Anomaly detection and diagnosis for wind turbines using long short-term memory-based stacked denoising autoencoders and XGBoost.
Chen ZhangDi HuTao YangPublished in: Reliab. Eng. Syst. Saf. (2022)
Keyphrases
- denoising
- anomaly detection
- short term
- wind speed
- wind turbine
- wind power
- long term
- intrusion detection
- anomalous behavior
- wind farm
- image processing
- fault diagnosis
- network intrusion detection
- power generation
- network traffic
- detecting anomalies
- forecasting model
- long term memory
- load forecasting
- intrusion detection system
- one class support vector machines
- short term and long term
- negative selection algorithm
- unsupervised learning
- detect anomalies
- probabilistic model
- network anomaly detection
- neural network
- computational intelligence
- control system
- active learning
- expert systems
- artificial intelligence
- data mining