Enhancing Bearing Fault Diagnosis Using Transfer Learning and Random Forest Classification: A Comparative Study on Variable Working Conditions.
Durjay SahaMd. Emdadul HoqueMuhammad E. H. ChowdhuryPublished in: IEEE Access (2024)
Keyphrases
- fault diagnosis
- random forest
- transfer learning
- monitoring and fault diagnosis
- decision trees
- feature set
- machine learning
- text classification
- neural network
- operating conditions
- expert systems
- machine learning algorithms
- labeled data
- feature vectors
- fuzzy logic
- text categorization
- supervised learning
- ensemble methods
- reinforcement learning
- active learning
- support vector
- multi label
- class labels
- support vector machine svm
- semi supervised learning
- feature extraction
- image classification
- collaborative filtering
- classification accuracy
- information retrieval
- machine learning methods
- data sets
- genetic algorithm
- artificial intelligence
- prediction accuracy
- naive bayes
- unlabeled data
- support vector machine