Predicting existing tunnel deformation from adjacent foundation pit construction using hybrid machine learning
To accurately predict the existing tunnel deformation from adjacent foundation pit construction (AFPC), a hybrid prediction framework based on random forest recursive feature elimination and the Bayesian optimization natural gradient boosting algorithm (RF-RFE-BO-NGBoost) is presented in this paper....
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| Published in: | Automation in construction Vol. 165; p. 105516 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.09.2024
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| Subjects: | |
| ISSN: | 0926-5805 |
| Online Access: | Get full text |
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| Abstract | To accurately predict the existing tunnel deformation from adjacent foundation pit construction (AFPC), a hybrid prediction framework based on random forest recursive feature elimination and the Bayesian optimization natural gradient boosting algorithm (RF-RFE-BO-NGBoost) is presented in this paper. The key findings from this study include the following: (1) RF-RFE effectively screens out crucial parameters, with the optimal feature subset postscreening encompassing ten influencing factors. (2) The BO-NGBoost-based prediction model for existing tunnel deformation from AFPC achieves high accuracy, with R2 values ranging from 0.914 to 0.935, RMSE values ranging from 0.104 to 0.364, MAE values ranging from 0.089 to 0.335, and MAPE values ranging from 3.08% to 10.71% (3) SHapley Additive ExPlanations (SHAP) determines the contribution of each parameter, identifying important construction parameters influencing existing tunnel deformation. The hybrid prediction framework proposed herein provides guidance for realizing the excavation safety management of existing tunnels.
•A method for predicting the adjacent existing tunnel deformation caused by foundation pit construction is proposed.•RF-RFE is used to screen out important parameters and BO-NGBoost is used to predict existing tunnel deformation.•The contribution of each parameter to the model output is analyzed using SHAP.•A tunnel construction example in China is taken as an example for verification. |
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| AbstractList | To accurately predict the existing tunnel deformation from adjacent foundation pit construction (AFPC), a hybrid prediction framework based on random forest recursive feature elimination and the Bayesian optimization natural gradient boosting algorithm (RF-RFE-BO-NGBoost) is presented in this paper. The key findings from this study include the following: (1) RF-RFE effectively screens out crucial parameters, with the optimal feature subset postscreening encompassing ten influencing factors. (2) The BO-NGBoost-based prediction model for existing tunnel deformation from AFPC achieves high accuracy, with R2 values ranging from 0.914 to 0.935, RMSE values ranging from 0.104 to 0.364, MAE values ranging from 0.089 to 0.335, and MAPE values ranging from 3.08% to 10.71% (3) SHapley Additive ExPlanations (SHAP) determines the contribution of each parameter, identifying important construction parameters influencing existing tunnel deformation. The hybrid prediction framework proposed herein provides guidance for realizing the excavation safety management of existing tunnels.
•A method for predicting the adjacent existing tunnel deformation caused by foundation pit construction is proposed.•RF-RFE is used to screen out important parameters and BO-NGBoost is used to predict existing tunnel deformation.•The contribution of each parameter to the model output is analyzed using SHAP.•A tunnel construction example in China is taken as an example for verification. |
| ArticleNumber | 105516 |
| Author | Liu, Yang Feng, Zongbao Wu, Xianguo Liu, Jun Chen, Hongyu |
| Author_xml | – sequence: 1 givenname: Xianguo surname: Wu fullname: Wu, Xianguo organization: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China – sequence: 2 givenname: Zongbao surname: Feng fullname: Feng, Zongbao organization: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China – sequence: 3 givenname: Jun surname: Liu fullname: Liu, Jun organization: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China – sequence: 4 givenname: Hongyu surname: Chen fullname: Chen, Hongyu organization: Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, China – sequence: 5 givenname: Yang surname: Liu fullname: Liu, Yang email: dabailiu@whu.edu.cn organization: ZhongNan Hospital of Wuhan University, Wuhan University, Wuhan 430071, China |
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| Cites_doi | 10.1016/j.ymssp.2013.12.013 10.1016/j.ins.2023.03.004 10.1016/j.compgeo.2024.106149 10.1016/j.autcon.2021.103647 10.1016/j.scs.2023.104823 10.1016/j.jclepro.2024.142746 10.1016/j.tust.2023.105236 10.1016/j.aei.2023.102056 10.3846/jcem.2023.19226 10.1016/j.autcon.2021.103779 10.1016/j.asoc.2022.109848 10.1007/s43452-021-00259-7 10.1016/j.tust.2020.103383 10.1016/j.trgeo.2022.100771 10.1016/j.tust.2023.105445 10.1016/j.conbuildmat.2022.129232 10.1016/j.joes.2021.08.007 10.1016/j.trgeo.2022.100791 10.1016/j.autcon.2022.104488 10.1016/j.tust.2022.104879 10.1016/j.autcon.2022.104331 10.1016/j.energy.2023.127227 10.3390/su15129740 10.1016/j.asoc.2023.110206 10.1109/TBME.2007.890733 10.1016/j.tust.2020.103493 10.1016/j.gsf.2020.03.007 10.1007/s11771-021-4737-3 10.1016/j.compgeo.2018.11.001 10.1016/j.aei.2020.101201 10.1016/j.tust.2022.104452 10.1016/j.tust.2022.104846 10.1016/j.tust.2022.104903 10.3846/jcem.2021.14901 10.1016/j.jclepro.2020.122542 10.1016/j.tust.2024.105704 10.1016/j.tust.2022.104908 10.1016/j.autcon.2022.104219 10.1016/j.scitotenv.2020.136511 10.1016/j.engappai.2023.106386 10.1016/j.undsp.2023.09.014 10.1007/s00500-020-05560-w 10.1016/j.asoc.2020.106921 10.1016/j.ress.2023.109126 10.1016/j.autcon.2022.104730 10.1016/j.undsp.2021.12.005 10.1016/j.scs.2023.104796 10.1007/s40534-015-0087-x 10.1016/j.jrmge.2021.06.012 10.1016/j.jclepro.2024.141774 10.3390/app12094752 10.1016/j.engstruct.2023.117307 10.1016/j.conbuildmat.2022.127132 10.1016/j.asoc.2022.109711 10.1016/j.autcon.2021.104109 10.1016/j.gsf.2021.101211 10.1016/j.jrmge.2016.04.001 10.1016/j.eswa.2022.118721 10.1016/j.autcon.2022.104572 10.1016/j.autcon.2022.104672 10.1016/j.eswa.2023.122786 10.1109/TSG.2019.2892595 10.1016/j.engfailanal.2022.106786 10.1016/j.conbuildmat.2023.130644 10.2113/2022/7227330 10.1016/j.tust.2013.07.002 10.1016/j.jocs.2022.101587 10.1016/j.autcon.2024.105421 10.1016/j.enbuild.2023.113665 10.3390/e23010018 10.1016/j.autcon.2023.104805 10.1007/s13132-024-01755-w 10.1016/j.tust.2023.105243 10.1016/j.undsp.2021.11.004 |
