Abstract The Sparse Identification of Nonlinear Dynamics (SINDy) toolbox can be used to
estimate a nonlinear model of dynamical systems. SINDy is a dictionary method that applies …

Abstract The Sparse Identification of Nonlinear Dynamics (SINDy) toolbox can be used to
estimate a nonlinear model of dynamical systems. SINDy is a dictionary method that applies …

We perform a sparse identification of nonlinear dynamics (SINDy) for low-dimensionalized
complex flow phenomena. We first apply the SINDy with two regression methods, the …

In recent years, the rapid growth of computing technology has enabled identifying
mathematical models for vibration systems using measurement data instead of domain …

Recently, data‐driven modeling approaches are getting increasingly examined regarding
their applicability for nonlinear mechanical or mechatronic systems. With a high data …

Data-driven modeling can help improve understanding of the governing equations for
systems that are challenging to model. In the current work, the Sparse Identification of …

This work develops a general new framework to discover the governing equations
underlying a dynamical system simply from data measurements, leveraging advances in …

The flow-induced vibration of bluff bodies is an important problem of many marine, civil, or
mechanical engineers. In the design phase of such structures, it is vital to obtain good …

This paper focuses on the application of experimental data-based system identification of
unknown systems utilising sparse identification of nonlinear dynamics (SINDy). SINDy is …

Abstract Machine learning methods have revolutionized studies in several areas of
knowledge, helping to understand and extract information from experimental data. Recently …