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Type: Journal article
Title: State of the Art of Artificial Neural Networks in Geotechnical Engineering
Author: Shahin, M.
Jaksa, M.
Maier, H.
Citation: Electronic Journal of Geotechnical Engineering, 2008; online:www1-www26
Publisher: Electronic Journal of Geotechnical Engineering
Issue Date: 2008
ISSN: 1089-3032
Statement of
Mohamed A. Shahin, Mark B. Jaksa, Holger R. Maier
Abstract: Over the last few years, artificial neural networks (ANNs) have been used successfully for modeling almost all aspects of geotechnical engineering problems. Whilst ANNs provide a great deal of promise, they suffer from a number of shortcomings such as knowledge extraction, extrapolation and uncertainty. This paper presents a state-of-the-art examination of ANNs in geotechnical engineering and provides insights into the modeling issues of ANNs. The paper also discusses current research directions of ANNs that need further attention in the future.
Keywords: artificial neural networks
artificial intelligence
geotechnical engineering.
Description: © 2008 ejge
Appears in Collections:Aurora harvest
Civil and Environmental Engineering publications
Environment Institute publications

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