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| Keywords | Existing tunnel Random forest recursive feature elimination Feature selection Natural gradient boosting algorithm Adjacent foundation pit construction Shapley additive ExPlanations |
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| References | Chen, Yang, Feng, Liu, Qin (bb0095) 2023; 124 Wei, Qi, Chen, Zhang, Qian, Zhou (bb0295) 2022; 35 Fu, Wu, Ponnarasu, Zhang (bb0225) 2023; 212 Zhang, Hu, Liu, Tan (bb0195) 2020; 103 Tao, He, Sun, Cai, Chen (bb0320) 2022; 7 Yan, Fan, Zhang (bb0405) 2023; 273 Mahmoodzadeh, Mohammadi, Hashim Ibrahim, Nariman Abdulhamid, Ali, Hasan, Khishe, Mahmud (bb0175) 2021; 128 Liu, Li, Fang, Qi, Shen, Zhou, Zhang (bb0385) 2021; 125 Liu, Xue, Wang, Zhang, Zhang (bb0055) 2023; 15 Chen, Shen, Feng, Liu (bb0005) 2023; 98 Kim, Kwon, Pham, Oh, Choi (bb0070) 2022; 140 Liu, Lin, Chen, Liu, Guo (bb0330) 2022; 2022 Lin, Zhou, Shen (bb0315) 2023; 138 Chen, Wang, Feng, Liu, Xu, Qin (bb0285) 2023; 98 Ge, Gao, Cui, Chen, Wang (bb0080) 2022; 142 Linardatos, Papastefanopoulos, Kotsiantis (bb0210) 2020; 23 Zhang, Huang, Wang (bb0355) 2013; 38 Roy, Chakraborty (bb0115) 2023; 233 Liu, Chen, Zhang (bb0120) 2021; 27 Wu, Zheng, Feng, Chen, Qin, Xu, Liu (bb0155) 2022; 333 Wu, Hou, Wang, Yin, Yu (bb0380) 2023; 149 Liu, Wang, Chen, Zhang, Zhao, Devici, Jin, Skibniewski (bb0260) 2023 Chen, Cao, Liu, Qin, Xia (bb0110) 2023; 371 Wu, Feng, Yang, Qin, Chen, Liu (bb0010) 2024; 163 Mei, Sun, Li, Xu, Zhang, Shen (bb0145) 2022; 142 Hu, Sun, Pei, Han, Li (bb0365) 2024; 242 Li, Pan, Zhang, Chen (bb0300) 2023; 140 Pan, Zhang (bb0360) 2022; 138 Yu, Wang, Wang, Ling, Zhang, Wang, Qu (bb0045) 2021; 2021 Punmiya, Choe (bb0125) 2019; 10 Duan, Avati, Ding, Thai, Basu, Ng, Schuler (bb0130) 2019 Lei, Feng, Dong, Zhai (bb0370) 2024; 301 Wang, Zhang, Fu (bb0220) 2023; 147 Zhao, Chen, Hu, Huang, Lu, Yao (bb0345) 2023; 142 Sun, Ding, Zhang, Jia (bb0180) 2021; 25 Huang, Zhang, Wang, Chen, Liu (bb0275) 2024 Kim, Pham, Oh, Lee, Choi (bb0170) 2022; 135 Wu, Feng, Liu, Qin, Yang, Duan (bb0025) 2023; 132 Zhang, Cao, Xia, Zhang, Xu, Liu (bb0265) 2023; 29 Zhou, Hu, Hu, Zhen (bb0185) 2022; 7 Pang, Li, Dong, Gong (bb0375) 2024; 163 Cao, Su, Antwi Afari, Lei, Wu, Liu (bb0270) 2024 Ye, Jin, Chen (bb0075) 2022; 124 Liu, Cao, Wang, Chen, Qin (bb0240) 2022; 356 Liu, Chen, Zhang, Wu, Wang (bb0280) 2020; 272 Sun, Chen, Zhang, Kuang (bb0040) 2019; 106 Chen, Li, Feng, Wang, Qin, Skibniewski, Chen, Liu (bb0200) 2023; 632 Wu, Li, Qin, Xu, Liu (bb0245) 2023; 339 Sun, Wu, Zhang, Zhang, Wang (bb0395) 2022; 59 Zhao, Wang, Zhongwei, Dai, Yin, Cao, Zhou (bb0065) 2022; 12 Zhang, Wu, Zhong, Li, Wang (bb0190) 2021; 12 Zhou, Chen, Tu, Zhang (bb0340) 2015; 23 Wu, Lan, Liu, Chen, Meng, Xu (bb0350) 2023; 132 de Menezes, Bispo, Faria, Gonçalves, Curi, Guilherme (bb0165) 2020; 712 Liu, Wu, Lu, Chen, Zhang (bb0310) 2024; 147 Wei, Feng, Cui, Wang, Diao, Wu (bb0050) 2023; 140 Zhao, Chen, Hu, Wang, Li (bb0335) 2023; 131 Zhou, Zhou, Zhou, Yang, Luo (bb0150) 2014; 46 Anh, Pandey, Mishra, Singh, Ahmadi, Janizadeh, Tran, Linh, Dang (bb0400) 2023; 132 Qiu, Jiang, Zhou, Zhang, Pan (bb0035) 2021; 28 Ling, Kong, Tang, Zhao, Tang, Zhang (bb0100) 2022; 35 Wang, Chen, Liu, Li, Zhang (bb0255) 2023; 57 Zhang, Yuan, Long, Yao, Jia, Liu (bb0305) 2024; 168 Chen, Li, Feng, Wang, Qin, Skibniewski, Chen, Liu (bb0105) 2023; 632 Fan, Song, Xu, Wang, Zhang (bb0060) 2021; 21 Zhang, Wu, Chen, Chan (bb0090) 2020; 99 Fu, Wu, Tiong, Zhang (bb0230) 2023; 146 Feng, Wang, Zhang, Wang, Jin (bb0030) 2022; 7 Liu, Li, Xu, Wang, Huang, He (bb0085) 2023; 300 Lundberg, Lee (bb0215) 2017 Zhou, Wen, Zhang, Xu, Zhang (bb0250) 2021; 12 Qian, Lin (bb0020) 2016; 8 Kolappan Geetha, Sim (bb0205) 2022; 143 Shen, Ong, Li, Hui, Wilder-Smith (bb0160) 2007; 54 Chakraborty, Elhegazy, Elzarka, Gutierrez (bb0140) 2020; 46 Zhou, Hu, Zhang, Ye, Zhao, Bian (bb0325) 2024; 17 Meng, Chen, Liu, Wu, Cheng (bb0290) 2023; 132 Zhu, Chu, Wang, Wu, Yan, Chiam (bb0135) 2021; 13 Zhuang, Cui, Hu (bb0015) 2023; 132 Chen, Cheng, Qin, Xu, Liu (bb0235) 2024; 449 Zhang, Liu, Wang, Zhang, Han, Yu (bb0390) 2021; 99 Zhuang (10.1016/j.autcon.2024.105516_bb0015) 2023; 132 Roy (10.1016/j.autcon.2024.105516_bb0115) 2023; 233 Tao (10.1016/j.autcon.2024.105516_bb0320) 2022; 7 Kolappan Geetha (10.1016/j.autcon.2024.105516_bb0205) 2022; 143 Chen (10.1016/j.autcon.2024.105516_bb0200) 2023; 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46 Zhao (10.1016/j.autcon.2024.105516_bb0345) 2023; 142 Chen (10.1016/j.autcon.2024.105516_bb0095) 2023; 124 Yan (10.1016/j.autcon.2024.105516_bb0405) 2023; 273 Fu (10.1016/j.autcon.2024.105516_bb0225) 2023; 212 Sun (10.1016/j.autcon.2024.105516_bb0040) 2019; 106 Zhang (10.1016/j.autcon.2024.105516_bb0195) 2020; 103 Kim (10.1016/j.autcon.2024.105516_bb0070) 2022; 140 Ling (10.1016/j.autcon.2024.105516_bb0100) 2022; 35 Zhao (10.1016/j.autcon.2024.105516_bb0065) 2022; 12 Zhou (10.1016/j.autcon.2024.105516_bb0325) 2024; 17 Duan (10.1016/j.autcon.2024.105516_bb0130) 2019 Li (10.1016/j.autcon.2024.105516_bb0300) 2023; 140 Wu (10.1016/j.autcon.2024.105516_bb0010) 2024; 163 Qiu (10.1016/j.autcon.2024.105516_bb0035) 2021; 28 Zhou (10.1016/j.autcon.2024.105516_bb0150) 2014; 46 Shen (10.1016/j.autcon.2024.105516_bb0160) 2007; 54 Zhou (10.1016/j.autcon.2024.105516_bb0340) 2015; 23 Pang (10.1016/j.autcon.2024.105516_bb0375) 2024; 163 Ye (10.1016/j.autcon.2024.105516_bb0075) 2022; 124 Sun (10.1016/j.autcon.2024.105516_bb0180) 2021; 25 Zhu (10.1016/j.autcon.2024.105516_bb0135) 2021; 13 Liu (10.1016/j.autcon.2024.105516_bb0330) 2022; 2022 Liu (10.1016/j.autcon.2024.105516_bb0085) 2023; 300 Mei (10.1016/j.autcon.2024.105516_bb0145) 2022; 142 Wei (10.1016/j.autcon.2024.105516_bb0050) 2023; 140 Wang (10.1016/j.autcon.2024.105516_bb0255) 2023; 57 Wu (10.1016/j.autcon.2024.105516_bb0350) 2023; 132 Chen (10.1016/j.autcon.2024.105516_bb0005) 2023; 98 Liu (10.1016/j.autcon.2024.105516_bb0260) 2023 Zhang (10.1016/j.autcon.2024.105516_bb0305) 2024; 168 Wu (10.1016/j.autcon.2024.105516_bb0025) 