The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
@unpublished{edelen:napac2019-thxba1,
author = {A.L. Edelen},
title = {{Machine Learning Demonstrations on Accelerators}},
booktitle = {Proc. NAPAC'19},
language = {english},
intype = {presented at the},
series = {North American Particle Accelerator Conference},
number = {4},
venue = {Lansing, MI, USA},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {oct},
year = {2019},
note = {presented at NAPAC2019 in Lansing, MI, USA, unpublished},
abstract = {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.},
}