Journal
OCEAN ENGINEERING
Volume 36, Issue 12-13, Pages 985-991Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2009.05.010
Keywords
Scour; Genetic programming; Neuro-fuzzy; Circular pile; Regression
Funding
- Universiti Sains Malaysia
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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. (C) 2009 Elsevier Ltd. All rights reserved.
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