Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/40578
Type: Journal article
Title: Artificial neural network applications in geotechnical engineering
Author: Shahin, M.
Jaksa, M.
Maier, H.
Citation: Australian Geomechanics, 2001; 36(1):49-62
Publisher: Australian Geomechanics Society
Issue Date: 2001
ISSN: 0818-9110
Statement of
Responsibility: 
Mohamed A. Shahin, Mark B. Jaksa and Holger R. Maier
Abstract: Over the last few years or so, the use of artificial neural networks (ANNs) has increased in many areas of engineering. In particular, ANNs have been applied to many geotechnical engineering problems and have demonstrated some degree of success. A review of the literature reveals that ANNs have been used successfully in pile capacity prediction, modelling soil behaviour, site characterisation, earth retaining structures, settlement of structures, slope stability, design of tunnels and underground openings, liquefaction, soil permeability and hydraulic conductivity, soil compaction, soil swelling and classification of soils. The objective of this paper is to provide a general view of some ANN applications for solving some types of geotechnical engineering problems. It is not intended to describe the ANNs modelling issues in geotechnical engineering. The paper also does not intend to cover every single application or scientific paper that found in the literature. For brevity, some works are selected to be described in some detail, while others are acknowledged for reference purposes. The paper then discusses the strengths and limitations of ANNs compared with the other modelling approaches.
RMID: 0020073934
Published version: http://www.ecms.adelaide.edu.au/civeng/staff/pdf/AusGeo2001_Shahin.pdf
Appears in Collections:Civil and Environmental Engineering publications
Environment Institute publications

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