Active Broad-Transfer Learning Algorithm for Class-Imbalanced Fault Diagnosis

Knowledge transfer with class-imbalanced data is a challenge in predictive maintenance and fault diagnosis. Deep learning algorithms have provided promising results in fault diagnosis. However, their prediction performance is affected by class-imbalanced data in cross-domain tasks. Broad learning algorithms present promising performance in handling class-imbalanced domain-adaptation (CIDA) problems. In the presence of a domain shift, active …