2023; 132 Feng (10.1016/j.autcon.2024.105516_bb0030) 2022; 7 Wei (10.1016/j.autcon.2024.105516_bb0295) 2022; 35 Yu (10.1016/j.autcon.2024.105516_bb0045) 2021; 2021 Liu (10.1016/j.autcon.2024.105516_bb0280) 2020; 272 Wu (10.1016/j.autcon.2024.105516_bb0155) 2022; 333 Fu (10.1016/j.autcon.2024.105516_bb0230) 2023; 146 Wang (10.1016/j.autcon.2024.105516_bb0220) 2023; 147 Lin (10.1016/j.autcon.2024.105516_bb0315) 2023; 138 Fan (10.1016/j.autcon.2024.105516_bb0060) 2021; 21 Meng (10.1016/j.autcon.2024.105516_bb0290) 2023; 132 Chen (10.1016/j.autcon.2024.105516_bb0235) 2024; 449 Qian (10.1016/j.autcon.2024.105516_bb0020) 2016; 8 Zhang (10.1016/j.autcon.2024.105516_bb0265) 2023; 29 Chen (10.1016/j.autcon.2024.105516_bb0105) 2023; 632 Lundberg (10.1016/j.autcon.2024.105516_bb0215) 2017 Anh (10.1016/j.autcon.2024.105516_bb0400) 2023; 132 de Menezes (10.1016/j.autcon.2024.105516_bb0165) 2020; 712 Chen (10.1016/j.autcon.2024.105516_bb0110) 2023; 371 Zhang (10.1016/j.autcon.2024.105516_bb0090) 2020; 99 Zhou (10.1016/j.autcon.2024.105516_bb0185) 2022; 7 Liu (10.1016/j.autcon.2024.105516_bb0120) 2021; 27 Liu (10.1016/j.autcon.2024.105516_bb0240) 2022; 356 Sun (10.1016/j.autcon.2024.105516_bb0395) 2022; 59 Wu (10.1016/j.autcon.2024.105516_bb0380) 2023; 149 Ge (10.1016/j.autcon.2024.105516_bb0080) 2022; 142 Zhou (10.1016/j.autcon.2024.105516_bb0250) 2021; 12 |
| References_xml | – volume: 106 start-page: 193 year: 2019 end-page: 198 ident: bb0040 article-title: Analytical investigation of tunnel deformation caused by circular foundation pit excavation publication-title: Comput. Geotech. – start-page: 142746 year: 2024 ident: bb0270 article-title: Enhancing mix proportion design of low carbon concrete for shield segment using a combination of Bayesian optimization-NGBoost and NSGA-III algorithm publication-title: J Clean Prod – volume: 632 start-page: 105 year: 2023 end-page: 129 ident: bb0200 article-title: Shield attitude prediction based on Bayesian-LGBM machine learning publication-title: Inf. Sci. – volume: 132 year: 2023 ident: bb0025 article-title: Enhanced safety prediction of vault settlement in urban tunnels using the pair-copula and Bayesian network publication-title: Appl Soft Comput – volume: 163 year: 2024 ident: bb0375 article-title: Convolutional neural network-based model for recognizing TBM rock chip gradation, Automation in Construction – volume: 273 year: 2023 ident: bb0405 article-title: Predicting the NOx emissions of low heat value gas rich-quench-lean combustor via three integrated learning algorithms with Bayesian optimization publication-title: Energy – volume: 632 start-page: 105 year: 2023 end-page: 129 ident: bb0105 article-title: Shield attitude prediction based on Bayesian-LGBM machine learning publication-title: Inform Sci. – year: 2024 ident: bb0275 article-title: Evaluating Media Knowledge Capabilities of Intelligent Search Dialogue Systems: A Case Study of ChatGPT and New Bing publication-title: J Knowl Econ – volume: 233 year: 2023 ident: bb0115 article-title: Support vector machine in structural reliability analysis: a review publication-title: Reliab. Eng. Syst. Saf. – year: 2019 ident: bb0130 article-title: NGBoost: Natural Gradient Boosting for Probabilistic Prediction – volume: 371 year: 2023 ident: bb0110 article-title: Enhancing the durability of concrete in severely cold regions: Mix proportion optimization based on machine learning publication-title: Constr. Build. Mater. – volume: 128 year: 2021 ident: bb0175 article-title: Machine learning forecasting models of disc cutters life of tunnel boring machine publication-title: Autom. Constr. – volume: 147 year: 2023 ident: bb0220 article-title: Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI) publication-title: Autom. Constr. – volume: 57 year: 2023 ident: bb0255 article-title: Application of copula-based Bayesian network method to water leakage risk analysis in cross river tunnel of Wuhan Rail Transit Line 3 publication-title: Adv. Eng. Inform. – volume: 21 start-page: 109 year: 2021 ident: bb0060 article-title: Tunnel deformation and stress response under the bilateral foundation pit construction: a case study publication-title: Archives of Civil and Mechanical Engineering – volume: 142 year: 2022 ident: bb0145 article-title: Probabilistic prediction model of steel to concrete bond failure under high temperature by machine learning publication-title: Eng. Fail. Anal. – volume: 142 year: 2023 ident: bb0345 article-title: Automatic monitoring and control of excavation disturbance of an ultra-deep foundation pit extremely adjacent to metro tunnels publication-title: Tunn. Undergr. Space Technol. – volume: 38 start-page: 244 year: 2013 end-page: 253 ident: bb0355 article-title: Evaluation of deformation response for adjacent tunnels due to soil unloading in excavation engineering publication-title: Tunn. Undergr. Space Technol. – volume: 17 start-page: 320 year: 2024 end-page: 360 ident: bb0325 article-title: Adaptive mutation sparrow search algorithm-Elman-AdaBoost model for predicting the deformation of subway tunnels publication-title: Underground Space – volume: 242 year: 2024 ident: bb0365 article-title: Evaluate asphalt pavement frictional characteristics based on IGWO-NGBoost using 3D macro-texture data publication-title: Expert Syst. Appl. – volume: 138 year: 2023 ident: bb0315 article-title: Safety assessment of excavation system via TOPSIS-based MCDM modelling in fuzzy environment publication-title: Appl. Soft Comput. – volume: 15 start-page: 9740 year: 2023 ident: bb0055 article-title: Numerical study on the behavior of an existing tunnel during excavating adjacent deep foundation pit publication-title: Sustainability – volume: 212 year: 2023 ident: bb0225 article-title: A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns publication-title: Expert Syst. Appl. – volume: 7 start-page: 735 year: 2022 end-page: 747 ident: bb0320 article-title: Multi-objective optimization-based prediction of excavation-induced tunnel displacement publication-title: Underground Space – volume: 132 year: 2023 ident: bb0400 article-title: Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm publication-title: Appl. Soft Comput. – volume: 712 year: 2020 ident: bb0165 article-title: Modeling arsenic content in Brazilian soils: what is relevant? publication-title: Sci. Total Environ. – volume: 131 year: 