大学物理 ›› 2026, Vol. 45 ›› Issue (2): 1-.doi: 10.16854/j.cnki.1000-0712. 250211

• 教学研究 •    下一篇

计算物理课程引入机器学习的有效路径研究——以SINDy-PI算法在双摆与罗斯勒系统中的应用为例

王晓云,李文渊,刘翔   

  1. 1.兰州理工大学 理学院,甘肃 兰州730050;2.兰州理论物理中心,甘肃 兰州730000; 3.兰州大学 物理科学与技术学院, 甘肃 兰州730000
  • 收稿日期:2025-04-17 修回日期:2025-06-27 出版日期:2026-05-15 发布日期:2026-05-21
  • 作者简介:王晓云(1984—),男,甘肃武威人,兰州理工大学理学院教授,博士,从事理论物理研究工作. E-mail:xywang@lut.edu.cn
  • 基金资助:
    国家自然科学基金项目(12247101);兰州理工大学高教研究项目(GJ2023B-45)

Study on effective approaches to incorporating machine  learning into computational physics course——taking the application of SINDyPI algorithm in double  pendulum and Rssler systems as an example

WANG Xiaoyun1,2, LI Wenyuan1, LIU Xiang2,3   

  1. 1.School of Science,Lanzhou University of Technology ,Lanzhou, Gansu 730050, China;
    2.Lanzhou Center for Theoretical Physics,Lanzhou, Gansu 730000, China;
    3.School of Physical Science and Technology, Lanzhou University,Lanzhou, Gansu 730000, China
  • Received:2025-04-17 Revised:2025-06-27 Online:2026-05-15 Published:2026-05-21

摘要: 本文从两个简单的经典非线性系统——双摆系统和罗斯勒系统入手,通过使用SINDy-PI算法对它们动力学方程的识别,展现了机器学习方法在处理非线性系统时的高效性与准确性,指出了该算法在数据驱动研究方面的优点. 并以此为契机,对计算物理课程中引入机器学习的有效路径进行了探索和讨论,研究结果可为计算物理课程的教学实践提供有益参考.


关键词: SINDy-PI算法, 双摆系统, 罗斯勒系统, 机器学习

Abstract: This paper begins by examining two simple classical nonlinear systems—the double pendulum system and the Rssler system. Through the use of the SINDyPI algorithm for identifying their dynamical equations, it demonstrates the efficiency and accuracy of machine learning methods in handling nonlinear systems and highlights the merits of this algorithm in datadriven approaches. Additionally, taking this as a basis, the study explores and discusses effective approaches to incorporating machine learning into the computational physics course. The findings provide valuable references for the practical implementation of teaching in computational physics.

Key words: SINDyP algorithm, double pendulum system, Rssler system, machine learning