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September 30, 2018 to October 5, 2018
Charles B. Wang Center
US/Eastern timezone

Developing Machine Learning Algorithms for NSLS-II Linac with Operators

Oct 5, 2018, 8:30 AM
Theater (Charles B. Wang Center)


Charles B. Wang Center

Stony Brook University 100 Nicolls Rd, Stony Brook, NY 11794
Oral Impact of New Technology for Control Room Operations New Technology


Raymond Fliller (Brookhaven National Laboratory)


Machine Learning has proven itself as a useful technique in a variety of applications. We have used machine learning techniques to provide an RF feedforward system to the NSLS-II linac to correct for long term drifts in the system. Prior to this, the operator needed to do the correction manually. The operators participated in every aspect of the process from generating the necessary controls, to data collection, and verification. In this paper, we discuss have machine learning was used to correct drifts in the NSLS-II linac and how the operators participated in its development.

Primary author

Raymond Fliller (Brookhaven National Laboratory)


Robert Rainer (Brookhaven National Laboratory) Mr Charles Gardner (Brookhaven National Laboratory) Mr Philip Marino (Brookhaven National Laboratory) Mr Michael Santana (Brookhaven National Laboratory) Mr Gary Weiner (Brookhaven National Laboratory) Mr Edward Zeitler (Brookhaven National Laboratory)

Presentation materials