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TY - CONF AU - Gao, B. AU - Chen, J. AU - Leng, Y.B. AU - Zhou, Y.M. ED - Schaa, Volker RW TI - Machine Learning Applied to Predict Transverse Oscillation at SSRF J2 - Proc. of IBIC2018, Shanghai, China, 09-13 September 2018 CY - Shanghai, China T2 - International Beam Instrumentation Conference T3 - 7 LA - english AB - A fast beam size diagnostic system has been developed at SSRF (Shanghai Synchrotron Radiation Facility) storage ring for turn-by-turn and bunch-by-bunch beam transverse oscillation study. This system is based on visible synchrotron radiation direct imaging system. Currently, this system already has good experimental results. However, this system still has some limitations, the resolution is subject to the point spread function and the speed of online data processing is limited by the complex algorithm. We present a technique that applied machine learning tools to predict transverse oscillation. PB - JACoW Publishing CP - Geneva, Switzerland SP - 512 EP - 515 KW - diagnostics KW - SRF KW - injection KW - storage-ring KW - network DA - 2019/01 PY - 2019 SN - 978-3-95450-201-1 DO - DOI: 10.18429/JACoW-IBIC2018-WEPC15 UR - http://jacow.org/ibic2018/papers/wepc15.pdf ER -