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BiBTeX citation export for MOPP21: Research on Resolution of Orbit Based on Clustering Analysis and BP Neural Network in SSRF

@inproceedings{jiang:ibic2021-mopp21,
  author       = {R. Jiang and Y.M. Deng and Y.B. Leng and N. Zhang},
  title        = {{Research on Resolution of Orbit Based on Clustering Analysis and BP Neural Network in SSRF}},
  booktitle    = {Proc. IBIC'21},
  pages        = {88--90},
  eid          = {MOPP21},
  language     = {english},
  keywords     = {SRF, network, experiment, electron, storage-ring},
  venue        = {Pohang, Rep. of Korea},
  series       = {International Beam Instrumentation Conference},
  number       = {10},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {10},
  year         = {2021},
  issn         = {2673-5350},
  isbn         = {978-3-95450-230-1},
  doi          = {10.18429/JACoW-IBIC2021-MOPP21},
  url          = {https://jacow.org/ibic2021/papers/mopp21.pdf},
  note         = {https://doi.org/10.18429/JACoW-IBIC2021-MOPP21},
  abstract     = {{Keeping the beam current’s normal motion is an important mission for Shanghai Synchrotron Radiation Facility (SSRF). So the Orbit (rms)x/y is an main parameter for SSRF’s running. However, the orbital resolution has been constrained by the accuracy of acquired data. To eliminate BPM’s failure causing the inaccurate orbital resolution, the work based on clustering analysis and BP neural network to removed the abnormal BPM and recalculate the resolution of orbit. Data came from the machine research. The analysis results showed that the rms value of orbit is 100.75±6.87 um (x direction) and 14.9±0.6 um (y direction) using all BPM’s data but the recalculate value is 98.03±6 um (x direction) and 2.6±0.4 um (y direction) when eliminate the data of faulty BPM. The analysis result indicated that the method can optimize the resolution of orbit and next work is further to evaluate the orbital resolution with more operation data.}},
}