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dc.contributor.authorShahin, Mohamed
dc.identifier.citationShahin, M. 2015. A review of artificial intelligence applications in shallow foundations. International Journal of Geotechnical Engineering. 9 (1): pp. 49-60.

Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behavior because of 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, including foundations, because it has demonstrated superior predictive ability compared to traditional methods. The main aim of this paper is to review the AI applications in shallow foundations and present the salient features associated with the AI modeling development. The paper also discusses the strengths and limitations of AI techniques compared to other modeling approaches.

dc.publisherJ Ross Publishing Inc/Maney
dc.subjectGenetic programing
dc.subjectArtificial intelligence
dc.subjectNeural networks
dc.subjectShallow foundations
dc.subjectEvolutionary polynomial regression
dc.titleA review of artificial intelligence applications in shallow foundations
dc.typeJournal Article
dcterms.source.titleInternational Journal of Geotechnical Engineering
curtin.departmentDepartment of Civil Engineering
curtin.accessStatusOpen access

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