Model order reduction for parameterized electromagnetic problems using matrix decomposition and deep neural networks (Q6137793)

scientific article; zbMATH DE number 7733949

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English	Model order reduction for parameterized electromagnetic problems using matrix decomposition and deep neural networks	scientific article; zbMATH DE number 7733949

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instance of

scholarly article

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title

Model order reduction for parameterized electromagnetic problems using matrix decomposition and deep neural networks (English)

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Journal of Computational and Applied Mathematics

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publication date

4 September 2023

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full work available at URL

https://arxiv.org/abs/2207.07811

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zbMATH Keywords

non-intrusive reduced-order modeling

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parameterized electromagnetic scattering

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proper orthogonal decomposition

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convolutional autoencoder

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cubic spline interpolation

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MaRDI profile type

MaRDI publication profile

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cites work

Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media

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Q4485431

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Introduction to the Finite-Difference Time-Domain (FDTD) Method for Electromagnetics

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Q5756148

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Convergence and stability of a discontinuous Galerkin time-domain method for the 3D heterogeneous Maxwell equations on unstructured meshes

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Model reduction of parametrized systems. Selected contributions based on the presentations at the MoRePaS conference, SISSA, Trieste, Italy, October 13--16, 2015

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Certified Reduced Basis Methods for Parametrized Partial Differential Equations

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Data-driven reduced order modeling for time-dependent problems

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Non-intrusive reduced-order modeling of parameterized electromagnetic scattering problems using cubic spline interpolation

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Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

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Non-intrusive reduced order modelling of the Navier-Stokes equations

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Nonintrusive reduced-order modeling of parametrized time-dependent partial differential equations

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An upwind local radial basis functions-differential quadrature (RBF-DQ) method with proper orthogonal decomposition (POD) approach for solving compressible Euler equation

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A reduced proper orthogonal decomposition (POD) element free Galerkin (POD-EFG) method to simulate two-dimensional solute transport problems and error estimate

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Numerical solution of Helmholtz equation by the modified Hopfield finite difference techniques

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The use of proper orthogonal decomposition (POD) meshless RBF-FD technique to simulate the shallow water equations

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Reduced order modeling of time-dependent incompressible Navier-Stokes equation with variable density based on a local radial basis functions-finite difference (LRBF-FD) technique and the POD/DEIM method

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Non-intrusive reduced order modeling of nonlinear problems using neural networks

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Reduced order modeling for nonlinear structural analysis using Gaussian process regression

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A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

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A parameterized non-intrusive reduced order model and error analysis for general time-dependent nonlinear partial differential equations and its applications

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Simulating backward wave propagation in metamaterial with radial basis functions

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Non intrusive method for parametric model order reduction using a bi-calibrated interpolation on the Grassmann manifold

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Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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DeepXDE: A Deep Learning Library for Solving Differential Equations

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Physics-informed machine learning for reduced-order modeling of nonlinear problems

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Discrete Hessian eigenmaps method for dimensionality reduction

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POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition

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Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

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Non-linear manifold reduced-order models with convolutional autoencoders and reduced over-collocation method

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Finite Element Methods for Maxwell's Equations

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POD-based model order reduction with an adaptive snapshot selection for a discontinuous Galerkin approximation of the time-domain Maxwell's equations

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A comparison of the \(E(3)\) and not-a-knot cubic splines

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Identifiers

arXiv ID

2207.07811

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DOI

10.1016/j.cam.2023.115271

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6137793