Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks.
Jecinta MulongoMarcellin AtemkengTheophilus Ansah-NarhRockefeller RockefellerGabin Maxime NguegnangMarco Andrea GarutiPublished in: Appl. Artif. Intell. (2020)
Keyphrases
- anomaly detection
- power generation
- machine learning
- neural network
- connectionist systems
- network anomaly detection
- pattern recognition
- power system
- intrusion detection
- short term
- unsupervised learning
- network intrusion detection
- power plant
- anomalous behavior
- detecting anomalies
- network traffic
- production cost
- long term
- intrusion detection system
- text classification
- artificial neural networks
- fuzzy logic
- fault diagnosis
- fuzzy systems
- back propagation
- computational intelligence
- genetic algorithm
- model selection
- supervised learning
- stochastic programming
- wind turbine
- feature selection
- detect anomalies
- learning algorithm
- one class support vector machines
- data mining
- self organizing maps
- neural network model
- intelligent systems
- support vector machine
- expert systems