邻近盾构施工对既有隧道沉降的影响:现场监测与智能预测
Author:
Publisher
Zhejiang University Press
Subject
General Engineering
Link
https://link.springer.com/content/pdf/10.1631/jzus.A2200573.pdf
Reference46 articles.
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2. Chen RP, Zhang P, Wu HN, et al., 2019b. Prediction of shield tunneling-induced ground settlement using machine learning techniques. Frontiers of Structural and Civil Engineering, 13(6):1363–1378. https://doi.org/10.1007/s11709-019-0561-3
3. Chen RP, Song X, Meng FY, et al., 2022. Analytical approach to predict tunneling-induced subsurface settlement in sand considering soil arching effect. Computers and Geotechnics, 141:104492. https://doi.org/10.1016/j.compgeo.2021.104492
4. Deng HS, Fu HL, Yue S, et al., 2022. Ground loss model for analyzing shield tunneling-induced surface settlement along curve sections. Tunnelling and Underground Space Technology, 119:104250. https://doi.org/10.1016/j.tust.2021.104250
5. Ding Y, Ye XW, Guo Y, 2023a. Data set from wind, temperature, humidity and cable acceleration monitoring of the Jiashao bridge. Journal of Civil Structural Health Monitoring, 13(2–3):579–589. https://doi.org/10.1007/s13349-022-00662-5
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