Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks.
Peng LiangHai-Dong YangWen-Si ChenSi-Yuan XiaoZhao-Ze LanPublished in: Int. J. Comput. Integr. Manuf. (2018)
Keyphrases
- anomaly detection
- transfer learning
- electricity consumption
- neural network
- connectionist systems
- learning tasks
- intrusion detection
- electric power
- cross domain
- detecting anomalies
- network traffic
- reinforcement learning
- machine learning
- economic development
- labeled data
- semi supervised learning
- energy consumption
- anomalous behavior
- intrusion detection system
- network intrusion detection
- text categorization
- collaborative filtering
- energy saving
- unsupervised learning
- active learning
- machine learning algorithms
- fuzzy logic
- pattern recognition
- activity recognition
- target domain
- text classification
- semi supervised
- probabilistic model
- transfer knowledge
- genetic algorithm
- one class support vector machines
- unlabeled data
- growth rate
- detect anomalies
- decision trees
- real world