| 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 | 170 | 2019 |
| Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots J Long, J Mou, L Zhang, S Zhang, C Li Journal of manufacturing systems 61, 736-745, 2021 | 127 | 2021 |
| A comparison of dimension reduction techniques for support vector machine modeling of multi-parameter manufacturing quality prediction Y Bai, Z Sun, B Zeng, J Long, L Li, JV de Oliveira, C Li Journal of Intelligent Manufacturing 30, 2245-2256, 2019 | 118 | 2019 |
| Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor D Cabrera, A Guamán, S Zhang, M Cerrada, RV Sánchez, J Cevallos, ... Neurocomputing 380, 51-66, 2020 | 114 | 2020 |
| Deep fuzzy echo state networks for machinery fault diagnosis S Zhang, Z Sun, M Wang, J Long, Y Bai, C Li IEEE Transactions on Fuzzy Systems 28 (7), 1205-1218, 2019 | 98 | 2019 |
| A hybrid multi-objective genetic local search algorithm for the prize-collecting vehicle routing problem J Long, Z Sun, PM Pardalos, Y Hong, S Zhang, C Li Information Sciences 478, 40-61, 2019 | 94 | 2019 |
| A novel sparse echo autoencoder network for data-driven fault diagnosis of delta 3-D printers J Long, Z Sun, C Li, Y Hong, Y Bai, S Zhang IEEE Transactions on Instrumentation and Measurement 69 (3), 683-692, 2019 | 79 | 2019 |
| Manufacturing quality prediction using intelligent learning approaches: A comparative study Y Bai, Z Sun, J Deng, L Li, J Long, C Li Sustainability 10 (1), 85, 2017 | 74 | 2017 |
| Scheduling a realistic hybrid flow shop with stage skipping and adjustable processing time in steel plants J Long, Z Zheng, X Gao, PM Pardalos Applied Soft Computing 64, 536-549, 2018 | 73 | 2018 |
| Generative adversarial networks selection approach for extremely imbalanced fault diagnosis of reciprocating machinery D Cabrera, F Sancho, J Long, RV Sánchez, S Zhang, M Cerrada, C Li IEEE Access 7, 70643-70653, 2019 | 71 | 2019 |
| Intelligent fault diagnosis of delta 3D printers using attitude sensors based on support vector machines K He, Z Yang, Y Bai, J Long, C Li Sensors 18 (4), 1298, 2018 | 70 | 2018 |
| Superplastic deformation behavior of Mg alloys: A-review F Nazeer, J Long, Z Yang, C Li Journal of Magnesium and Alloys 10 (1), 97-109, 2022 | 68 | 2022 |
| A novel self-training semi-supervised deep learning approach for machinery fault diagnosis J Long, Y Chen, Z Yang, Y Huang, C Li International Journal of Production Research 61 (23), 8238-8251, 2023 | 65 | 2023 |
| Dynamic condition monitoring for 3D printers by using error fusion of multiple sparse auto-encoders S Zhang, Z Sun, J Long, C Li, Y Bai Computers in Industry 105, 164-176, 2019 | 60 | 2019 |
| Dynamic scheduling in steelmaking-continuous casting production for continuous caster breakdown J Long, Z Zheng, X Gao International Journal of Production Research 55 (11), 3197-3216, 2017 | 56 | 2017 |
| Discriminative feature learning using a multiscale convolutional capsule network from attitude data for fault diagnosis of industrial robots J Long, Y Qin, Z Yang, Y Huang, C Li Mechanical Systems and Signal Processing 182, 109569, 2023 | 54 | 2023 |
| Deep hybrid state network with feature reinforcement for intelligent fault diagnosis of delta 3-D printers S Zhang, Z Sun, C Li, D Cabrera, J Long, Y Bai IEEE Transactions on Industrial Informatics 16 (2), 779-789, 2019 | 50 | 2019 |
| Fusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals C Li, D Cabrera, F Sancho, RV Sánchez, M Cerrada, J Long, ... Mechanical Systems and Signal Processing 147, 107108, 2021 | 48 | 2021 |
| Fault diagnosis of delta 3D printers using transfer support vector machine with attitude signals J Guo, J Wu, Z Sun, J Long, S Zhang IEEE Access 7, 40359-40368, 2019 | 46 | 2019 |
| Towards a thermodynamically favorable dew point evaporative cooler via optimization J Lin, R Wang, C Li, S Wang, J Long, KJ Chua Energy Conversion and Management 203, 112224, 2020 | 39 | 2020 |
