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ORCIDQi Zhou 0006
Person information
- affiliation: Huazhong University of Science and Technology, School of Mechanical Science and Engineering, Wuhan, China
Other persons with the same name
- Qi Zhou — disambiguation page
- Qi Zhou 0001
![[0000-0002-7759-800X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7759-800X")
— Georgia Institute of Technology, Center for Signal & Image Processing, Atlanta, GA, USA (and 1 more) - Qi Zhou 0002 — Guangdong University of Technology, School of Automation, Guangzhou, China (and 1 more)
- Qi Zhou 0003 — China University of Geosciences, School of Information Engineering, Wuhan
- Qi Zhou 0004 — University of Edinburgh, School of Engineering, UK (and 1 more)
- Qi Zhou 0005 — Southwest Jiaotong University, School of Electrical Engineering, Chengdu, China
- Qi Zhou 0007 — Georgia Institute of Technology, School of Electrical & Computer Engineering, Atlanta, GA, USA
- Qi Zhou 0008 — University of Science and Technology of China, Hefei, China
- Qi Zhou 0009 — University of Calgary, Department of Civil Engineering, AB, Canada (and 1 more)
- Qi Zhou 0010 — Georgia Institute of Technology, Atlanta, GA, USA
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2020 – today
- 2024
[j29]Xufeng Huang, Tingli Xie, Shuyang Luo, Jinhong Wu, Rongmin Luo, Qi Zhou:
Incremental learning with multi-fidelity information fusion for digital twin-driven bearing fault diagnosis. Eng. Appl. Artif. Intell. 133: 108212 (2024)- [j28]Jingchang Li, Jiexiang Hu, Qi Zhou, Yahui Zhang:
Transfer learning-based quality monitoring of laser powder bed fusion across materials. Expert Syst. Appl. 252: 124150 (2024) - [j27]Wang Cai, Leshi Shu, ShaoNing Geng, Qi Zhou, Longchao Cao:
Real-time tracking method for motion spatter in high-power laser welding of stainless steel plate based on a lightweight deep learning model. Expert Syst. Appl. 254: 124386 (2024) - [j26]Xufeng Huang, Tingli Xie, Jinhong Wu, Qi Zhou, Jiexiang Hu:
Deep continuous convolutional networks for fault diagnosis. Knowl. Based Syst. 292: 111623 (2024) - 2023
- [j25]Jinhong Wu, Xingxing Feng, Xuan Cai, Xufeng Huang, Qi Zhou:
A deep learning-based multi-fidelity optimization method for the design of acoustic metasurface. Eng. Comput. 39(5): 3421-3439 (2023) - [j24]Jingchang Li, Qi Zhou, Xufeng Huang, Menglei Li, Longchao Cao:
In situ quality inspection with layer-wise visual images based on deep transfer learning during selective laser melting. J. Intell. Manuf. 34(2): 853-867 (2023) - [j23]Wang Cai, Ping Jiang, Leshi Shu, ShaoNing Geng, Qi Zhou:
Real-time laser keyhole welding penetration state monitoring based on adaptive fusion images using convolutional neural networks. J. Intell. Manuf. 34(3): 1259-1273 (2023) - 2022
- [j22]Lili Zhang, Yuda Wu, Ping Jiang, Seung-Kyum Choi, Qi Zhou:
A multi-fidelity surrogate modeling approach for incorporating multiple non-hierarchical low-fidelity data. Adv. Eng. Informatics 51: 101430 (2022) - [j21]Jiexiang Hu, Yutong Peng, Quan Lin, Huaping Liu, Qi Zhou:
An ensemble weighted average conservative multi-fidelity surrogate modeling method for engineering optimization. Eng. Comput. 38(3): 2221-2244 (2022) - [j20]Jingchang Li, Longchao Cao, Jiexiang Hu, Minhua Sheng, Qi Zhou, Peng Jin:
A prediction approach of SLM based on the ensemble of metamodels considering material efficiency, energy consumption, and tensile strength. J. Intell. Manuf. 33(3): 687-702 (2022) - [j19]Quan Lin, Jiachang Qian, Yuansheng Cheng, Qi Zhou, Jiexiang Hu:
A multi-output multi-fidelity Gaussian process model for non-hierarchical low-fidelity data fusion. Knowl. Based Syst. 254: 109645 (2022) - [j18]Shuyang Luo, Xufeng Huang, Yanzhi Wang, Rongmin Luo, Qi Zhou:
Transfer learning based on improved stacked autoencoder for bearing fault diagnosis. Knowl. Based Syst. 256: 109846 (2022) - 2021
- [j17]Quan Lin, Dawei Hu, Jiexiang Hu, Yuansheng Cheng, Qi Zhou:
A screening-based gradient-enhanced Gaussian process regression model for multi-fidelity data fusion. Adv. Eng. Informatics 50: 101437 (2021) - [j16]Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Leshi Shu:
