Applications of Machine Learning in Geomaterials

Collection on "Machine Learning Applications in Geo-materials" focuses on the nexus between machine learning and geotechnical engineering, examining how data-driven methods can improve the comprehension, modelling, and forecasting of the behaviour of geo-materials (such as rock, soil, and other earth materials). The potential for this field to increase accuracy and efficiency in a number of geotechnical engineering domains, including: Soil behaviour prediction , Geotechnical investigation, slope stability and landslide prediction, optimization and design.

The Collection would likely feature case studies, reviews, and original research demonstrating how these machine learning techniques are being applied to real-world problems in the study and use of geo-materials. It would also discuss challenges such as data quality, model interpretability, and the integration of machine learning with traditional geotechnical analysis methods.

This Collection supports and amplifies research related to SDG 9.

Keywords: Geomaterials Analysis; Environmental Materials; Machine Learning; Data-driven technology; Soil