Reinforcement learning-based optimizer to improve the steering of shield tunneling machine-Reference-Cited by-同舟云学术

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Reinforcement learning-based optimizer to improve the steering of shield tunneling machine

Published:2023-12-10 Issue: Volume: Page:
ISSN:1861-1125
Container-title:Acta Geotechnica
language:en
Short-container-title:Acta Geotech.

Author:

Elbaz Khalid^ORCID,Shen Shui-Long^ORCID,Zhou Annan^ORCID,Yoo Chungsik

Funder

Pearl River Talent Recruitment Program

), Guangdong Province and the Research Funding of Shantou University for New Faculty Member

Research Fund for International Scientists of National Natural Science Fund of China

Guangdong Province and the Scientific Research Initiation Grant of Shantou University for New Faculty Member

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Geotechnical Engineering and Engineering Geology

Link

https://link.springer.com/content/pdf/10.1007/s11440-023-02136-4.pdf

Reference62 articles.

1. Ates U, Bilgin N, Copur H (2014) Estimating torque, thrust and other design parameters of different type TBMs with some criticism to TBMs used in Turkish tunneling projects. Tunn Undergr Space Technol 40:46–63. https://doi.org/10.1016/j.tust.2013.09.004

2. Chen RP, Zhang P, Kang X, Zhong ZQ, Liu Y, Wu HN (2019) Prediction of maximum surface settlement caused by EPB shield tunneling with ANN methods. Soils Found 59(2):284–295. https://doi.org/10.1016/j.sandf.2018.11.005

3. Conejo AJ, Plazas MA, Espinola R, Molina AB (2005) Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Trans Power Syst 20(2):1035–1042

4. Dai SY, Niu DX, Han Y (2018) Forecasting of power grid investment in china based on support vector machine optimized by differential evolution algorithm and grey wolf optimization algorithm. Appl Sci 8:636. https://doi.org/10.3390/app8040636

5. Delgado JMD, Oyedele L (2022) Robotics in construction: a critical review of the reinforcement learning and imitation learning paradigms. Adv Eng Inform 54:101787

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