NUCLEAR TECHNIQUES, Volume. 48, Issue 5, 050002(2025)

A prototype system for intelligent accelerator operation monitoring at CSNS based on machine learning

Na PENG1,3, Yuliang ZHANG1,2,3、*, Sinong CHENG1,3, Yongcheng HE1,2,3, Hao MEI1,3, Lin WANG1,2,3, Kangjia XUE1,3, Mingtao LI1,2,3, Xuan WU1,2,3, Peng ZHU1,2,3, and Weiling HUANG1,2,3
Author Affiliations
  • 1Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Spallation Neutron Source Science Center, Dongguan 523803, China
  • show less
    References(16)

    [8] Aurelio G C, François L, Michael G[M]. Hands-on machine learning with Scikit-Learn & TensorFlow, 8-14(2017).

    [11] Fol E, Carlier F, de Portugal J M C et al. Machine learning methods for optics measurements and corrections at LHC[C], 1967-1970(2018).

    Tools

    Get Citation

    Copy Citation Text

    Na PENG, Yuliang ZHANG, Sinong CHENG, Yongcheng HE, Hao MEI, Lin WANG, Kangjia XUE, Mingtao LI, Xuan WU, Peng ZHU, Weiling HUANG. A prototype system for intelligent accelerator operation monitoring at CSNS based on machine learning[J]. NUCLEAR TECHNIQUES, 2025, 48(5): 050002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Special Topics on Applications of Machine Learning in Nuclear Physics and Nuclear Data

    Received: Dec. 19, 2024

    Accepted: --

    Published Online: Jun. 26, 2025

    The Author Email: Yuliang ZHANG (张玉亮)

    DOI:10.11889/j.0253-3219.2025.hjs.48.240522

    Topics