An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection.
Liangwei ZhangJing LinRamin KarimPublished in: Reliab. Eng. Syst. Saf. (2015)
Keyphrases
- anomaly detection
- high dimensional data
- fault detection
- industrial processes
- subspace clustering
- low dimensional
- high dimensional
- fault diagnosis
- dimensionality reduction
- nearest neighbor
- intrusion detection
- detecting anomalies
- clustering high dimensional data
- network intrusion detection
- dimension reduction
- data points
- data analysis
- lower dimensional
- data sets
- anomalous behavior
- unsupervised learning
- network traffic
- high dimensional spaces
- subspace learning
- detect anomalies
- one class support vector machines
- negative selection algorithm
- manifold learning
- low rank
- subspace clusters
- power plant
- quality improvement
- principal component analysis
- feature space
- artificial intelligence
- genetic algorithm