2023 ident: bb0335 article-title: Evolution of tunnel uplift induced by adjacent long and collinear excavation and an effective protective measure publication-title: Tunn. Undergr. Space Technol. – volume: 149 year: 2023 ident: bb0380 article-title: Predictive modeling of loader's working resistance measurement based on multi-sourced parameter data publication-title: Autom. Constr. – volume: 124 year: 2023 ident: bb0095 article-title: Safety evaluation of buildings adjacent to shield construction in karst areas: An improved extension cloud approach publication-title: Eng Appl Artif Intel – year: 2017 ident: bb0215 article-title: A Unified Approach to Interpreting Model Predictions – volume: 135 year: 2022 ident: bb0170 article-title: Classification of surface settlement levels induced by TBM driving in urban areas using random forest with data-driven feature selection publication-title: Autom. Constr. – volume: 99 year: 2020 ident: bb0090 article-title: Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: a comparative study publication-title: Tunn. Undergr. Space Technol. – volume: 124 year: 2022 ident: bb0075 article-title: Machine learning-based forecasting of soil settlement induced by shield tunneling construction publication-title: Tunn. Undergr. Space Technol. – volume: 132 year: 2023 ident: bb0290 article-title: Impacts of reinforced wall on nearby excavation-induced ground and tunnel responses: a centrifugal and numerical study publication-title: Tunn. Undergr. Space Technol. – volume: 12 year: 2021 ident: bb0250 article-title: Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization publication-title: Geosci. Front. – volume: 13 start-page: 1231 year: 2021 end-page: 1245 ident: bb0135 article-title: Prediction of rockhead using a hybrid N-XGBoost machine learning framework publication-title: J. Rock Mech. Geotech. Eng. – volume: 140 year: 2023 ident: bb0300 article-title: Dynamic and explainable deep learning-based risk prediction on adjacent building induced by deep excavation publication-title: Tunn. Undergr. Space Technol. – volume: 7 start-page: 514 year: 2022 end-page: 527 ident: bb0030 article-title: An improved artificial bee colony-random forest (IABC-RF) model for predicting the tunnel deformation due to an adjacent foundation pit excavation publication-title: Underground Space – volume: 8 start-page: 423 year: 2016 end-page: 442 ident: bb0020 article-title: Safety risk management of underground engineering in China: Progress, challenges and strategies publication-title: J. Rock Mech. Geotech. Eng. – volume: 138 year: 2022 ident: bb0360 article-title: Mitigating tunnel-induced damages using deep neural networks publication-title: Autom. Constr. – volume: 98 start-page: 104823 year: 2023 ident: bb0005 article-title: Vulnerability assessment in urban metro systems based on an improved cloud model and a Bayesian network publication-title: Sustain. Cities. Soc. – volume: 98 year: 2023 ident: bb0285 article-title: Research on the risk evaluation of urban wastewater treatment projects based on an improved fuzzy cognitive map publication-title: Sustain Cities Soc – volume: 10 start-page: 2326 year: 2019 end-page: 2329 ident: bb0125 article-title: Energy theft detection using gradient boosting theft detector with feature engineering-based preprocessing publication-title: IEEE Transact Smart Grid – volume: 46 start-page: 82 year: 2014 end-page: 90 ident: bb0150 article-title: Structure damage detection based on random forest recursive feature elimination publication-title: Mech. Syst. Signal Process. – volume: 2022 start-page: 7227330 year: 2022 ident: bb0330 article-title: Deformation Stability Response of Adjacent Subway Tunnels considering Excavation and Support of Foundation Pit publication-title: Lithosphere – volume: 449 year: 2024 ident: bb0235 article-title: Sustainability evaluation of urban large-scale infrastructure construction based on dynamic fuzzy cognitive map publication-title: J Clean Prod – volume: 27 start-page: 539 year: 2021 end-page: 552 ident: bb0120 article-title: Risk prediction and diagnosis of water seepage in operational shield tunnels based on random forest publication-title: J. Civ. Eng. Manag. – volume: 54 start-page: 1231 year: 2007 end-page: 1237 ident: bb0160 article-title: A feature selection method for multilevel mental fatigue EEG classification publication-title: IEEE Trans. Biomed. Eng. – volume: 300 year: 2023 ident: bb0085 article-title: Building information modelling-enabled multi-objective optimization for energy consumption parametric analysis in green buildings design using hybrid machine learning algorithms publication-title: Energ Build. – volume: 28 start-page: 1888 year: 2021 end-page: 1900 ident: bb0035 article-title: Analytical solution for evaluating deformation response of existing metro tunnel due to excavation of adjacent foundation pit publication-title: J. Cent. South Univ. – volume: 23 start-page: 18 year: 2020 ident: bb0210 article-title: Explainable AI: a review of machine learning interpretability methods publication-title: Entropy – volume: 146 year: 2023 ident: bb0230 article-title: Data-driven real-time advanced geological prediction in tunnel construction using a hybrid deep learning approach publication-title: Autom. Constr. – volume: 23 start-page: 287 year: 2015 end-page: 297 ident: bb0340 article-title: An analytic study on the deflection of subway tunnel due to adjacent excavation of foundation pit publication-title: J Modern Transportation – volume: 29 start-page: 516 year: 2023 end-page: 529 ident: bb0265 article-title: Intelligent prediction of the frost resistance of high-performance concrete: a machine learning method publication-title: J. Civil Eng. Manage. – volume: 35 year: 2022 ident: bb0100 article-title: Predicting earth pressure balance (EPB) shield tunneling-induced ground settlement in compound strata using random forest publication-title: Transportation Geotechnics – volume: 2021 start-page: 5587857 year: 2021 ident: bb0045 article-title: Experimental and numerical investigation on the effects of foundation pit excavation on adjacent tunnels in soft soil publication-title: Math. Probl. Eng. – volume: 132 year: 2023 ident: bb0350 article-title: Field performance of an anti-uplift portal frame in control of the tunnel uplift induced by overlying excavation publication-title: Tunn. Undergr. Space