A review of Genetic Programming and Artificial Neural Network applications in pile foundations

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Fatehnia2018,

• author = "Milad Fatehnia and Gholamreza Amirinia",
• title = "A review of Genetic Programming and Artificial Neural Network applications in pile foundations",
• journal = "International Journal of Geo-Engineering",
• year = "2018",
• month = dec,
• volume = "9",
• number = "2",
• keywords = "genetic algorithms, genetic programming, Pile foundation, Artificial Intelligence, AI, Artificial Neural Network, ANN",
• ISSN = "2198-2783",
• DOI = "doi:10.1186/s40703-017-0067-6",
• size = "20 pages",
• abstract = "Uncertainty in the behaviour of geotechnical materials (e.g. soil and rock) is the result of imprecise physical processes associated with their formation. This uncertainty provides complexity in modelling the behaviour of such materials. The same condition is applied to the behavior of the structural elements dealing with them. In this regard, pile foundations, as the structural elements used to transfer superstructure loads deep into the ground, are subjected to these material uncertainties and modeling complexity. Artificial Intelligence (AI) has demonstrated superior predictive ability compared to traditional methods in modelling the complex behaviour of materials. This ability has made AI a popular and particularly amenable option in geotechnical engineering applications. Genetic Programming (GP) and Artificial Neural Network (ANN) are two of the most common examples of AI techniques. This paper provides a review of GP and ANN applications in estimation of the pile foundations bearing capacity.",

}

Genetic Programming entries for Milad Fatehnia Gholamreza Amirinia

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