TC Chair: Zhongqiang Liu
Disseminate knowledge and practice within the TC’s subject area to the membership of the ISSMGE:
TC309 aims to provide a forum for all interested members of ISSMGE to explore the use of machine learning (ML) techniques to solve problems relevant to soil mechanics and geotechnical engineering. To disseminate and develop knowledge and practice within the area of ML in geotechnical engineering, TC309 will deal with the following important technical issues:
The development of accurate, robust and efficient predictive tools based on ML methods, such as Support Vector Machine (SVM), Deep Learning (DL), Reinforcement Learning (RL) and Case-based Reasoning (CBR).
The development of webinars for global training use;
Producing a widely distributed newsletter for general dissemination and communication on ML;
The organization of symposia and workshops with the aim to promote cooperation and exchange of information concerning research and developments in using ML in geotechnical practice;
Advancing the collaboration between ML techniques and complicated geotechnical problems by showing the advantages of popular and more advanced ML methods, and by demonstrating the efficiency of these techniques applied to geotechnical engineering via organizing prediction events.