Constructing neural network based models for simulating dynamical systems
Dynamical systems see widespread use in natural sciences like physics, biology, and
chemistry, as well as engineering disciplines such as circuit analysis, computational fluid
dynamics, and control. For simple systems, the differential equations governing the
dynamics can be derived by applying fundamental physical laws. However, for more
complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an
alternative paradigm that seeks to learn an approximation of the dynamics of a system using …
chemistry, as well as engineering disciplines such as circuit analysis, computational fluid
dynamics, and control. For simple systems, the differential equations governing the
dynamics can be derived by applying fundamental physical laws. However, for more
complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an
alternative paradigm that seeks to learn an approximation of the dynamics of a system using …
Constructing Neural Network-Based Models for Simulating Dynamical Systems
C Møldrup Legaard, T Schranz, G Schweiger… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Dynamical systems see widespread use in natural sciences like physics, biology, chemistry,
as well as engineering disciplines such as circuit analysis, computational fluid dynamics,
and control. For simple systems, the differential equations governing the dynamics can be
derived by applying fundamental physical laws. However, for more complex systems, this
approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm
that seeks to learn an approximation of the dynamics of a system using observations of the …
as well as engineering disciplines such as circuit analysis, computational fluid dynamics,
and control. For simple systems, the differential equations governing the dynamics can be
derived by applying fundamental physical laws. However, for more complex systems, this
approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm
that seeks to learn an approximation of the dynamics of a system using observations of the …
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