Ant clustering for the CPT and DMT-based soil profile generation

The paper presents the automated method of the soil profile generation using the unsupervised learning. This method can be used as the main source of knowledge for the future soil classification module, which would identify geotechnical layers without the interaction with the user. The method uses the ant clustering, which groups measurements from the Dilatometer of Marchetti Test and Cone Penetration Test. The test site, algorithm and its application to the generation of soil profiles in the Warsaw University of Life Sciences campus are described. Results are discussed to provide a more general insight into application of intelligent algorithms into the geotechnical data analysis.