{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T12:12:18Z","timestamp":1773663138298,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Project of Hubei Province","award":["2023BAB094"],"award-info":[{"award-number":["2023BAB094"]}]},{"name":"Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System","award":["HBSEES202106"],"award-info":[{"award-number":["HBSEES202106"]}]},{"name":"Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System","award":["HBSEES202309"],"award-info":[{"award-number":["HBSEES202309"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Accurately predicting and controlling the attitude of a shield tunneling machine is critical for quality assurance in shield tunneling projects. Existing prediction methods utilize historical data to construct a machine learning framework to predict future attitude deviations. However, this method is poorly interpretable and lacks practical engineering guidance. Considering the shortcomings of this prediction method, this study suggests an innovative deep learning method called causal graph convolutional network (C-GCN-GRU), and the goal of this project is the improvement of the interpretability of the shield attitude prediction. The causal relationships between key attitude features of the shield machine are recognized and quantified by the PCMCI+ method. The found causal relationships are converted into collocation matrices to be input into a model consisting of GCN and GRU, and combined with multi-head causal attention to better forecast the shield machine attitude. The results trained on a dataset from the Karnaphuli River Tunnel Project in Bangladesh show that the accuracy of the four variables characterizing the shield attitude and position predicted by the C-GCN-GRU model outperforms that of the other four similar models and provides decision support for attitude and position adjustments in shield tunnels.<\/jats:p>","DOI":"10.3390\/a19030224","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T11:13:14Z","timestamp":1773659594000},"page":"224","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Shield Machine Attitude Prediction Method Based on Causal Graph Convolutional Network"],"prefix":"10.3390","volume":"19","author":[{"given":"Liang","family":"Zeng","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China"},{"name":"Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingao","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenning","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xue","family":"Wang","sequence":"additional","affiliation":[{"name":"CCCC Wuhan Zhi Xing International Engineering Consulting Company Ltd., Wuhan 430068, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanshan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China"},{"name":"Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1721","DOI":"10.1007\/s12541-019-00073-5","article-title":"Trajectory Control of Tunnel Boring Machine Based on Adaptive Rectification Trajectory Planning and Multi-Cylinders Coordinated Control","volume":"20","author":"Liu","year":"2019","journal-title":"Int. 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