人工智能在岩巷工程中的应用:地点与方式综述

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Expert Systems Pub Date : 2025-05-23 DOI:10.1111/exsy.70080
Xiaojie Yu, Ben-Guo He, Xu Xu, Yicong Zhou, Miguel A. Diaz, Junxin Chen, David Camacho
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引用次数: 0

摘要

岩石隧道工程在现代基础设施建设中起着至关重要的作用。人工智能(AI)的发展能够推动RTE的变革进步。本文对人工智能在RTE中的应用进行了深入的分析。通过对现有文献的全面研究,我们探讨了人工智能技术如何彻底改变RTE的各个方面,包括施工方法、岩石参数估计、施工期间的灾害管理和隧道运营。此外,我们还深入研究了各种人工智能算法与相关开放数据集之间的协同作用。本工作还概述了人工智能在RTE中应用的未来研究方向,旨在激发这一新兴领域的进一步发展。总之,本综述强调了人工智能对隧道施工的积极影响,强调了人工智能在隧道工程各个阶段提高效率、准确性和安全标准的能力。人工智能与RTE的融合为推进该领域并确保未来隧道基础设施的成功和可持续性带来了巨大的希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Artificial Intelligence in Rock Tunnel Engineering: A Survey on Where and How

Rock tunnel engineering (RTE) plays a crucial role in modern infrastructure development. The development of artificial intelligence (AI) is able to drive transformative advances in RTE. This review provides an in-depth analysis of the AI application in RTE. Through a comprehensive examination of existing literature, we explore how AI technologies have revolutionised various aspects of RTE, including construction methodology, rock parameter estimation, hazard disaster management during construction, and tunnel operation. In addition, we provide an in-depth study of the synergies between various AI algorithms and related open datasets. This work also outlines promising future research directions for the AI application in RTE, aiming to inspire further advancements in this emerging field. In conclusion, this review underscores the positive influence of AI on RTE, emphasising its capacity to elevate efficiency, accuracy, and safety standards throughout various phases of tunnel projects. The convergence of AI with RTE holds immense promise for advancing the field and ensuring the success and sustainability of future tunnel infrastructure endeavours.

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来源期刊
Expert Systems
Expert Systems 工程技术-计算机:理论方法
CiteScore
7.40
自引率
6.10%
发文量
266
审稿时长
24 months
期刊介绍: Expert Systems: The Journal of Knowledge Engineering publishes papers dealing with all aspects of knowledge engineering, including individual methods and techniques in knowledge acquisition and representation, and their application in the construction of systems – including expert systems – based thereon. Detailed scientific evaluation is an essential part of any paper. As well as traditional application areas, such as Software and Requirements Engineering, Human-Computer Interaction, and Artificial Intelligence, we are aiming at the new and growing markets for these technologies, such as Business, Economy, Market Research, and Medical and Health Care. The shift towards this new focus will be marked by a series of special issues covering hot and emergent topics.
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