Machine learning and Big Data in deep underground engineering
Asoke Nandi, 张茹 , 赵涛, Tao Lei
发布时间：2025-02-28
关键词：Machine learning and Big Data in deep underground engineering
摘要：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 Prof. Asoke Nandi (Brunel University of London, UK), Prof. Ru Zhang (Sichuan University, China), Prof. Tao Zhao (Chinese Academy of Sciences, China), and Prof. Tao Lei (Shaanx...
阅读全文 PDF 引用Performance evaluation of rock fragmentation prediction based on RF-BOA, AdaBoost-BOA, GBoost-BOA, and ERT-BOA hybrid models
Junjie Zhao, Diyuan Li, Jian Zhou, Danial J. Armaghani, Aohui Zhou
发布时间：2024-04-22
关键词：ayesian optimization, blasting, machine learning, rock fragmentation
摘要：AbstractRock 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 and rock properties. For this reason, optimized by the Bayesian optimization algorithm (BOA), four hybrid machine learning models, including random forest, adaptive boost...
阅读全文 PDF 引用Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree-support vector machine models
Mohammad H. Kadkhodaei, Ebrahim Ghasemi, Jian Zhou, Melika Zahraei
发布时间：2025-03-21
关键词：Evaluation of underground hard rock mine pillar stability using gene expression programming and decision treesupport vector machine models
摘要：AbstractAssessing 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 two practical models to predict pillar stability status. For this purpose, two robust models were developed using a database including 236 case histories from seven und...
阅读全文 PDF 引用Development of an optimization model for a monitoring point in tunnel stress deduction using a machine learning algorithm
Xuyan Tan, Weizhong Chen, Luyu Wang, Wei Ye
发布时间：2024-03-07
关键词：Development of an optimization model for a monitoring point in tunnel stress deduction using machine learning algorithm
摘要：HighlightsScientific guidance for monitoring scheme optimization is provided.The stress distribution of the overall section is characterized using limited numbers of monitoring points.Interdisciplinary application of machine learning helps in solving practical engineering problems.1 INTRODUCTIONAssessments of stress patterns in tunnel engineering are invaluable, as they directly impact the safe...
阅读全文 PDF 引用Laboratory evaluation of a low-cost micro electro-mechanical systems sensor for inclination and acceleration monitoring
低成本微机电系统传感器用于倾斜和加速度监测的实验室评估
Antonis Paganis, Vassiliki N. Georgiannou, Xenofon Lignos, Reina El Dahr
发布时间：2025-03-21