Machine Learning in Nonlinear Dynamical Systems

In this article, we discuss some of the recent developments in applying machine learning (ML) techniques to nonlinear dynamical systems. In particular, we demonstrate how to build a suitable ML framework for addressing two specific objectives of relevance: prediction of future evolution of a system...

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Bibliographic Details
Published in:arXiv.org 2020-11
Main Authors: Roy, Sayan, Rana, Debanjan
Format: Article
Language:English
Subjects:
Dynamical systems
Machine learning
Nonlinear dynamics
Nonlinear systems
Online Access:Get full text
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Summary:In this article, we discuss some of the recent developments in applying machine learning (ML) techniques to nonlinear dynamical systems. In particular, we demonstrate how to build a suitable ML framework for addressing two specific objectives of relevance: prediction of future evolution of a system and unveiling from given time-series data the analytical form of the underlying dynamics. This article is written in a pedagogical style appropriate for a course in nonlinear dynamics or machine learning.
ISSN:2331-8422