Intelligent Empowerment of Geotechnical Engineering: Big Data, AI and Optimization
A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geoheritage, Geoparks and Geotourism".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 19
Special Issue Editors
Interests: intelligent monitoring and real-time early warning; geotechnical analysis driven by artificial intelligence and big data; BIM and digital twin technology; intelligent reconnaissance and remote sensing technology; machine learning; intelligent algorithm optimization
Special Issues, Collections and Topics in MDPI journals
Interests: underground structural engineering; soil dynamics; machine learning; geotechnical engineering
Special Issues, Collections and Topics in MDPI journals
Interests: energy underground engineering
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the application of big data analysis technology for processing large-scale geotechnical engineering datasets, establishing intelligent monitoring and early warning systems to facilitate real-time safety management and control in engineering projects. It also investigates the utilization of artificial intelligence, deep learning, and intelligent optimization algorithms in geotechnical parameter inversion, disaster prediction, and engineering design. Additionally, this Special Issue explores the innovative application of intelligent reconnaissance and remote sensing technologies, such as drones, LiDAR, and InSAR, to enhance the precision and efficiency of geological exploration. By integrating these cutting-edge technologies, the Special Issue aims to provide theoretical frameworks, technical case studies, and future directions for both academic and engineering communities, addressing the gaps in systematic, practical, and interdisciplinary integration within existing research, thereby advancing the collaborative development of informatization and intelligence in geotechnical engineering. In particular, the topics of interest include, but are not limited to, the following aspects:
- Big data analysis and mining technology of geotechnical engineering;
- Research on intelligent monitoring systems and real-time early warning methods;
- Application of artificial intelligence and machine learning in geotechnical engineering;
- Application of deep learning algorithms in the identification and prediction of geotechnical parameters;
- Application of intelligent optimization algorithms in geotechnical engineering design;
- Intelligent reconnaissance technology and new methods of remote sensing monitoring;
- Multi-source data fusion and 3D geological modeling technology;
- Research on intelligent standard systems and the specification of geotechnical engineering.
Dr. Jiangbo Xu
Dr. Yi Shan
Prof. Dr. Yu Cong
Dr. Shuaifeng Wang
Guest Editors
Manuscript Submission Information
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Keywords
- geotechnical information and intelligence
- big data analysis
- intelligent monitoring and early warning
- artificial intelligence
- machine learning
- deep learning
- intelligent algorithms
- intelligent reconnaissance
- remote sensing technology
- digital twin
- three-dimensional geological modeling
- data fusion
- parameter inversion
- disaster prediction
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