Online anomaly detection for drinking water quality using a multi-objective machine learning approach.
Victor Henrique Alves RibeiroGilberto Reynoso-MezaPublished in: GECCO (Companion) (2018)
Keyphrases
- anomaly detection
- water quality
- multi objective
- machine learning
- network anomaly detection
- intrusion detection
- anomalous behavior
- detecting anomalies
- evolutionary algorithm
- network intrusion detection
- unsupervised learning
- network traffic
- multi objective optimization
- detecting anomalous
- water treatment
- objective function
- one class support vector machines
- negative selection algorithm
- measured data
- behavior analysis
- particle swarm optimization
- grey relational analysis
- unsupervised anomaly detection
- intrusion detection system
- decision trees
- detect anomalies
- learning algorithm
- water resources
- information extraction
- genetic algorithm
- feature selection
- pattern recognition
- support vector machine
- data mining
- nsga ii
- network security
- text classification
- maximum likelihood
- computer vision
- neural network
- network intrusion
- active learning
- knowledge discovery
- text mining
- computational intelligence