Genetic programming for the prediction of berm breakwaters recession
Created by W.Langdon from
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- @Article{SADATHOSSEINI:2023:oceaneng,
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author = "Alireza {Sadat Hosseini} and Amir Kabiri and
Amir H. Gandomi and Mehdi Shafieefar",
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title = "Genetic programming for the prediction of berm
breakwaters recession",
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journal = "Ocean Engineering",
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volume = "279",
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pages = "114465",
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year = "2023",
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ISSN = "0029-8018",
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DOI = "doi:10.1016/j.oceaneng.2023.114465",
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URL = "https://www.sciencedirect.com/science/article/pii/S0029801823008491",
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keywords = "genetic algorithms, genetic programming, Berm
Breakwater, Recession (Rec), Rebuild experiments,
Cumulative experiments, Multi-objective genetic
programming (MOGP)",
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abstract = "The response of berm breakwaters to wave forces has
been examined with rebuild and cumulative experiments.
In rebuild experiments, the breakwaters were
reconstructed after each test, whereas in cumulative
experiments the structural damages were examined at the
end of the experiment. This study presents a new method
to investigate the berm breakwaters recession
considering datasets collected of both types of
experiments. Cumulative experimental results were
converted to their equivalent rebuild experimental
results by modifying the number of waves for the
reported damage. After homogenizing the data, the
datasets were divided into the train, validation, and
test subsets. The data were analyzed using the
Multi-Objective Genetic Programming (MOGP) approach,
and a prediction model was created to evaluate the berm
breakwater recession. The results obtained from the
MOGP model were compared to outcomes computed using
implicit formulas available in the literature showing
that the MOGP model is accurate (R2 = 0.911 and RMSE =
0.111) with a relatively broader applicability range.
The impact of each input parameter on the berm
breakwater recession was examined using parametric and
sensitivity analyses. The stability number was the most
important parameter impacting the damage on the coastal
structure. The results are in line with findings
reported in previous studies",
- }
Genetic Programming entries for
Alireza Sadat Hosseini
Amir Kabiri
A H Gandomi
Mehdi Shafieefar
Citations