An accurate and adaptative cutterhead torque prediction method for shield tunneling machines via adaptative residual long-short term memory network-Reference-Cited by-同舟云学术

An accurate and adaptative cutterhead torque prediction method for shield tunneling machines via adaptative residual long-short term memory network

Published:2022-02 Issue: Volume:165 Page:108312
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Jin Yanrui,Qin Chengjin,Tao Jianfeng,Liu Chengliang

Funder

Science and Technology Commission of Shanghai Municipality

State Key Laboratory of Mechanical System and Vibration

National Key Research and Development Program of China

National Key Research and Development Program of China Stem Cell and Translational Research

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference49 articles.

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3. C. Qin G. Shi J. Tao H. Yu Y. Jin J. Lei C. Liu Precise cutterhead torque prediction for shield tunneling machines using a novel hybrid deep neural network Mechanical Systems and Signal Processing 151 2021 107386.

4. A VMD-EWT-LSTM-based multi-step prediction approach for shield tunneling machine cutterhead torque;Shi;Knowledge-Based Systems,2021

5. A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data;Zhao;IEEE Access,2019

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