IMWMOTE: A novel oversampling technique for fault diagnosis in heterogeneous imbalanced data.
Jiaxin WangJianan WeiHaisong HuangLong WenYage YuanHualin ChenRui WuJinxing WuPublished in: Expert Syst. Appl. (2024)
Keyphrases
- fault diagnosis
- imbalanced data
- class imbalance
- minority class
- sampling methods
- neural network
- expert systems
- fault detection
- class distribution
- linear regression
- operating conditions
- bp neural network
- fuzzy logic
- ensemble methods
- feature selection
- monitoring and fault diagnosis
- support vector machine
- chemical process
- multi sensor information fusion
- random forest
- high dimensionality
- decision trees
- artificial intelligence
- ensemble learning
- decision boundary
- supervised learning
- active learning
- training data
- genetic algorithm