Chuan LI
Chuan LI
Professor, Chongqing Technology and Business University
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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
Gearbox fault identification and classification with convolutional neural networks
ZQ Chen, C Li, RV Sanchez
Shock and Vibration 2015, 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
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
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
A systematic review of deep transfer learning for machinery fault diagnosis
C Li, S Zhang, Y Qin, E Estupinan
Neurocomputing 407, 121-135, 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
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
Li-ion battery fire hazards and safety strategies
L Kong, C Li, J Jiang, MG Pecht
Energies 11 (9), 2191, 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
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
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
A generalized synchrosqueezing transform for enhancing signal time–frequency representation
C Li, M Liang
Signal Processing 92 (9), 2264-2274, 2012
Forecasting the natural gas demand in China using a self-adapting intelligent grey model
B Zeng, C Li
Energy 112, 810-825, 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
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
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
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
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
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
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