A reduced order method for nonlinear parameterized partial differential equations using dynamic mode decomposition coupled with \(k\)-nearest-neighbors regression

DOI10.1016/j.jcp.2021.110907OpenAlexW4200558850WikidataQ114163385 ScholiaQ114163385MaRDI QIDQ2133585

Yifan Lin, Zhen Gao, Xiang Sun, Xueying Zeng

Publication date: 4 May 2022

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2021.110907

zbMATH Keywords

dynamic mode decompositionreduced order modelparameterized partial differential equations\(k\)-nearest-neighbors regression

Mathematics Subject Classification ID

Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Approximation methods and numerical treatment of dynamical systems (37Mxx) Numerical problems in dynamical systems (65Pxx)

Related Items (3)

A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation ⋮ Surrogate modeling of time-domain electromagnetic wave propagation via dynamic mode decomposition and radial basis function ⋮ A dynamic mode decomposition based reduced-order model for parameterized time-dependent partial differential equations

Uses Software

• ElemStatLearn
• redbKIT
• PRMLT

Cites Work

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