Automated position control of tunnel boring machine during excavation using deep reinforcement learning considering spatial-temporal dynamics-Reference-Cited by-同舟云学术

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Automated position control of tunnel boring machine during excavation using deep reinforcement learning considering spatial-temporal dynamics

Published:2024-09 Issue: Volume: Page:112234
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Lin Penghui,Ji Ankang,Zhou Yunxiang,Zhang Limao^ORCID,Tiong Robert L.K.

Publisher

Elsevier BV

Reference61 articles.

1. Factors in the development of urban underground space surrounding metro stations: A case study of Osaka, Japan;Peng;Tunnelling and Underground Space Technology,2019

2. Surface settlement control in the excavation of a shallow intersection between a double-arched tunnel and a connection tunnel;Yang;International Journal of Geomechanics,2021

3. Construction and maintenance of urban underground infrastructure with digital technologies;Wang;Autom Constr,2022

4. Global sensitivity analysis of influential parameters for excavation stability of metro tunnel;Liu;Autom Constr,2020

5. Prediction of tunnel boring machine operating parameters using various machine learning algorithms;Xu;Tunnelling and Underground Space Technology,2021

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