Author: Tomko, M.R.
Paper Title Page
THCPL07 Experience Using NuPIC to Detect Anomalies in Controls Data 1612
  • T. D’Ottavio, P.S. Dyer, J. Piacentino, M.R. Tomko
    BNL, Upton, New York, USA
  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.  
slides icon Slides THCPL07 [11.115 MB]  
DOI • reference for this paper ※  
About • paper received ※ 02 October 2019       paper accepted ※ 09 October 2019       issue date ※ 30 August 2020  
Export • reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)