Linear genetic programming for prediction of circular pile scour
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- @Article{Guven2009985,
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author = "Aytac Guven and H. Md. Azamathulla and N. A. Zakaria",
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title = "Linear genetic programming for prediction of circular
pile scour",
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journal = "Ocean Engineering",
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volume = "36",
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number = "12-13",
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pages = "985--991",
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year = "2009",
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ISSN = "0029-8018",
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DOI = "doi:10.1016/j.oceaneng.2009.05.010",
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URL = "http://www.sciencedirect.com/science/article/B6V4F-4WCTX10-3/2/805df81deb25d8c99465f876a03fc1e5",
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keywords = "genetic algorithms, genetic programming, Scour,
Neuro-fuzzy, Circular pile, Regression",
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abstract = "Genetic programming (GP) has nowadays attracted the
attention of researchers in the prediction of hydraulic
data. This study presents linear genetic programming
(LGP), which is an extension to GP, as an alternative
tool in the prediction of scour depth around a circular
pile due to waves in medium dense silt and sand bed.
Field measurements were used to develop LGP models. The
proposed LGP models were compared with adaptive
neuro-fuzzy inference system (ANFIS) model results. The
predictions of LGP models were observed to be in good
agreement with measured data, and quite better than
ANFIS and regression-based equation of scour depth at
circular piles. The results were tabulated in terms of
statistical error measures and illustrated via scatter
plots.",
- }
Genetic Programming entries for
Aytac Guven
Hazi Mohammad Azamathulla
Nor Azazi Zakaria
Citations