Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network-Reference-Cited by-同舟云学术

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Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network

Published:2021-05 Issue: Volume:125 Page:103647
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Liu Zaobao,Li Long,Fang Xingli,Qi Wenbiao,Shen Jimei,Zhou Hongyuan,Zhang Yulong

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference50 articles.

1. Prediction of geological conditions for a tunnel boring machine using big operational data;Zhang;Autom. Constr.,2019

2. An anomalous event detection and tracking method for a tunnel look-ahead ground prediction system;Wei;Autom. Constr.,2018

3. Web-based visualisation for look-ahead ground imaging in tunnel boring machines;Wei;Autom. Constr.,2019

4. A lithology identification method for continental shale oil reservoir based on BP neural network;Luo;J. Geophys. Eng.,2018

5. Analysis of disc cutter damage and consumption of TBM1 section on water conveyance tunnel at Lanzhou water source construction engineering;Yang;Tunn. Undergr. Space Technol.,2019

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