Intelligent Attitude Control Method for Shield Tunneling Machines Considering a Rectifying Mechanism: A Case Study of the Chengdu Subway-Reference-Cited by-同舟云学术

Intelligent Attitude Control Method for Shield Tunneling Machines Considering a Rectifying Mechanism: A Case Study of the Chengdu Subway

Published:2024-08 Issue:8 Volume:24 Page:
ISSN:1532-3641
Container-title:International Journal of Geomechanics
language:en
Short-container-title:Int. J. Geomech.

Author:

Xiao Haohan¹,Cao Ruilang²,Feng Shangxin³

Affiliation:

1. Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.

2. Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China (corresponding author).

3. School of Architecture and Civil Engineering, Xi’an University of Science and Technology, Xi’an, Shaanxi 710054, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/IJGNAI.GMENG-9026

Reference39 articles.

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2. Al-Maolegi M. and B. Arkok. 2014. “An improved Apriori algorithm for association rules.” Preprint submitted March 16 2014. https://arxiv.org/abs/1403.3948.

3. Feature selection in machine learning: A new perspective

4. Prediction of shield tunneling-induced ground settlement using machine learning techniques

5. A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns

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