Robust prediction of thrust for tunnel boring machines with adaptive heavy-tailed error distribution-Reference-Cited by-同舟云学术

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Robust prediction of thrust for tunnel boring machines with adaptive heavy-tailed error distribution

Published:2024-10 Issue: Volume:62 Page:102619
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Li Shuang,Zhang Qian^ORCID,Liu Shanglin,Ma Minghui

Publisher

Elsevier BV

Reference52 articles.

1. Physics-based machine learning method and the application to energy consumption prediction in tunneling construction;Zhou;Adv. Eng. Inf.,2022

2. A hybrid comprehensive performance evaluation approach of cutter holder for tunnel boring machine;Yang;Adv. Eng. Inf.,2022

3. A LightGBM-based strategy to predict tunnel rockmass class from TBM construction data for building control;Li;Adv. Eng. Inf.,2023

4. X. Li et al., A data driven real-time perception method of rock condition in TBM construction, Can. Geotech. J. 0(ja), doi: 10.1139/cgj-2023-0168.

5. Data-driven multi-step robust prediction of TBM attitude using a hybrid deep learning approach;Wang;Adv. Eng. Inf.,2023

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