JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@unpublished{yucesan:napac2022-thxd1,
author = {Y.A. Yucesan},
title = {{Machine Learning for Improved Accelerator Health and Reliability}},
% booktitle = {Proc. NAPAC'22},
booktitle = {Proc. 5th Int. Particle Accel. Conf. (NAPAC'22)},
language = {english},
intype = {presented at the},
series = {International Particle Accelerator Conference},
number = {5},
venue = {Albuquerque, NM, USA},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {10},
year = {2022},
note = {presented at NAPAC'22 in Albuquerque, NM, USA, unpublished},
abstract = {{This talk will summarize the effort by the community in using machine learning for improved accelerator operations. This talk will also discuss efforts to implement a machine learning framework to improve accelerator reliability at the Spallation Neutron Source. It will describe new prognostics algorithms for detecting beam faults, classification of the fault sources, and efforts to integrate the algorithms into operations. it will also describe additional efforts to utilize ML for health and predictive prognostics on critical accelerator hardware and targets.}},
}