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[1] A Novel Transfer Kernel Enabled Kernel Extreme Learning Machine Model for Cross-Domain Condition Monitoring and Fault Diagnosis of Bearings
[2] Early Failure Point Monitoring for Remaining Useful Life Estimation of Bearings Using Covariance Transfer Enabled T2 Control Chart
[3] Enhanced Cross-Domain Projection Based Heterogeneous Domain Adaptation Method for Cross-Domain Fault Diagnosis
[4] Deep Active Transfer Learning for Cross-Domain Fault Diagnosis With Limited Samples
[5] Bearing Compound Fault Diagnosis Based on Double-Domain Reweighted Adaptive Sparse Representation
[6] 基于小波核扩散与双阶段SVM的轴承复合故障分类方法
[7] A New Safe-Level Enabled Borderline-SMOTE for Condition Recognition of Imbalanced Dataset
[8] A Subspace Domain Adaptation Method: SSA-Theoretic Drift Correction for Gear Fault Diagnosis under Varying Working Conditions
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