Geomechanics and Geoengineering

Machine Learning Methods and Applications in Geoengineering and Geomechanics

The concept of Big Data naturally agrees well with geoengineering and geomechanics, in which the exciting field of sensing techniques is advancing. This understanding would come through the analysis of increasingly large geo-datasets and from computationally intensive simulations. As a result, large-scale, comprehensive, multidirectional and multifield geotechnical investigation and monitoring is becoming a reality. Geo-engineers are faced with the challenge of extracting as much useful information as possible and gaining new insights from these data, simulations, and interplay between the two. This special issue is meant to address these challenges, as a part of the 9th International Symposium for Geotechnical Safety and Risk (ISGSR 2025) to feature the latest research developments and innovations with a focus on Machine Learning methods and applications in geoengineering and geomechanics through advanced algorithms, techniques, and methodology, and adherence to industry best practices and safety standards. 

Keywords: 

Machine Learning 

Deep Learning 

Geoengineering and Geomechanics 

Physics-informed neural network 

Physics-informed data-driven techniques 

Evolution-based methods  

Explanation-based learning  

Visualization of patterns in data 

Learning in integrated architectures 

Multistrategy learning 

Multi-agent learning  

etc.