Online Interpolation Point Refinement for Reduced-Order Models using a Genetic Algorithm
DOI10.1137/16M1086352zbMath1383.65123arXiv1607.07702OpenAlexW2479330356MaRDI QIDQ4603498
Steven L. Brunton, Syuzanna Sargsyan, J. Nathan Kutz
Publication date: 21 February 2018
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1607.07702
proper orthogonal decompositionGinzburg-Landau equationNavier-Stokes equationgenetic algorithmdimensionality reductionreduced-order modelingdiscrete empirical interpolation methodsparse sampling
Navier-Stokes equations (35Q30) Multigrid methods; domain decomposition for initial value and initial-boundary value problems involving PDEs (65M55) Ginzburg-Landau equations (35Q56)
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Cites Work
- Unnamed Item
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- CUR matrix decompositions for improved data analysis
- Discovering governing equations from data by sparse identification of nonlinear dynamical systems
- The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows
- Fast local reduced basis updates for the efficient reduction of nonlinear systems with hyper-reduction
- A theory of pseudoskeleton approximations
- Real-time solution of linear computational problems using databases of parametric reduced-order models with arbitrary underlying meshes
- Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction
- Dynamic data-driven reduced-order models
- An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
- Gradient-based constrained optimization using a database of linear reduced-order models
- Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition
- A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
- Sparse Sensor Placement Optimization for Classification
- Compressive Sensing and Low-Rank Libraries for Classification of Bifurcation Regimes in Nonlinear Dynamical Systems
- Compressive sensing based machine learning strategy for characterizing the flow around a cylinder with limited pressure measurements
- Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- Mode‐Locked Soliton Lasers
- Cluster-based reduced-order modelling of a mixing layer
- A ‘best points’ interpolation method for efficient approximation of parametrized functions
- Low-dimensional models for complex geometry flows: Application to grooved channels and circular cylinders
- A low-dimensional model for simulating three-dimensional cylinder flow
- Low-order modelling of laminar flow regimes past a confined square cylinder
- Gappy data and reconstruction procedures for flow past a cylinder
- Sparse dynamics for partial differential equations
- Compressed modes for variational problems in mathematics and physics
- An "$hp$" Certified Reduced Basis Method for Parametrized Elliptic Partial Differential Equations
- On the Compressive Spectral Method
- Pattern formation outside of equilibrium
- Turbulence, Coherent Structures, Dynamical Systems and Symmetry
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