Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Journal article
Title: Recent advances and future challenges for artificial neural systems in geotechnical engineering applications
Author: Shahin, M.
Jaksa, M.
Maier, H.
Citation: Advances in Artificial Neural Systems, 2009; 2009:1-9
Publisher: Hindawi Publishing
Issue Date: 2009
ISSN: 1687-7594
Statement of
Mohamed A. Shahin, Mark B. Jaksa and Holger R. Maier
Abstract: Artificial neural networks (ANNs) are a form of artificial intelligence that has proved to provide a high level of competency in solving many complex engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. In particular, ANNs have been applied successfully to almost all aspects of geotechnical engineering problems. Despite the increasing number and diversity of ANN applications in geotechnical engineering, the contents of reported applications indicate that the progress in ANN development and procedures is marginal and not moving forward since the mid-1990s. This paper presents a brief overview of ANN applications in geotechnical engineering, briefly provides an overview of the operation of ANN modeling, investigates the current research directions of ANNs in geotechnical engineering, and discusses some ANN modeling issues that need further attention in the future, including model robustness; transparency and knowledge extraction; extrapolation; uncertainty.
Description: Published as Open Access article.
Rights: Copyright © 2009 Mohamed A. Shahin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1155/2009/308239
Appears in Collections:Aurora harvest
Civil and Environmental Engineering publications
Environment Institute publications

Files in This Item:
File Description SizeFormat 
hdl_57783.pdf592.71 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.