Qi Zhou
Cited by
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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
Fault diagnosis of rotating machinery based on recurrent neural networks
Y Zhang, T Zhou, X Huang, L Cao, Q Zhou
Measurement 171, 108774, 2021
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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