Author

Yujun Shi

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Open access Aug 2026

A CNN Feature Extraction and BKA-Optimized LSSVM Classification Method for Small-Sample Rolling Bearing Fault Diagnosis

Experiments indicate that the proposed fault diagnosis approach that combines Continuous Wavelet Transform, Convolutional Neural Network, CNN, Black-winged Kite Algorithm, and Least Squares Support Vector Machine outperforms CNN, CNN-SVM, and CNN-BiGRU under small-sample conditions.

Shi-Yan Sun, Yujun Shi, Quan Li et al. · Italian National Conference... · 0 citations