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dc.contributor.authorShahin, Mohamed
dc.date.accessioned2017-01-30T15:25:42Z
dc.date.available2017-01-30T15:25:42Z
dc.date.created2016-02-18T19:30:20Z
dc.date.issued2016
dc.identifier.citationShahin, M. 2016. State-of-the-art review of some artificial intelligence applications in pile foundations. Geoscience Frontiers. 7 (1): pp. 33-44.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/46200
dc.identifier.doi10.1016/j.gsf.2014.10.002
dc.description.abstract

© 2014, China University of Geosciences (Beijing) and Peking University. Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behavior due to the imprecise physical processes associated with the formation of these materials. Modeling the behavior of such materials in geotechnical engineering applications is complex and sometimes beyond the ability of most traditional forms of physically-based engineering methods. Artificial intelligence (AI) is becoming more popular and particularly amenable to modeling the complex behavior of most geotechnical engineering applications because it has demonstrated superior predictive ability compared to traditional methods. This paper provides state-of-the-art review of some selected AI techniques and their applications in pile foundations, and presents the salient features associated with the modeling development of these AI techniques. The paper also discusses the strength and limitations of the selected AI techniques compared to other available modeling approaches.

dc.titleState-of-the-art review of some artificial intelligence applications in pile foundations
dc.typeJournal Article
dcterms.source.volume7
dcterms.source.number1
dcterms.source.startPage33
dcterms.source.endPage44
dcterms.source.issn1674-9871
dcterms.source.titleGeoscience Frontiers
curtin.note

This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by-nc-nd/3.0/

curtin.departmentDepartment of Civil Engineering
curtin.accessStatusOpen access


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