Technol. – volume: 46 year: 2020 ident: bb0140 article-title: A novel construction cost prediction model using hybrid natural and light gradient boosting publication-title: Adv. Eng. Inform. – volume: 356 year: 2022 ident: bb0240 article-title: Prediction of the durability of high-performance concrete using an integrated RF-LSSVM model publication-title: Constr. Build. Mater. – volume: 132 year: 2023 ident: bb0015 article-title: Numerical simulation and simplified analytical method to evaluate the displacement of adjacent tunnels caused by excavation publication-title: Tunn. Undergr. Space Technol. – year: 2023 ident: bb0260 article-title: Evaluating Digital Health Services Quality via Social Media publication-title: Ieee T Eng Manage – volume: 125 year: 2021 ident: bb0385 article-title: Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network publication-title: Autom. Constr. – volume: 140 year: 2022 ident: bb0070 article-title: Surface settlement prediction for urban tunneling using machine learning algorithms with Bayesian optimization publication-title: Autom. Constr. – volume: 35 year: 2022 ident: bb0295 article-title: Analysis of the protective effect of setting isolation piles outside the foundation pit on the underpass tunnel side publication-title: Transportation Geotechnics – volume: 12 start-page: 4752 year: 2022 ident: bb0065 article-title: Numerical study on the deformation of tunnels by excavation of foundation pit adjacent to the Subway publication-title: Appl. Sci. – volume: 272 start-page: 122542 year: 2020 ident: bb0280 article-title: Energy consumption prediction and diagnosis of public buildings based on support vector machine learning: A case study in China publication-title: J Clean Prod – volume: 99 year: 2021 ident: bb0390 article-title: StackPDB: predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier publication-title: Appl. Soft Comput. – volume: 103 year: 2020 ident: bb0195 article-title: TBM performance prediction with Bayesian optimization and automated machine learning publication-title: Tunn. Undergr. Space Technol. – volume: 143 year: 2022 ident: bb0205 article-title: Fast identification of concrete cracks using 1D deep learning and explainable artificial intelligence-based analysis publication-title: Autom. Constr. – volume: 12 start-page: 469 year: 2021 end-page: 477 ident: bb0190 article-title: Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization publication-title: Geosci. Front. – volume: 59 year: 2022 ident: bb0395 article-title: Based on multi-algorithm hybrid method to predict the slope safety factor-- stacking ensemble learning with bayesian optimization publication-title: J. Comput. Sci. – volume: 7 start-page: 255 year: 2022 end-page: 263 ident: bb0185 article-title: An adaptive hyper parameter tuning model for ship fuel consumption prediction under complex maritime environments publication-title: Journal of Ocean Engineering and Science – volume: 168 year: 2024 ident: bb0305 article-title: Prediction of surface settlement around subway foundation pits based on spatiotemporal characteristics and deep learning models publication-title: Comput. Geotech. – volume: 301 year: 2024 ident: bb0370 article-title: Bayesian-optimized interpretable surrogate model for seismic demand prediction of urban highway bridges publication-title: Eng. Struct. – volume: 142 year: 2022 ident: bb0080 article-title: Safety prediction of shield tunnel construction using deep belief network and whale optimization algorithm publication-title: Autom. Constr. – volume: 140 year: 2023 ident: bb0050 article-title: Research on the influence of foundation pit excavation on the lateral force and deformation of side shield tunnels based on full-scale experiments publication-title: Tunn. Undergr. Space Technol. – volume: 333 year: 2022 ident: bb0155 article-title: Prediction of the frost resistance of high-performance concrete based on RF-REF: a hybrid prediction approach publication-title: Constr. Build. Mater. – volume: 147 year: 2024 ident: bb0310 article-title: Effect and control of foundation pit excavation on existing tunnels: a state-of-the-art review publication-title: Tunn. Undergr. Space Technol. – volume: 25 start-page: 5633 year: 2021 end-page: 5644 ident: bb0180 article-title: An improved grid search algorithm to optimize SVR for prediction publication-title: Soft. Comput. – volume: 163 start-page: 105421 year: 2024 ident: bb0010 article-title: Safety risk perception and control of water inrush during tunnel excavation in karst areas: An improved uncertain information fusion method publication-title: Automat Constr – volume: 339 year: 2023 ident: bb0245 article-title: Intelligent multiobjective optimization design for NZEBs in China publication-title: Four climatic regions,Appl Energ – volume: 46 start-page: 82 issue: 1 year: 2014 ident: 10.1016/j.autcon.2024.105516_bb0150 article-title: Structure damage detection based on random forest recursive feature elimination publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2013.12.013 – volume: 632 start-page: 105 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0200 article-title: Shield attitude prediction based on Bayesian-LGBM machine learning publication-title: Inf. Sci. doi: 10.1016/j.ins.2023.03.004 – volume: 168 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0305 article-title: Prediction of surface settlement around subway foundation pits based on spatiotemporal characteristics and deep learning models publication-title: Comput. Geotech. doi: 10.1016/j.compgeo.2024.106149 – volume: 125 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0385 article-title: Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network publication-title: Autom. Constr. doi: 10.1016/j.autcon.2021.103647 – volume: 98 start-page: 104823 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0005 article-title: Vulnerability assessment in urban metro systems based on an improved cloud model and a Bayesian network publication-title: Sustain. Cities. Soc. doi: 10.1016/j.scs.2023.104823 – start-page: 142746 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0270 article-title: Enhancing mix proportion design of low carbon concrete for shield segment using a combination of Bayesian optimization-NGBoost and NSGA-III algorithm publication-title: J Clean Prod doi: 10.1016/j.jclepro.2024.142746 – volume: 