论文标题
非线性动力学系统中的机器学习
Machine Learning in Nonlinear Dynamical Systems
论文作者
论文摘要
在本文中，我们讨论了将机器学习（ML）技术应用于非线性动力学系统的一些最新发展。特别是，我们演示了如何构建合适的ML框架来解决两个相关性的两个特定目标：预测系统的未来演变以及从给定的时间序列数据揭示基础动力学的分析形式。本文以适合非线性动力学或机器学习课程的教学方式编写。
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.
