State-of-the-art review of some artificial intelligence applications in pile foundations

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@Article{Shahin:2014:GF,

• author = "Mohamed A. Shahin",
• title = "State-of-the-art review of some artificial intelligence applications in pile foundations",
• journal = "Geoscience Frontiers",
• year = "2014",
• keywords = "genetic algorithms, genetic programming, Artificial intelligence, Pile foundations, Artificial neural networks, Evolutionary polynomial regression",
• ISSN = "1674-9871",
• DOI = "doi:10.1016/j.gsf.2014.10.002",
• URL = "http://www.sciencedirect.com/science/article/pii/S1674987114001327",
• abstract = "Geotechnical engineering deals with materials (e.g. soil and rock) that, by their very nature, exhibit varied and uncertain behaviour due to the imprecise physical processes associated with the formation of these materials. Modelling 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 behaviour 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 modelling development of these AI techniques. The paper also discusses the strength and limitations of the selected AI techniques compared to other available modelling approaches.",

}

Genetic Programming entries for Mohamed Shahin

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