Special Issue Call for Papers
Machine Learning and Big Data in Deep Underground Engineering
《深地科学(英文)》特刊“机器学习与大数据在深部地下工程中的应用”期待您的投稿！
1
Introduction
Deep underground science and engineering face significant challenges in understanding and predicting the complex behaviour of geomaterials in a variety of geological environments. Despite the availability of various mathematical and physical methods, accurately capturing the nonlinear mechanical response of deep geomaterials remains a formidable task.
In recent years, machine learning (ML) has emerged as a promising sub-branch of artificial intelligence (AI) for acquiring knowledge and making models from training data and making predictions without explicit programming. With the proliferation of Big Data generated by various geotechnical projects, ML and data mining have the potential for offering unprecedented opportunities for knowledge discovery and data-driven decision making in deep underground engineering.
This Special Issue aims to bring together the latest research and advances in ML and Big Data applications to deep underground science and engineering. By disseminating cutting-edge results and promoting interdisciplinary collaborations, we aim to enhance the impact of AI and data mining in geotechnics and facilitate the exchange of knowledge, expertise, and experience. Furthermore, this issue seeks to explore the trends, challenges, and opportunities in the adoption of ML and Big Data in geotechnical research and industrial workflows, and to promote a promising future of intelligent geotechnics.
We sincerely invite you and your team to submit papers
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topics
The Special Issue welcomes original research papers and review articles reporting innovative applications of ML and Big Data to deep underground engineering. The focal themes include, but are not limited to,
The design, construction, and maintenance of tunnels and underground infrastructures；
TBM tunnelling aided by ML and data-driven approaches；
Innovative monitoring technologies and AI for mining；
Image analysis and ML for geomechanics；
Deep learning and computer vision for characterizing geotechnical processes；
ML and Big Data for disaster prevention and mitigation；
Emerging technologies in urban systems；
Repair and reinforcement of aging tunnels and underground structures；
Data quality assurance and pre-processing in geoscience.
SI keywords: Artificial Intelligence; Data Mining; Data-driven Decision Making; Deep Excavation; Disaster Mitigation
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Important Date
Submission deadline: 31/01/2024
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Submission Guidelines
The article in this SI may be Original Research Paper, Review, Commentary, Correspondence, or Short Communication.
Please submit your manuscript via the online editorial system of DUSE journal below：
https://mc.manuscriptcentral.com/duse
Please contact the Guest Editors or DUSE editorial office (duse@cumt.edu.cn) for any question or query on this SI
DUSE Journal website:
https://onlinelibrary.wiley.com/journal/27701328
During submission, please select "Machine Learning and Big Data in Deep Underground Engineering" at the Special Issue custom question found in Step 1 (Type, Title, & Abstract) of the author submission page to ensure that your submission is considered for the appropriate special issue.
No Article Process Cost (APC) is applied during 2022-2024
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Guest Editors
Prof. Asoke K. Nandi
Brunel University London, UK
Email: asoke.nandi@brunel.ac.uk
Prof. Ru Zhang
Sichuan University, China
Email: zhangru@scu.edu.cn
Dr. Tao Zhao
Brunel University London, UK
Email: tao.zhao@brunel.ac.uk
Prof. Tao Lei
Shaanxi University of Science and Technology, China
Email: leitao@sust.edu.cn
《 深地科学（英文）》欢迎广大学者积极投稿！
《深地科学（英文）》（Deep Underground Science and Engineering）是由中华人民共和国教育部主管，中国矿业大学主办的“深地科学”领域的第一本国际期刊，成功入选 ”中国科技期刊卓越行动计划高起点新刊项目”。主编是中国工程院院士谢和平教授。与国际知名出版商 Wiley 合作，进行全球出版发行。
《深地科学（英文）》以创办高起点国际期刊，构建世界领先的专注于深地科学前沿研究的学术交流主流平台，建设成为世界一流科技期刊为目标，为打造“深地科学”联盟奠定基础，致力于引领“深地科学”研究，有望成为刊发该领域重要研究的战略前沿阵地。
《深地科学（英文）》欢迎广大学者积极投稿，共同努力将本刊建成世界一流的高水平期刊。出版费由期刊资助，您无需支付任何费用。
Deep Underground Science and Engineering (DUSE), as a new international and fully open access journal ,aims to build a mainstream academic exchange platform focusing on forefront research, and to become a world-class scientific and technological journal.
The DUSE publishes the papers on important theoretical breakthroughs, valuable reviews of state-of-the-art, or discussions on the latest innovative, prospective, and leading achievements in the field of Deep Underground Science and Engineering. Papers on core fundamental research, revolutionary technology development, major engineering construction, special environmental effects, and other important related studies are also solicited.
DUSE intends to present the latest findings to help keep researchers worldwide abreast of the latest developments in the field and it welcomes papers with an emphasis on innovation, leading achievements, core research, theoretical breakthroughs and valuable reviews focusing on, but not limited to, the following topics:
刊登范围：
地质资源勘探与开采
Exploration and extraction of geo-resources
能源物质地下储存和提取
Energy extraction and storage
地下空间基础设施
Underground infrastructures
地质环境和废弃物地质处置
Geo-environments and waste geological disposal
深地空间科学实验
Research and testing space in deep underground
地下空间或地下工程规划，设计和施工技术
Plan， design and construction technology for underground space and engineering
文章类型：Research Article、Review Article、Short Communication、Commentary、Correspondence、Editorial.
图文编辑 | 侯庆萍
审核 | 王继红
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