Artificial Intelligence Applications in Geotechnical Engineering   David Geoffrey Toll Geotechnical Systems Group, School of Engineering, University of Durham, Durham, DH1 3LE, UK e-mail Dr Toll
			INVITED PAPER

Abstract

The paper reviews artificial intelligence (AI) systems that have been developed for geotechnical applications. It covers knowledge-based ('expert') systems and neural network approaches. A significant number of systems have been developed for site characterisation, classification of soils and rocks, foundations, earth retaining structures, slopes, tunnels and underground openings, mining, liquefaction, ground improvement, geotextiles, ground water/dams, roads and earthworks. It is suggested that AI systems should be developed as support tools, rather than attempting to replace human expertise. It is also recognised that AI techniques are good for some aspects of solving engineering problems, but that other approaches are still valid for many applications. Therefore, the way forward will be the development of hybrid systems which mix different artificial intelligence techniques and conventional programming.

KEYWORDS: knowledge-based systems, expert systems, neural network systems, site characterisation, soil classification, foundations, earth retaining structures, slopes, tunnels, underground openings, mining, liquefaction, ground improvement, geotextiles, ground water, dams, earthworks

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