A parallel constrained lower confidence bounding approach for computationally expensive constrained optimization problems. Appl. Soft Comput. 106: 107276 (2021) - [j15]Quan Lin, Jiexiang Hu, Qi Zhou, Yuansheng Cheng, Zhen Hu, Ivo Couckuyt, Tom Dhaene:
Multi-output Gaussian process prediction for computationally expensive problems with multiple levels of fidelity. Knowl. Based Syst. 227: 107151 (2021) - 2020
- [j14]Xufeng Huang, Qiang Lei, Tingli Xie, Yahui Zhang, Zhen Hu, Qi Zhou:
Deep Transfer Convolutional Neural Network and Extreme Learning Machine for lung nodule diagnosis on CT images. Knowl. Based Syst. 204: 106230 (2020)
2010 – 2019
- 2018
- [j13]Ping Jiang, Yahui Zhang, Qi Zhou, Xinyu Shao, Jiexiang Hu, Leshi Shu:
An adaptive sampling strategy for Kriging metamodel based on Delaunay triangulation and TOPSIS. Appl. Intell. 48(6): 1644-1656 (2018) - [j12]Leshi Shu, Ping Jiang, Qi Zhou, Xinyu Shao, Jiexiang Hu, Xiangzheng Meng:
An on-line variable fidelity metamodel assisted Multi-objective Genetic Algorithm for engineering design optimization. Appl. Soft Comput. 66: 438-448 (2018) - [j11]Tingli Xie, Ping Jiang, Qi Zhou, Leshi Shu, Yahui Zhang, Xiangzheng Meng, Hua Wei:
Advanced Multi-Objective Robust Optimization Under Interval Uncertainty Using Kriging Model and Support Vector Machine. J. Comput. Inf. Sci. Eng. 18(4) (2018) - [j10]Qi Zhou, Longchao Cao, Hui Zhou, Xiang Huang:
Prediction of angular distortion in the fiber laser keyhole welding process based on a variable-fidelity approximation modeling approach. J. Intell. Manuf. 29(3): 719-736 (2018) - [j9]Qi Zhou, Youmin Rong, Xinyu Shao, Ping Jiang, Zhongmei Gao, Longchao Cao:
Optimization of laser brazing onto galvanized steel based on ensemble of metamodels. J. Intell. Manuf. 29(7): 1417-1431 (2018) - [j8]Ping Jiang, Tingli Xie, Qi Zhou, Xinyu Shao, Jiexiang Hu, Longchao Cao:
A space mapping method based on Gaussian process model for variable fidelity metamodeling. Simul. Model. Pract. Theory 81: 64-84 (2018) - 2017
- [j7]Qi Zhou, Ping Jiang, Xinyu Shao, Jiexiang Hu, Longchao Cao, Li Wan:
A variable fidelity information fusion method based on radial basis function. Adv. Eng. Informatics 32: 26-39 (2017) - [j6]Qi Zhou, Yang Yang, Ping Jiang, Xinyu Shao, Longchao Cao, Jiexiang Hu, Zhongmei Gao, Chao-Chao Wang:
A multi-fidelity information fusion metamodeling assisted laser beam welding process parameter optimization approach. Adv. Eng. Softw. 110: 85-97 (2017) - [j5]Qi Zhou, Yan Wang, Ping Jiang, Xinyu Shao, Seung-Kyum Choi, Jiexiang Hu, Longchao Cao, Xiangzheng Meng:
An active learning radial basis function modeling method based on self-organization maps for simulation-based design problems. Knowl. Based Syst. 131: 10-27 (2017) - [j4]Qi Zhou, Yan Wang, Seung-Kyum Choi, Ping Jiang, Xinyu Shao, Jiexiang Hu:
A sequential multi-fidelity metamodeling approach for data regression. Knowl. Based Syst. 134: 199-212 (2017) - 2016
- [j3]Qi Zhou, Xinyu Shao, Ping Jiang, Zhongmei Gao, Chao-Chao Wang, Leshi Shu:
An active learning metamodeling approach by sequentially exploiting difference information from variable-fidelity models. Adv. Eng. Informatics 30(3): 283-297 (2016) - [j2]Ping Jiang, Chao-Chao Wang, Qi Zhou, Xinyu Shao, Leshi Shu, Xiongbin Li:
Optimization of laser welding process parameters of stainless steel 316L using FEM, Kriging and NSGA-II. Adv. Eng. Softw. 99: 147-160 (2016) - [c3]Jiexiang Hu, Qi Zhou, Ping Jiang, Tingli Xie:
An Improved Hierarchical Kriging for Variable-Fidelity Surrogate Modeling. CRC 2016: 86-90 - [c2]Yahui Zhang, Jiexiang Hu, Qi Zhou, Ping Jiang:
A Sequential Sampling Strategy for Multiresponse Radial Basis Function. ISCID (2) 2016: 206-210 - 2015
- [j1]Qi Zhou, Xinyu Shao, Ping Jiang, Hui Zhou, Leshi Shu:
An adaptive global variable fidelity metamodeling strategy using a support vector regression based scaling function. Simul. Model. Pract. Theory 59: 18-35 (2015) - [c1]Qi Zhou, Ping Jiang, Hui Zhou, Leshi Shu:
An active learning variable-fidelity metamodeling approach for engineering design. IEEM 2015: 411-415
Coauthor Index
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last updated on 2024-10-23 20:29 CEST by the dblp team
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