| A review on data-driven fault severity assessment in rolling bearings M Cerrada, RV Sánchez, C Li, F Pacheco, D Cabrera, JV De Oliveira, ... Mechanical Systems and Signal Processing 99, 169-196, 2018 | 615 | 2018 |
| Gearbox fault identification and classification with convolutional neural networks ZQ Chen, C Li, RV Sanchez Shock and Vibration 2015, 2015 | 463 | 2015 |
| Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals C Li, RV Sanchez, G Zurita, M Cerrada, D Cabrera, RE Vásquez Mechanical Systems and Signal Processing 76, 283-293, 2016 | 440 | 2016 |
| State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network F Yang, W Li, C Li, Q Miao Energy 175, 66-75, 2019 | 372 | 2019 |
| Fault diagnosis in spur gears based on genetic algorithm and random forest M Cerrada, G Zurita, D Cabrera, RV Sánchez, M Artés, C Li Mechanical Systems and Signal Processing 70, 87-103, 2016 | 335 | 2016 |
| A systematic review of deep transfer learning for machinery fault diagnosis C Li, S Zhang, Y Qin, E Estupinan Neurocomputing 407, 121-135, 2020 | 318 | 2020 |
| Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions Y Bai, Y Li, X Wang, J Xie, C Li Atmospheric pollution research 7 (3), 557-566, 2016 | 314 | 2016 |
| Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis C Li, RV Sanchez, G Zurita, M Cerrada, D Cabrera, RE Vásquez Neurocomputing 168, 119-127, 2015 | 295 | 2015 |
| Li-ion battery fire hazards and safety strategies L Kong, C Li, J Jiang, MG Pecht Energies 11 (9), 2191, 2018 | 293 | 2018 |
| Time–frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform C Li, M Liang Mechanical Systems and Signal Processing 26, 205-217, 2012 | 290 | 2012 |
| Deep neural networks-based rolling bearing fault diagnosis Z Chen, S Deng, X Chen, C Li, RV Sanchez, H Qin Microelectronics Reliability 75, 327-333, 2017 | 252 | 2017 |
| Fault diagnosis for rotating machinery using vibration measurement deep statistical feature learning C Li, RV Sánchez, G Zurita, M Cerrada, D Cabrera Sensors 16 (6), 895, 2016 | 246 | 2016 |
| A generalized synchrosqueezing transform for enhancing signal time–frequency representation C Li, M Liang Signal Processing 92 (9), 2264-2274, 2012 | 225 | 2012 |
| Forecasting the natural gas demand in China using a self-adapting intelligent grey model B Zeng, C Li Energy 112, 810-825, 2016 | 214 | 2016 |
| Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models Y Bai, Z Chen, J Xie, C Li Journal of hydrology 532, 193-206, 2016 | 205 | 2016 |
| An ensemble long short-term memory neural network for hourly PM2. 5 concentration forecasting Y Bai, B Zeng, C Li, J Zhang Chemosphere 222, 286-294, 2019 | 165 | 2019 |
| Improved multi-variable grey forecasting model with a dynamic background-value coefficient and its application B Zeng, C Li Computers & Industrial Engineering 118, 278-290, 2018 | 160 | 2018 |
| Evolving deep echo state networks for intelligent fault diagnosis J Long, S Zhang, C Li IEEE Transactions on Industrial Informatics 16 (7), 4928-4937, 2019 | 152 | 2019 |
| Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time–frequency ridge enhancement C Li, V Sanchez, G Zurita, MC Lozada, D Cabrera ISA transactions 60, 274-284, 2016 | 145 | 2016 |
| Improving forecasting accuracy of daily enterprise electricity consumption using a random forest based on ensemble empirical mode decomposition C Li, Y Tao, W Ao, S Yang, Y Bai Energy 165, 1220-1227, 2018 | 141 | 2018 |
