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Gao, Han / Zhong, Botao / Ding, Lieyun (2024): A blockchain-based engineering design review service trading scheme for digital building permits. Dans: Automation in Construction, v. 165 (septembre 2024).
https://doi.org/10.1016/j.autcon.2024.105496
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Zhou, Ying / Wang, Yu / Li, Chenshuang / Ding, Lieyun / Yang, Zhigang (2024): Health and comfort oriented automatic generative design and optimization of residence space layout: An integrated data-driven and knowledge-based approach. Dans: Developments in the Built Environment, v. 17 (mars 2024).
https://doi.org/10.1016/j.dibe.2023.100318
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Zhou, Cheng / Gao, Yuyue / Chen, Elton J. / Ding, Lieyun / Qin, Wenbo (2023): Deep learning technologies for shield tunneling: Challenges and opportunities. Dans: Automation in Construction, v. 154 (octobre 2023).
https://doi.org/10.1016/j.autcon.2023.104982
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You, Ke / Zhou, Cheng / Ding, Lieyun (2023): Deep learning technology for construction machinery and robotics. Dans: Automation in Construction, v. 150 (juin 2023).
https://doi.org/10.1016/j.autcon.2023.104852
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Zhong, Botao / Pan, Xing / Ding, Lieyun / Chen, Qiang / Hu, Xiaowei (2023): Blockchain-driven integration technology for the AEC industry. Dans: Automation in Construction, v. 150 (juin 2023).
https://doi.org/10.1016/j.autcon.2023.104791
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Zhou, Ying / Wang, Yu / Li, Chenshuang / Ding, Lieyun / Wang, Cong (2022): Automatic generative design and optimization of hospital building layouts in consideration of public health emergency. Dans: Engineering, Construction and Architectural Management, v. 31, n. 4 (décembre 2022).
https://doi.org/10.1108/ecam-08-2022-0757
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Wei, Wei / Ding, Lieyun / Luo, Hanbin / Li, Chen / Li, Guowei (2021): Automated bughole detection and quality performance assessment of concrete using image processing and deep convolutional neural networks. Dans: Construction and Building Materials, v. 281 (avril 2021).
https://doi.org/10.1016/j.conbuildmat.2021.122576
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Jiang, Weiguang / Ding, Lieyun / Zhou, Cheng (2022): Digital twin: Stability analysis for tower crane hoisting safety with a scale model. Dans: Automation in Construction, v. 138 (juin 2022).
https://doi.org/10.1016/j.autcon.2022.104257
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You, Ke / Ding, Lieyun / Zhou, Cheng / Dou, Quanli / Wang, Xuepeng / Hu, Bin (2021): 5G-based earthwork monitoring system for an unmanned bulldozer. Dans: Automation in Construction, v. 131 (novembre 2021).
https://doi.org/10.1016/j.autcon.2021.103891
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Jiang, Weiguang / Ding, Lieyun / Zhou, Cheng (2021): Cyber physical system for safety management in smart construction site. Dans: Engineering, Construction and Architectural Management, v. 28, n. 3 ( 2021).
https://doi.org/10.1108/ecam-10-2019-0578
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Sheng, Da / Ding, Lieyun / Zhong, Botao / Love, Peter E. D. / Luo, Hanbin / Chen, Jiageng (2020): Construction quality information management with blockchains. Dans: Automation in Construction, v. 120 (décembre 2020).
https://doi.org/10.1016/j.autcon.2020.103373
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Zhou, Cheng / Tang, Bin / Ding, Lieyun / Sekula, Przemyslaw / Zhou, Ying / Zhang, Zekun (2020): Design and automated assembly of Planetary LEGO Brick for lunar in-situ construction. Dans: Automation in Construction, v. 118 (octobre 2020).
https://doi.org/10.1016/j.autcon.2020.103282
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Zhong, Botao / Pan, Xing / Love, Peter E. D. / Ding, Lieyun / Fang, Weili (2020): Deep learning and network analysis: Classifying and visualizing accident narratives in construction. Dans: Automation in Construction, v. 113 (mai 2020).
https://doi.org/10.1016/j.autcon.2020.103089
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Liu, Wenli / Ding, Lieyun (2020): Global sensitivity analysis of influential parameters for excavation stability of metro tunnel. Dans: Automation in Construction, v. 113 (mai 2020).
https://doi.org/10.1016/j.autcon.2020.103080
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Fang, Weili / Ding, Lieyun / Love, Peter E. D. / Luo, Hanbin / Li, Heng / Peña-Mora, Feniosky / Zhong, Botao / Zhou, Cheng (2020): Computer vision applications in construction safety assurance. Dans: Automation in Construction, v. 110 (février 2020).
https://doi.org/10.1016/j.autcon.2019.103013
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Zhang, Limao / Wu, Xianguo / Ding, Lieyun / Skibniewski, Miroslaw J. / Lu, Yujie (2016): BIM-based Risk Identification System in Tunnel Construction. Dans: Journal of Civil Engineering and Management, v. 22, n. 4 (août 2016).
