Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets.
Maciej WielgoszAndrzej SkoczenMatej MertikPublished in: CoRR (2017)
Keyphrases
- anomaly detection
- recurrent neural networks
- post mortem
- magnetic field
- detect anomalies
- chaotic time series
- echo state networks
- intrusion detection
- feed forward
- neural network
- detecting anomalies
- recurrent networks
- mr images
- intrusion detection system
- network intrusion detection
- anomalous behavior
- network traffic
- detecting anomalous
- artificial neural networks
- coronary artery
- one class support vector machines
- network anomaly detection
- unsupervised learning
- intravascular ultrasound
- phase space
- maximum likelihood
- negative selection algorithm
- active learning