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The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.


RIS citation export for THXBA1: Machine Learning Demonstrations on Accelerators

TY  - UNPB
AU  - Edelen, A.L.
ED  - Yamazaki, Yoshishige
ED  - Raubenheimer, Tor
ED  - McCausey, Amy
ED  - Schaa, Volker RW
TI  - Machine Learning Demonstrations on Accelerators
J2  - Proc. of NAPAC2019, Lansing, MI, USA, 01-06 September 2019
CY  - Lansing, MI, USA
T2  - North American Particle Accelerator Conference
T3  - 4
LA  - english
AB  - Machine learning has been used in various ways to improve acclerator operation including the development of surrogate models to improve real-time modeling, advanced optimization of accelerator operating configurations such as quadrupole or undulator strengths, development of virtual diagnostics to ’measure’ accelerator and beam parameters, and prognostics to improve operating time.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
ER  -