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BiBTeX citation export for WEPV011: Research on Correction of Beam Beta Function of HLS-II Storage Ring Based on Deep Learning

  author       = {Y.B. Yu and C. Li and W. Li and G. Liu and W. Xu and K. Xuan},
  title        = {{Research on Correction of Beam Beta Function of HLS-II Storage Ring Based on Deep Learning}},
  booktitle    = {Proc. ICALEPCS'21},
  pages        = {645--647},
  eid          = {WEPV011},
  language     = {english},
  keywords     = {network, storage-ring, quadrupole, controls, feedback},
  venue        = {Shanghai, China},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {18},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {03},
  year         = {2022},
  issn         = {2226-0358},
  isbn         = {978-3-95450-221-9},
  doi          = {10.18429/JACoW-ICALEPCS2021-WEPV011},
  url          = {https://jacow.org/icalepcs2021/papers/wepv011.pdf},
  abstract     = {{The beam stability of the storage ring determines the light quality of synchrotron radiation. The beam stability of the storage ring will be affected by many factors ’such as magnetic field error, installation error, foundation vibration, temperature variation, etc., so it is inevitable to correct the beam optical parameters to improve the beam stability. In this paper, the deep learning technology is used to establish the HLS-II storage ring beam stability model, and the beam optical parameters can be corrected based on the model. The simulation results show that this method realizes the simulation correction of the Beta function of the HLS-II storage ring, and the correction accuracy precision meets the design requirements.}},