Forecasting faults of industrial equipment using machine learning classifiers.
Nikolaos KolokasThanasis VafeiadisDimosthenis IoannidisDimitrios TzovarasPublished in: INISTA (2018)
Keyphrases
- machine learning
- machine learning methods
- machine learning algorithms
- machine learning approaches
- decision trees
- supervised classification
- fault detection
- training data
- feature selection
- industrial processes
- training set
- test set
- fault diagnosis
- meta learning
- svm classifier
- short term
- pattern recognition
- multiple classifier systems
- supervised learning
- multiple classifiers
- industrial applications
- learning problems
- inductive learning
- learning tasks
- training samples
- model selection
- knowledge acquisition
- feature set
- information extraction
- support vector machine
- learning classifier systems
- linear classifiers
- ensemble classifier
- fault model
- training examples
- data sets
- semi supervised learning
- text mining
- active learning
- support vector
- computer vision
- learning algorithm
- data mining
- test cases
- classification models
- ensemble learning
- computational intelligence
- natural language processing
- computer science
- induction algorithms
- artificial intelligence