Genetic Programming to Predict Spillway Scour
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gp-bibliography.bib Revision:1.8098
- @Article{Deo:2008:IJTS,
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author = "Omkar Deo and V. Jothiprakash and M. C. Deo",
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title = "Genetic Programming to Predict Spillway Scour",
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journal = "International Journal of Tomography \& Statistics",
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year = "2008",
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volume = "8",
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number = "W08",
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pages = "32--45",
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month = "Winter",
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keywords = "genetic algorithms, genetic programming, neural
networks, scour predictions spillway scour, skijump
bucket",
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ISSN = "0972-9976",
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URL = "http://www.ceser.in/ceserp/index.php/ijts/article/view/110",
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size = "14 pages",
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abstract = "Investigators in the past had noticed that application
of a soft computing tool like artificial neural
networks (ANN) in place of traditional statistics based
data mining techniques produce more attractive results
in hydrologic as well as hydraulic predictions. Mostly
these works pertained to applications of ANN. Recently
another tool of soft computing namely genetic
programming (GP) has caught attention of researchers in
civil engineering computing. This paper examines the
usefulness of the GP based approach to predict the
depth and geometry of the scour hole produced
downstream of a common type of spillway, namely, the
ski-jump bucket. Hydraulic model measurements were used
to develop the GP models. The GP based estimations were
found to be equally, and possibly more, accurate than
the ANN based ones,especially when the underlying
cause-effect relationship became more uncertain to
model.",
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notes = "Discipulus.
Datta Meghe College of Engineering, Airoli, Navi
Mumbai, 400708, India",
- }
Genetic Programming entries for
Omkar Deo
V Jothiprakash
M C Deo
Citations