Time-series prediction of shield movement performance during tunneling based on hybrid model-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Time-series prediction of shield movement performance during tunneling based on hybrid model

Published:2022-01 Issue: Volume:119 Page:104245
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Lin Song-Shun,Zhang Ning,Zhou Annan,Shen Shui-Long

Funder

Shantou University

Guangdong Provincial Pearl River Talents Program

Government of Guangdong Province

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference53 articles.

1. Advanced finite element modeling of excavation and advancement processes in mechanized tunneling;Alsahly;Adv. Eng. Softw.,2016

2. Assessment of the factors affecting the advance rate of the Tunnel Gerede, the longest and one of the most problematic water transmission tunnels of Turkey;Alp;Tunn. Undergr. Space Technol.,2019

3. An optimized model using LSTM network for demand forecasting;Abbasimehr;Comput. Ind. Eng.,2020

4. Safe excavation of large section tunnels with Earth Pressure Balance Tunnel Boring Machine in gassy rock masses: the Sparvo tunnel case study;Bandini;Tunn. Undergr. Space Technol.,2017

5. An improved method to calculate the vertical earth pressure for deep shield tunnel in Shanghai soil layers;Chen;Tunn. Undergr. Space Technol.,2018

Cited by 57 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Two-layer autonomous intelligence dynamic trajectory planning method based on shield-tunnel ring-geology interactions;Underground Space;2024-12

2. Smart Techniques Promoting Sustainability in Construction Engineering and Management;Engineering;2024-09

3. Adaptive mutation sparrow search algorithm-Elman-AdaBoost model for predicting the deformation of subway tunnels;Underground Space;2024-08

4. A spatiotemporal deep learning method for excavation-induced wall deflections;J ROCK MECH GEOTECH;2024

5. A spatiotemporal deep learning method for excavation-induced wall deflections;Journal of Rock Mechanics and Geotechnical Engineering;2024-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3