Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Directions
Created by W.Langdon from
gp-bibliography.bib Revision:1.8157
- @InCollection{Shahin:2013:MWGTE,
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author = "Mohamed A. Shahin",
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title = "Artificial Intelligence in Geotechnical Engineering:
Applications, Modeling Aspects, and Future Directions",
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editor = "Xin-She Yang and Amir Hossein Gandomi and
Siamak Talatahari and Amir Hossein Alavi",
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booktitle = "Metaheuristics in Water, Geotechnical and Transport
Engineering",
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publisher = "Elsevier",
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address = "Oxford",
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year = "2013",
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chapter = "8",
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pages = "169--204",
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keywords = "genetic algorithms, genetic programming, Artificial
intelligence, geotechnical engineering, modelling,
artificial neural network, ANN, evolutionary polynomial
regression",
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isbn13 = "978-0-12-398296-4",
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URL = "https://espace.curtin.edu.au/handle/20.500.11937/33251",
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URL = "http://www.sciencedirect.com/science/article/pii/B9780123982964000088",
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DOI = "doi:10.1016/B978-0-12-398296-4.00008-8",
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size = "36 pages",
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abstract = "Over the last decade or so, artificial intelligence
(AI) has proved to provide a high level of competency
in solving many geotechnical engineering problems that
are beyond the computational capability of classical
mathematics and traditional procedures. This chapter
presents a brief overview of three selected AI
techniques and their applications in geotechnical
engineering, discusses some AI modelling aspects that
need further attention, and provides insights into
future directions and research challenges.",
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notes = "Also known as \cite{SHAHIN2013169}",
- }
Genetic Programming entries for
Mohamed Shahin
Citations