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RIS citation export for THCPL07: Experience Using NuPIC to Detect Anomalies in Controls Data

TY  - CONF
AU  - D’, Ottavio
AU  - D'Ottavio, T.
AU  - Dyer, P.S.
AU  - Piacentino, J.
AU  - Tomko, M.R.
ED  - White, Karen S.
ED  - Brown, Kevin A.
ED  - Dyer, Philip S.
ED  - Schaa, Volker RW
TI  - Experience Using NuPIC to Detect Anomalies in Controls Data
J2  - Proc. of ICALEPCS2019, New York, NY, USA, 05-11 October 2019
CY  - New York, NY, USA
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 17
LA  - english
AB  - NuPIC (Numenta Platform for Intelligent Computing) is an open-source computing platform that attempts to mimic neurological pathways in the human brain. We have used the Python implementation to explore the utility of using this system to detect anomalies in both stored and real-time data coming from the controls system for the RHIC Collider at Brookhaven National Laboratory. This paper explores various aspects of that work including the types of data most suited to anomaly detection, the likelihood of developing false positive and negative anomaly results, and experiences with training the system. We also report on the use of this software for monitoring various parts of the controls system in real-time.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 1612
EP  - 1616
KW  - software
KW  - real-time
KW  - controls
KW  - GUI
KW  - framework
DA  - 2020/08
PY  - 2020
SN  - 2226-0358
SN  - 978-3-95450-209-7
DO  - doi:10.18429/JACoW-ICALEPCS2019-THCPL07
UR  - https://jacow.org/icalepcs2019/papers/thcpl07.pdf
ER  -