Attention-based LSTM predictive model for the attitude and position of shield machine in tunneling

Attention-based LSTM predictive model for the attitude and position of shield machine in tunneling

Shield machine may deviate from its design axis during excavation due to the uncertainty of geological environment and the complexity of operation. This study therefore introduced a framework to predict the attitude and position of shield machine by combining long short-term memory (LSTM) model with...

Full description

Bibliographic Details
Main Authors: Qing Kang, Elton J. Chen, Zhong-Chao Li, Han-Bin Luo, Yong Liu
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-12-01
Series:Underground Space
Subjects:
LSTM
Shield machine
Attitude and position prediction
Attention mechanism
Tunnel excavation
Online Access:http://www.sciencedirect.com/science/article/pii/S2467967423000880

Similar Items

Similar Items