140 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0050 article-title: Research on the influence of foundation pit excavation on the lateral force and deformation of side shield tunnels based on full-scale experiments publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2023.105236 – volume: 57 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0255 article-title: Application of copula-based Bayesian network method to water leakage risk analysis in cross river tunnel of Wuhan Rail Transit Line 3 publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2023.102056 – volume: 29 start-page: 516 issue: 6 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0265 article-title: Intelligent prediction of the frost resistance of high-performance concrete: a machine learning method publication-title: J. Civil Eng. Manage. doi: 10.3846/jcem.2023.19226 – volume: 128 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0175 article-title: Machine learning forecasting models of disc cutters life of tunnel boring machine publication-title: Autom. Constr. doi: 10.1016/j.autcon.2021.103779 – volume: 132 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0400 article-title: Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2022.109848 – volume: 2021 start-page: 5587857 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0045 article-title: Experimental and numerical investigation on the effects of foundation pit excavation on adjacent tunnels in soft soil publication-title: Math. Probl. Eng. – volume: 21 start-page: 109 issue: 3 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0060 article-title: Tunnel deformation and stress response under the bilateral foundation pit construction: a case study publication-title: Archives of Civil and Mechanical Engineering doi: 10.1007/s43452-021-00259-7 – volume: 99 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0090 article-title: Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: a comparative study publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2020.103383 – volume: 35 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0100 article-title: Predicting earth pressure balance (EPB) shield tunneling-induced ground settlement in compound strata using random forest publication-title: Transportation Geotechnics doi: 10.1016/j.trgeo.2022.100771 – volume: 142 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0345 article-title: Automatic monitoring and control of excavation disturbance of an ultra-deep foundation pit extremely adjacent to metro tunnels publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2023.105445 – volume: 356 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0240 article-title: Prediction of the durability of high-performance concrete using an integrated RF-LSSVM model publication-title: Constr. Build. Mater. doi: 10.1016/j.conbuildmat.2022.129232 – volume: 7 start-page: 255 issue: 3 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0185 article-title: An adaptive hyper parameter tuning model for ship fuel consumption prediction under complex maritime environments publication-title: Journal of Ocean Engineering and Science doi: 10.1016/j.joes.2021.08.007 – volume: 35 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0295 article-title: Analysis of the protective effect of setting isolation piles outside the foundation pit on the underpass tunnel side publication-title: Transportation Geotechnics doi: 10.1016/j.trgeo.2022.100791 – volume: 142 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0080 article-title: Safety prediction of shield tunnel construction using deep belief network and whale optimization algorithm publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104488 – volume: 132 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0015 article-title: Numerical simulation and simplified analytical method to evaluate the displacement of adjacent tunnels caused by excavation publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2022.104879 – volume: 140 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0070 article-title: Surface settlement prediction for urban tunneling using machine learning algorithms with Bayesian optimization publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104331 – volume: 273 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0405 article-title: Predicting the NOx emissions of low heat value gas rich-quench-lean combustor via three integrated learning algorithms with Bayesian optimization publication-title: Energy doi: 10.1016/j.energy.2023.127227 – volume: 15 start-page: 9740 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0055 article-title: Numerical study on the behavior of an existing tunnel during excavating adjacent deep foundation pit publication-title: Sustainability doi: 10.3390/su15129740 – volume: 138 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0315 article-title: Safety assessment of excavation system via TOPSIS-based MCDM modelling in fuzzy environment publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2023.110206 – volume: 54 start-page: 1231 issue: 7 year: 2007 ident: 10.1016/j.autcon.2024.105516_bb0160 article-title: A feature selection method for multilevel mental fatigue EEG classification publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2007.890733 – volume: 103 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0195 article-title: TBM performance prediction with Bayesian optimization and automated machine learning publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2020.103493 – volume: 12 start-page: 469 issue: 1 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0190 article-title: Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization publication-title: Geosci. Front. doi: 10.1016/j.gsf.2020.03.007 – volume: 28 start-page: 1888 issue: 6 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0035 article-title: Analytical solution for evaluating deformation response of existing metro tunnel due to excavation of adjacent foundation pit publication-title: J. Cent. South Univ. doi: 10.1007/s11771-021-4737-3 – volume: 106 start-page: 193 year: 2019 ident: 10.1016/j.autcon.2024.105516_bb0040 article-title: Analytical investigation of tunnel deformation caused by circular foundation pit excavation publication-title: Comput. Geotech. doi: 10.1016/j.compgeo.2018.11.001 – volume: 46 