Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale dynamical systems
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Publication:6554903
DOI10.1016/j.physd.2024.134128zbMath1541.65177MaRDI QIDQ6554903
Publication date: 13 June 2024
Published in: Physica D (Search for Journal in Brave)
Lagrangian dynamicsstructure-preserving model reductionoperator inferencedata-driven modelingscientific machine learning
System structure simplification (93B11) Numerical methods for Hamiltonian systems including symplectic integrators (65P10) Discretization methods and integrators (symplectic, variational, geometric, etc.) for dynamical systems (37M15)
Related Items (3)
Gradient preserving operator inference: data-driven reduced-order models for equations with gradient structure ⋮ Operator inference driven data assimilation for high fidelity neutron transport ⋮ Model reduction on manifolds: a differential geometric framework
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