- Data|driven modeling and complexity reduction for nonlinear ...🔍
- Fast data|driven model reduction for nonlinear dynamical systems🔍
- Development of data|driven modeling method for nonlinear coupling ...🔍
- Data|driven reduced|order modeling for nonlinear aerodynamics ...🔍
- [2309.05386] Data|Driven Model Reduction and Nonlinear ...🔍
- Data|driven reduced|order modeling for nonautonomous dynamical ...🔍
- Data|driven modeling and prediction of non|linearizable dynamics ...🔍
- A data|driven approach to nonlinear model reduction🔍
Data|driven modeling and complexity reduction for nonlinear ...
Data-driven modeling and complexity reduction for nonlinear ...
of data-driven nonlinear modeling and nonlinear complexity reduction tools with stability guarantees forms the scope of this thesis. 1.2 ...
Data-driven modeling and complexity reduction for nonlinear ...
Data-driven modeling and complexity reduction for nonlinear systems with stability guarantees · Autonomous and Complex Systems · Dynamics and ...
Fast data-driven model reduction for nonlinear dynamical systems
Aside from a major reduction in complexity, our new method allows an increase in the training data dimensionality by several orders of magnitude ...
Development of data-driven modeling method for nonlinear coupling ...
integrated Finite Element Method (FEM) and SINDy to construct a Reduced Order Model (ROM) with an encoder neural network. Brunton et al.
Data-driven reduced-order modeling for nonlinear aerodynamics ...
High-dimensional problems often suffer from the curse of dimensionality, which can lead to increased computational complexity and a higher risk ...
[2309.05386] Data-Driven Model Reduction and Nonlinear ... - arXiv
... control (NMPC). Data-driven model reduction offers a way to obtain low-order control models from complex digital twins. In particular, data- ...
Data-driven reduced-order modeling for nonautonomous dynamical ...
... driven methods are dedicated to using data to exploit the model describing complex systems. ... nonlinear nonautonomous dynamical systems by using the ...
Data-driven modeling and prediction of non-linearizable dynamics ...
Low-dimensional reduced models of high-dimensional nonlinear dynamical systems are critically needed in various branches of applied science and ...
... Theory for Partial Differential Equations and Data-Driven Modeling of Spatio-Temporal Systems,” Complexity, Vol. 2018, 2018. [19] Brunton, S. L., Proctor ...
Fast data-driven model reduction for nonlinear dynamical systems
We present a fast method for nonlinear data-driven model reduction of dynamical systems onto their slowest nonresonant spectral submanifolds (SSMs).
Nonlinear model reduction from equations and data - AIP Publishing
References 25–27 pertain to data-driven approaches for reducing the dimensionality of complex systems using spectral submanifolds (SSMs). More ...
Data-driven Nonlinear Model Reduction using Koopman Theory
Request PDF | Data-driven Nonlinear Model Reduction using Koopman Theory: Integrated Control Form and NMPC Case Study | We use Koopman theory for ...
Data-driven model reduction for weakly nonlinear systems: A summary
Model reduction seeks to replace complex dynamical systems with simpler ones, having similar characteristics. One approach is data-driven reduction based on ...
Learning Nonlinear Reduced Models from Data with Operator ...
On filtering in non-intrusive data-driven reduced-order modeling ... Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems ...
Nonlinear Reduced-Order Modeling from Data by Prof. George Haller.
... data-driven reduced-order modeling of nonlinear phenomena. Specifically, spectral submanifolds (SSMs) represent very low-dimensional ...
Data-driven modeling and control of large-scale dynamical systems ...
... complex scenarios, including linear parametric or nonlinear ... Firstly, for data-driven complexity reduction of the underlying model ...
Data Driven Nonlinear Model Reduction and Metric Complexity Measures for Large Scale Systems. This project addresses the challenges of modeling, simulation, ...
Data-Driven Model Reduction of Monotone Systems by Nonlinear ...
Index Terms—Data-driven methods, dc gains, model reduction, monotone systems, nonlinear systems. I. INTRODUCTION. MODEL order reduction of nonlinear dynamical ...
Data-driven Modeling | Mickaël D. Chekroun - ucla.edu
We show how to perform rigorous and data-driven model reduction ... Parameterizations aim to reduce the complexity of high-dimensional dynamical systems.
Nonlinear Model Order Reduction via Dynamic Mode Decomposition
J. N. Kutz, S. L. Brunton, B. W. Brunton, and J. L. Proctor, Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, SIAM, Philadelphia, 2016.