Mini symposia/Special sessions

MS36 Artificial Intelligence Based Analysis for Geotechnical Design, Construction and Monitoring

Senior advisor Zhongqiang Liu: Zhongqiang.Liu@ngi.no

Session Chairs:
Dongming Zhang, Associate Professor (member of TC309, i.e., Machine learning and big data, of ISSMGE), Tongji University, Shanghai, China, 09zhang@tongji.edu.cn
Zijun Cao, Professor (member of TC309, i.e., Machine learning and big data, of ISSMGE), Wuhan University, Wuhan, China. zijuncao@whu.edu.cn
Zhongqiang Liu, Senior advisor (Chair of TC309, i.e., Machine learning and big data, of ISSMGE) Norwegian Geotechnical Institute, Oslo, Norway, Zhongqiang.Liu@ngi.no

Abstract of the special session:
This mini-symposium is supported by TC309 (machine learning and big data) of International Society of Soil Mechanics and Geotechnical Engineering.
Artificial intelligence (AI) including machine learning is the scientific study of algorithms and statistical models that allows computers to learn from existing data without being explicitly programmed. In recent years, the application of AI in a wide range of industries has grown rapidly. AI can be very useful in solving problems where deterministic solutions are not available or are excessively expensive in terms of computational cost but for which there is significant observations and data available. Due to the nature of materials, geotechnical engineering deals with more uncertainties than other fields of civil and mechanical engineering. Meanwhile, there is a lot of monitoring and construction data in geotechnical engineering which needs to be taken advantage of by using data analytic methods. Therefore, AI can be a suitable and effective alternative to solve geotechnical engineering problems related to the design, construction and monitoring. The AI based analysis or researches will have to merge the boundary of multi-disciplines including the electronic engineering, geotechnical engineering, management engineering, etc..
By organizing the such a mini-symposium with the support from TC309, the speakers and attendees will certainly benefit from the professional communications and discussions.

ICOSSAR 2021-2022 Secretariat

Tongji University, 1239 Siping Road, Shanghai 200092, China    Email: icossar2021@tongji.edu.cn

© 2021 ICOSSAR 2021-2022   Powered by Weicheng