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0140 article-title: A novel construction cost prediction model using hybrid natural and light gradient boosting publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2020.101201 – volume: 124 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0075 article-title: Machine learning-based forecasting of soil settlement induced by shield tunneling construction publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2022.104452 – volume: 131 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0335 article-title: Evolution of tunnel uplift induced by adjacent long and collinear excavation and an effective protective measure publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2022.104846 – volume: 132 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0290 article-title: Impacts of reinforced wall on nearby excavation-induced ground and tunnel responses: a centrifugal and numerical study publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2022.104903 – volume: 27 start-page: 539 issue: 7 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0120 article-title: Risk prediction and diagnosis of water seepage in operational shield tunnels based on random forest publication-title: J. Civ. Eng. Manag. doi: 10.3846/jcem.2021.14901 – volume: 272 start-page: 122542 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0280 article-title: Energy consumption prediction and diagnosis of public buildings based on support vector machine learning: A case study in China publication-title: J Clean Prod doi: 10.1016/j.jclepro.2020.122542 – volume: 147 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0310 article-title: Effect and control of foundation pit excavation on existing tunnels: a state-of-the-art review publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2024.105704 – volume: 132 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0350 article-title: Field performance of an anti-uplift portal frame in control of the tunnel uplift induced by overlying excavation publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2022.104908 – volume: 138 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0360 article-title: Mitigating tunnel-induced damages using deep neural networks publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104219 – volume: 712 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0165 article-title: Modeling arsenic content in Brazilian soils: what is relevant? publication-title: Sci. Total Environ. doi: 10.1016/j.scitotenv.2020.136511 – volume: 163 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0375 – volume: 124 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0095 article-title: Safety evaluation of buildings adjacent to shield construction in karst areas: An improved extension cloud approach publication-title: Eng Appl Artif Intel doi: 10.1016/j.engappai.2023.106386 – volume: 17 start-page: 320 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0325 article-title: Adaptive mutation sparrow search algorithm-Elman-AdaBoost model for predicting the deformation of subway tunnels publication-title: Underground Space doi: 10.1016/j.undsp.2023.09.014 – volume: 25 start-page: 5633 issue: 7 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0180 article-title: An improved grid search algorithm to optimize SVR for prediction publication-title: Soft. Comput. doi: 10.1007/s00500-020-05560-w – volume: 99 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0390 article-title: StackPDB: predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106921 – volume: 233 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0115 article-title: Support vector machine in structural reliability analysis: a review publication-title: Reliab. Eng. Syst. Saf. doi: 10.1016/j.ress.2023.109126 – volume: 147 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0220 article-title: Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI) publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104730 – volume: 7 start-page: 735 issue: 5 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0320 article-title: Multi-objective optimization-based prediction of excavation-induced tunnel displacement publication-title: Underground Space doi: 10.1016/j.undsp.2021.12.005 – volume: 98 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0285 article-title: Research on the risk evaluation of urban wastewater treatment projects based on an improved fuzzy cognitive map publication-title: Sustain Cities Soc doi: 10.1016/j.scs.2023.104796 – volume: 23 start-page: 287 issue: 4 year: 2015 ident: 10.1016/j.autcon.2024.105516_bb0340 article-title: An analytic study on the deflection of subway tunnel due to adjacent excavation of foundation pit publication-title: J Modern Transportation doi: 10.1007/s40534-015-0087-x – volume: 13 start-page: 1231 issue: 6 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0135 article-title: Prediction of rockhead using a hybrid N-XGBoost machine learning framework publication-title: J. Rock Mech. Geotech. Eng. doi: 10.1016/j.jrmge.2021.06.012 – volume: 449 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0235 article-title: Sustainability evaluation of urban large-scale infrastructure construction based on dynamic fuzzy cognitive map publication-title: J Clean Prod doi: 10.1016/j.jclepro.2024.141774 – volume: 12 start-page: 4752 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0065 article-title: Numerical study on the deformation of tunnels by excavation of foundation pit adjacent to the Subway publication-title: Appl. Sci. doi: 10.3390/app12094752 – volume: 301 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0370 article-title: Bayesian-optimized interpretable surrogate model for seismic demand prediction of urban highway bridges publication-title: Eng. Struct. doi: 10.1016/j.engstruct.2023.117307 – volume: 333 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0155 article-title: Prediction of the frost resistance of high-performance concrete based on RF-REF: a hybrid prediction approach publication-title: Constr. Build. Mater. doi: 10.1016/j.conbuildmat.2022.127132 – volume: 132 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0025 article-title: Enhanced safety prediction of vault settlement in urban tunnels using the pair-copula and Bayesian network publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2022.109711 – volume: 135 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0170 article-title: Classification of surface settlement levels induced by TBM driving in urban areas using random forest with data-driven feature selection publication-title: Autom. Constr. doi: 10.1016/j.autcon.2021.104109 – volume: 12 issue: 5 year: 2021 ident: 10.1016/j.autcon.2024.105516_bb0250 article-title: Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization publication-title: Geosci. Front. doi: 10.1016/j.gsf.2021.101211 – volume: 8 start-page: 423 issue: 4 year: 2016 ident: 10.1016/j.autcon.2024.105516_bb0020 article-title: Safety risk management of underground engineering in China: Progress, challenges and strategies publication-title: J. Rock Mech. Geotech. Eng. doi: 10.1016/j.jrmge.2016.04.001 – year: 2019 ident: 10.1016/j.autcon.2024.105516_bb0130 – volume: 212 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0225 article-title: A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2022.118721 – volume: 143 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0205 article-title: Fast identification of concrete cracks using 1D deep learning and explainable artificial intelligence-based analysis publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104572 – volume: 146 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0230 article-title: Data-driven real-time advanced geological prediction in tunnel construction using a hybrid deep learning approach publication-title: Autom. Constr. doi: 10.1016/j.autcon.2022.104672 – volume: 242 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0365 article-title: Evaluate asphalt pavement frictional characteristics based on IGWO-NGBoost using 3D macro-texture data publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2023.122786 – volume: 632 start-page: 105 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0105 article-title: Shield attitude prediction based on Bayesian-LGBM machine learning publication-title: Inform Sci. doi: 10.1016/j.ins.2023.03.004 – volume: 339 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0245 article-title: Intelligent multiobjective optimization design for NZEBs in China publication-title: Four climatic regions,Appl Energ – volume: 10 start-page: 2326 issue: 2 year: 2019 ident: 10.1016/j.autcon.2024.105516_bb0125 article-title: Energy theft detection using gradient boosting theft detector with feature engineering-based preprocessing publication-title: IEEE Transact Smart Grid doi: 10.1109/TSG.2019.2892595 – volume: 142 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0145 article-title: Probabilistic prediction model of steel to concrete bond failure under high temperature by machine learning publication-title: Eng. Fail. Anal. doi: 10.1016/j.engfailanal.2022.106786 – volume: 371 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0110 article-title: Enhancing the durability of concrete in severely cold regions: Mix proportion optimization based on machine learning publication-title: Constr. Build. Mater. doi: 10.1016/j.conbuildmat.2023.130644 – year: 2017 ident: 10.1016/j.autcon.2024.105516_bb0215 – volume: 2022 start-page: 7227330 issue: Special 10 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0330 article-title: Deformation Stability Response of Adjacent Subway Tunnels considering Excavation and Support of Foundation Pit publication-title: Lithosphere doi: 10.2113/2022/7227330 – volume: 38 start-page: 244 year: 2013 ident: 10.1016/j.autcon.2024.105516_bb0355 article-title: Evaluation of deformation response for adjacent tunnels due to soil unloading in excavation engineering publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2013.07.002 – volume: 59 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0395 article-title: Based on multi-algorithm hybrid method to predict the slope safety factor-- stacking ensemble learning with bayesian optimization publication-title: J. Comput. Sci. doi: 10.1016/j.jocs.2022.101587 – volume: 163 start-page: 105421 year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0010 article-title: Safety risk perception and control of water inrush during tunnel excavation in karst areas: An improved uncertain information fusion method publication-title: Automat Constr doi: 10.1016/j.autcon.2024.105421 – volume: 300 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0085 article-title: Building information modelling-enabled multi-objective optimization for energy consumption parametric analysis in green buildings design using hybrid machine learning algorithms publication-title: Energ Build. doi: 10.1016/j.enbuild.2023.113665 – volume: 23 start-page: 18 year: 2020 ident: 10.1016/j.autcon.2024.105516_bb0210 article-title: Explainable AI: a review of machine learning interpretability methods publication-title: Entropy doi: 10.3390/e23010018 – volume: 149 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0380 article-title: Predictive modeling of loader's working resistance measurement based on multi-sourced parameter data publication-title: Autom. Constr. doi: 10.1016/j.autcon.2023.104805 – year: 2024 ident: 10.1016/j.autcon.2024.105516_bb0275 article-title: Evaluating Media Knowledge Capabilities of Intelligent Search Dialogue Systems: A Case Study of ChatGPT and New Bing publication-title: J Knowl Econ doi: 10.1007/s13132-024-01755-w – volume: 140 year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0300 article-title: Dynamic and explainable deep learning-based risk prediction on adjacent building induced by deep excavation publication-title: Tunn. Undergr. Space Technol. doi: 10.1016/j.tust.2023.105243 – volume: 7 start-page: 514 issue: 4 year: 2022 ident: 10.1016/j.autcon.2024.105516_bb0030 article-title: An improved artificial bee colony-random forest (IABC-RF) model for predicting the tunnel deformation due to an adjacent foundation pit excavation publication-title: Underground Space doi: 10.1016/j.undsp.2021.11.004 – year: 2023 ident: 10.1016/j.autcon.2024.105516_bb0260 article-title: Evaluating Digital Health Services Quality via Social Media publication-title: Ieee T Eng Manage |
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| Title | Predicting existing tunnel deformation from adjacent foundation pit construction using hybrid machine learning |
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