Two-layer autonomous intelligence dynamic trajectory planning method based on shield-tunnel ring-geology interactions-Reference-Cited by-同舟云学术

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Two-layer autonomous intelligence dynamic trajectory planning method based on shield-tunnel ring-geology interactions

Published:2024-12 Issue: Volume:19 Page:227-250
ISSN:2467-9674
Container-title:Underground Space
language:en
Short-container-title:Underground Space

Author:

Hu Min,Wu Bingjian^ORCID,Wu Huiming,Pei Liefeng

Publisher

Elsevier BV

Reference41 articles.

1. Evaluating time series forecasting models: An empirical study on performance estimation methods;Cerqueira;Machine Learning,2020

2. Shield attitude prediction based on Bayesian-LGBM machine learning;Chen;Information Sciences,2023

3. Robust Locally Weighted Regression and Smoothing Scatterplots;Cleveland;Journal of the American Statistical Association,1979

4. Dynamic prediction for attitude and position of shield machine in tunneling: A hybrid deep learning method considering dual attention;Dai;Advanced Engineering Informatics,2023

5. A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns;Fu;Expert Systems with Applications,2023

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