| Surrogate-model-based design and optimization P Jiang, Q Zhou, X Shao, P Jiang, Q Zhou, X Shao Surrogate Model-Based Engineering Design and Optimization, 135-236, 2020 | 155 | 2020 |
| Fault diagnosis of rotating machinery based on recurrent neural networks Y Zhang, T Zhou, X Huang, L Cao, Q Zhou Measurement 171, 108774, 2021 | 140 | 2021 |
| Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature W Cai, JZ Wang, P Jiang, LC Cao, GY Mi, Q Zhou Journal of Manufacturing systems 57, 1-18, 2020 | 119 | 2020 |
| A sequential constraints updating approach for Kriging surrogate model-assisted engineering optimization design problem J Qian, J Yi, Y Cheng, J Liu, Q Zhou Engineering with Computers 36, 993-1009, 2020 | 109 | 2020 |
| Optimization of surface roughness and dimensional accuracy in LPBF additive manufacturing L Cao, J Li, J Hu, H Liu, Y Wu, Q Zhou Optics & Laser Technology 142, 107246, 2021 | 108 | 2021 |
| Optimization of laser welding process parameters of stainless steel 316L using FEM, Kriging and NSGA-II P Jiang, C Wang, Q Zhou, X Shao, L Shu, X Li Advances in Engineering Software 99, 147-160, 2016 | 105 | 2016 |
| A sequential multi-fidelity metamodeling approach for data regression Q Zhou, Y Wang, SK Choi, P Jiang, X Shao, J Hu Knowledge-Based Systems 134, 199-212, 2017 | 93 | 2017 |
| An adaptive global variable fidelity metamodeling strategy using a support vector regression based scaling function Q Zhou, X Shao, P Jiang, H Zhou, L Shu Simulation Modelling Practice and Theory 59, 18-35, 2015 | 92 | 2015 |
| Deep transfer convolutional neural network and extreme learning machine for lung nodule diagnosis on CT images X Huang, Q Lei, T Xie, Y Zhang, Z Hu, Q Zhou Knowledge-Based Systems 204, 106230, 2020 | 81 | 2020 |
| Parameters optimization of hybrid fiber laser-arc butt welding on 316L stainless steel using Kriging model and GA Z Gao, X Shao, P Jiang, L Cao, Q Zhou, C Yue, Y Liu, C Wang Optics & Laser Technology 83, 153-162, 2016 | 79 | 2016 |
| A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems Q Zhou, J Wu, T Xue, P Jin Engineering with computers 37, 623-639, 2021 | 77 | 2021 |
| An active learning metamodeling approach by sequentially exploiting difference information from variable-fidelity models Q Zhou, X Shao, P Jiang, Z Gao, C Wang, L Shu Advanced Engineering Informatics 30 (3), 283-297, 2016 | 77 | 2016 |
| A variable fidelity information fusion method based on radial basis function Q Zhou, P Jiang, X Shao, J Hu, L Cao, L Wan Advanced Engineering Informatics 32, 26-39, 2017 | 69 | 2017 |
| A robust optimization approach based on multi-fidelity metamodel Q Zhou, Y Wang, SK Choi, P Jiang, X Shao, J Hu, L Shu Structural and Multidisciplinary Optimization 57, 775-797, 2018 | 68 | 2018 |
| An active learning variable-fidelity metamodelling approach based on ensemble of metamodels and objective-oriented sequential sampling Q Zhou, X Shao, P Jiang, Z Gao, H Zhou, L Shu Journal of Engineering Design 27 (4-6), 205-231, 2016 | 60 | 2016 |
| Optimization of laser brazing onto galvanized steel based on ensemble of metamodels Q Zhou, Y Rong, X Shao, P Jiang, Z Gao, L Cao Journal of Intelligent Manufacturing 29, 1417-1431, 2018 | 57 | 2018 |
| Multi-objective process parameters optimization of hot-wire laser welding using ensemble of metamodels and NSGA-II Y Yang, L Cao, C Wang, Q Zhou, P Jiang Robotics and Computer-Integrated Manufacturing 53, 141-152, 2018 | 55 | 2018 |
| An active-learning method based on multi-fidelity Kriging model for structural reliability analysis J Yi, F Wu, Q Zhou, Y Cheng, H Ling, J Liu Structural and Multidisciplinary Optimization 63, 173-195, 2021 | 53 | 2021 |
| A generalized hierarchical co-Kriging model for multi-fidelity data fusion Q Zhou, Y Wu, Z Guo, J Hu, P Jin Structural and Multidisciplinary Optimization 62, 1885-1904, 2020 | 52 | 2020 |
| Variable-fidelity probability of improvement method for efficient global optimization of expensive black-box problems X Ruan, P Jiang, Q Zhou, J Hu, L Shu Structural and Multidisciplinary Optimization 62, 3021-3052, 2020 | 51 | 2020 |
Ping JiangHuazhong university of science and technologyDirección de correo verificada de hust.edu.cn
