norms, conditioning, scaling (65F35) Interpolation in approximation theory (41A05) Rate of convergence, degree of approximation (41A25) Approximation by other special function classes (41A30) Numerical radial basis function approximation (65D12)
Cites Work
- Unnamed Item
- Numerical study of stream-function formulation governing flows in multiply-connected domains by integrated RBFs and Cartesian grids
- Stable computation of multiquadric interpolants for all values of the shape parameter
- Numerical solution of Navier-Stokes equations using multiquadric radial basis function networks
- A higher order compact finite difference algorithm for solving the incompressible Navier-Stokes equations
- A Cartesian grid technique based on one-dimensional integrated radial basis function networks for natural convection in concentric annuli
- A Stable Algorithm for Flat Radial Basis Functions on a Sphere
This page was built for publication: A Radial Basis Neural Network Approximation with Extended Precision for Solving Partial Differential Equations
