A Deep Residual Recurrent Neural Network Model-Augmented Attention With Physical Characteristics: Application to Turntable Servo System. - Cheng Xie 003; Songlin Chen; Fengyu Guo; Xiaokun Liu (IEEE Trans. Ind. Electron., 2022)

A Physics-Guided Reversible Residual Neural Network Model: Applied to Build Forward and Inverse Models for Turntable Servo System. - Cheng Xie 003; Songlin Chen (IEEE Trans. Ind. Informatics, 2023)

A novel dynamic parameter identification method for the multi-degrees-of-freedom series direct drive manipulator. - Yang Liu 377; Songlin Chen; Cheng Xie 003 (Trans. Inst. Meas. Control, 2024)

Evolving temporal convolutional neural networks for modeling turntable servo systems. - Cheng Xie 003; Bing Xue 001; Mengjie Zhang 001; Songlin Chen; Yang Liu 377 (Appl. Soft Comput., 2025)

Evolutionary neural architecture search for automatically designing CNN-GRU-Attention neural networks for turntable servo systems. - Cheng Xie 003; Bing Xue 001; Mingyi Yang; Mengjie Zhang 001; Zhigang Xu; Junyi Wang; Songlin Chen; Yang Liu 377 (Expert Syst. Appl., 2025)