https://doi.org/10.3846/13923730.2015.1023348
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Zhou, Cheng / Xu, Hengcheng / Ding, Lieyun / Wei, Linchun / Zhou, Ying (2019): Dynamic prediction for attitude and position in shield tunneling: A deep learning method. Dans: Automation in Construction, v. 105 (septembre 2019).
https://doi.org/10.1016/j.autcon.2019.102840
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Guo, Shengyu / Ding, Lieyun / Zhang, Yongcheng / Skibniewski, Miroslaw J. / Liang, Kongzheng (2019): Hybrid Recommendation Approach for Behavior Modification in the Chinese Construction Industry. Dans: Journal of Construction Engineering and Management, v. 145, n. 6 (juin 2019).
https://doi.org/10.1061/(asce)co.1943-7862.0001665
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Zhou, Cheng / Ding, Lieyun / Zhou, Ying / Zhang, Hantao / Skibniewski, Miroslaw J. (2019): Hybrid Support Vector Machine Optimization Model for Prediction of Energy Consumption of Cutter Head Drives in Shield Tunneling. Dans: Journal of Computing in Civil Engineering, v. 33, n. 3 (mai 2019).
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Ding, Lieyun / Wang, Fan / Luo, Hanbin / Yu, Minghui / Wu, Xianguo (2013): Feedforward Analysis for Shield-Ground System. Dans: Journal of Computing in Civil Engineering, v. 27, n. 3 (mai 2013).
https://doi.org/10.1061/(asce)cp.1943-5487.0000219
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Ding, Lieyun / Fang, Weili / Luo, Hanbin / Love, Peter E. D. / Zhong, Botao / Ouyang, Xi (2018): A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory. Dans: Automation in Construction, v. 86 (février 2018).
https://doi.org/10.1016/j.autcon.2017.11.002
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Fang, Weili / Ding, Lieyun / Luo, Hanbin / Love, Peter E. D. (2018): Falls from heights: A computer vision-based approach for safety harness detection. Dans: Automation in Construction, v. 91 (juillet 2018).
https://doi.org/10.1016/j.autcon.2018.02.018
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Ding, Lieyun / Zhou, Ying / Akinci, Burcu (2014): Building Information Modeling (BIM) application framework: The process of expanding from 3D to computable nD. Dans: Automation in Construction, v. 46 (octobre 2014).
https://doi.org/10.1016/j.autcon.2014.04.009
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Ding, Lieyun / Li, Kaiman / Zhou, Ying / Love, Peter E. D. (2017): An IFC-inspection process model for infrastructure projects: Enabling real-time quality monitoring and control. Dans: Automation in Construction, v. 84 (décembre 2017).
https://doi.org/10.1016/j.autcon.2017.08.029
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Zhou, Ying / Ding, Lieyun / Wang, Xiangyu / Truijens, Martijn / Luo, Hanbin (2015): Applicability of 4D modeling for resource allocation in mega liquefied natural gas plant construction. Dans: Automation in Construction, v. 50 (février 2015).
https://doi.org/10.1016/j.autcon.2014.10.016
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Xu, Jie / Ding, Lieyun / Love, Peter E. D. (2017): Digital reproduction of historical building ornamental components: From 3D scanning to 3D printing. Dans: Automation in Construction, v. 76 (avril 2017).
https://doi.org/10.1016/j.autcon.2017.01.010
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Zhou, Ying / Ding, Lieyun / Rao, Yang / Luo, Hanbin / Medjdoub, Benachir / Zhong, Hua (2017): Formulating project-level building information modeling evaluation framework from the perspectives of organizations: A review. Dans: Automation in Construction, v. 81 (septembre 2017).
https://doi.org/10.1016/j.autcon.2017.05.004
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Fang, Qi / Li, Heng / Luo, Xiaochun / Ding, Lieyun / Luo, Hanbin / Li, Chengqian (2018): Computer vision aided inspection on falling prevention measures for steeplejacks in an aerial environment. Dans: Automation in Construction, v. 93 (septembre 2018).
https://doi.org/10.1016/j.autcon.2018.05.022
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Fang, Qi / Li, Heng / Luo, Xiaochun / Ding, Lieyun / Luo, Hanbin / Rose, Timothy M. / An, Wangpeng (2018): Detecting non-hardhat-use by a deep learning method from far-field surveillance videos. Dans: Automation in Construction, v. 85 (janvier 2018).
https://doi.org/10.1016/j.autcon.2017.09.018
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Zhou, Cheng / Luo, Hanbin / Fang, Weili / Wei, Ran / Ding, Lieyun (2019): Cyber-physical-system-based safety monitoring for blind hoisting with the internet of things: A case study. Dans: Automation in Construction, v. 97 (janvier 2019).
https://doi.org/10.1016/j.autcon.2018.10.017