云南高校图书馆联盟文献共享服务平台- Deep Underground Science and Engineering

《Deep Underground Science and Engineering》: 作品数：110被引量：49H指数：3; 导出分析报告; 主办单位：中国矿业大学; 最新期次：2025年1期更多>>; 发文主题：UNDERGROUNDDEEPJOURNALLINESAUTHOR_GUIDE更多>>; 发文领域：天文地球建筑科学交通运输工程矿业工程更多>>; 发文基金：国家自然科学基金中国博士后科学基金俄罗斯基础研究基金国家重点基础研究发展计划更多>>

Author Guidelines: 《Deep Underground Science and Engineering》2025年第1期F0003-F0003,共1页; Deep Underground Science and Engineering (DUSE) is a new international journal (Online ISSN:2770-1328;Print ISSN:2097-0668) launched by China University of Mining and Technology.The Journal is managed by a renowned in...; 关键词：JOURNAL devoted AUSTRALIA

Editorial Board of Deep Underground Science and Engineering: 《Deep Underground Science and Engineering》2025年第1期F0002-F0002,共1页

Machine learning and Big Data in deep underground engineering: 《Deep Underground Science and Engineering》2025年第1期1-2,共2页Asoke K.Nandi Ru Zhang Tao Zhao Tao Lei; This special issue of Deep Underground Science and Engineering(DUSE)showcases pioneering research on the transformative role of machine learning(ML)and Big Data in deep underground engineering.Edited by guest editors ...; 关键词：UNDERGROUND LEARNING operations

Performance evaluation of rock fragmentation prediction based on RF-BOA,AdaBoost-BOA,GBoost-BOA,and ERT-BOA hybrid models: 《Deep Underground Science and Engineering》2025年第1期3-17,共15页Junjie Zhao Diyuan Li Jian Zhou Danial JArmaghani Aohui Zhou; National Natural Science Foundation of China,Grant/Award Number:52374153。; Rock fragmentation is an important indicator for assessing the quality of blasting operations.However,accurate prediction of rock fragmentation after blasting is challenging due to the complicated blasting parameters ...; 关键词：Bayesian optimization BLASTING machine learning rock fragmentation

Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree-support vector machine models: 《Deep Underground Science and Engineering》2025年第1期18-34,共17页Mohammad H.Kadkhodaei Ebrahim Ghasemi Jian Zhou Melika Zahraei; Assessing the stability of pillars in underground mines(especially in deep underground mines)is a critical concern during both the design and the operational phases of a project.This study mainly focuses on developing...; 关键词：decision tree-support vector machine(DT-SVM) gene expression programming(GEP) hard rock pillar stability underground mining

Development of an optimization model for a monitoring point in tunnel stress deduction using a machine learning algorithm: 《Deep Underground Science and Engineering》2025年第1期35-45,共11页Xuyan Tan Weizhong Chen Luyu Wang Wei Ye; Key project in Hubei Province,Grant/Award Number:2023BCB048;National Key R&D Program of China,Grant/Award Number:2021YFC3100805;National Natural Science Foundation of China,Grant/Award Numbers:42293355,51991392;Project for Research Assistant of Chinese Academy of Sciences。; Monitoring of the mechanical behavior of underwater shield tunnels is vital for ensuring their long-term structural stability.Typically determined by empirical or semi-empirical methods,the limited number of monitorin...; 关键词：machine learning MONITORING OPTIMIZATION simulation TUNNEL

Laboratory evaluation of a low-cost micro electro-mechanical systems sensor for inclination and acceleration monitoring: 《Deep Underground Science and Engineering》2025年第1期46-54,共9页Antonis Paganis Vassiliki NGeorgiannou Xenofon Lignos Reina El Dahr; Research Committee,National Technical University of Athens。; In this study,the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented.Αmicro electro-mechanical systems,micro electro mechanical systems,sensor was housed i...; 关键词：field monitoring Kalman filter laboratory evaluation micro electro mechanical systems(MEMS) monitoring node shaking table

Grouped machine learning methods for predicting rock mass parameters in a tunnel boring machine-driven tunnel based on fuzzy C-means clustering: 《Deep Underground Science and Engineering》2025年第1期55-71,共17页Ruirui Wang Yaodong Ni Lingli Zhang Boyang Gao; Natural Science Foundation of Shandong Province,Grant/Award Number:ZR202103010903;Doctoral Fund of Shandong Jianzhu University,Grant/Award Number:X21101Z。; To guarantee safe and efficient tunneling of a tunnel boring machine(TBM),rapid and accurate judgment of the rock mass condition is essential.Based on fuzzy C-means clustering,this paper proposes a grouped machine lea...; 关键词：fuzzy C-means clustering machine learning rock mass parameter tunnel boring machine

ALSTNet:Autoencoder fused long-and short-term time-series network for the prediction of tunnel structure: 《Deep Underground Science and Engineering》2025年第1期72-82,共11页Bowen Du Haohan Liang Yuhang Wang Junchen Ye Xuyan Tan Weizhong Chen; National Key Research and Development Program of China,Grant/Award Number:2018YFB2101003;National Natural Science Foundation of China,Grant/Award Numbers:51991395,U1806226,51778033,51822802,71901011,U1811463,51991391;Science and Technology Major Project of Beijing,Grant/Award Number:Z191100002519012。; It is crucial to predict future mechanical behaviors for the prevention of structural disasters.Especially for underground construction,the structural mechanical behaviors are affected by multiple internal and externa...; 关键词：autoencoder deep learning structural health monitoring time-series prediction

Opportunities and challenges for gas coproduction from coal measure gas reservoirs with coal-shale-tight sandstone layers:A review: 《Deep Underground Science and Engineering》2025年第1期83-104,共22页Wei Liang Jianguo Wang Chunfai Leung Sianghuat Goh Shuxun Sang; China Scholarship Council,Grant/Award Number:202206420091;National Natural Science Foundation of China,Grant/Award Numbers:42030810,51674246。; The extraction of coal measure gas has been shifted toward thin gas reservoirs due to the depletion of medium-thick gas reservoirs.The coproduction of coalbed gas,shale gas,and tight sandstone gas(called a multisuperp...; 关键词：gas coproduction interlayer interference multisuperposed gas system numerical simulation model pore structure

《Deep Underground Science and Engineering》