Machine learning in adaptive FETI-DP -- a comparison of smart and random training data

DOI10.1007/978-3-030-56750-7_24OpenAlexW2902851268MaRDI QIDQ2100351

Janine Weber, Axel Klawonn, Martin Lanser, Alexander Heinlein

Publication date: 21 November 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-56750-7_24

zbMATH Keywords

eigenvalue problemdomain decomposition methodsmachine learningadaptive FETI-DP

Mathematics Subject Classification ID

Computational learning theory (68Q32) Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Artificial neural networks and deep learning (68T07) Linear elasticity with initial stresses (74B10) Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Iterative numerical methods for linear systems (65F10) Numerical computation of matrix norms, conditioning, scaling (65F35) Mesh generation, refinement, and adaptive methods for boundary value problems involving PDEs (65N50) Numerical methods for eigenvalue problems for boundary value problems involving PDEs (65N25) Preconditioners for iterative methods (65F08)

Related Items (3)

Learning adaptive coarse basis functions of FETI-DP ⋮ A frugal FETI-DP and BDDC coarse space for heterogeneous problems ⋮ Combining Machine Learning and Adaptive Coarse Spaces---A Hybrid Approach for Robust FETI-DP Methods in Three Dimensions

This page was built for publication: Machine learning in adaptive FETI-DP -- a comparison of smart and random training data