Genetic programming for the prediction of berm breakwaters recession

Sadat Hosseini, A; Kabiri, A; Gandomi, AH; Shafieefar, M

Genetic programming for the prediction of berm breakwaters recession

Sadat Hosseini, A Kabiri, A Gandomi, AH Shafieefar, M

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Publisher:: PERGAMON-ELSEVIER SCIENCE LTD
Publication Type:: Journal Article
Citation:: Ocean Engineering, 2023, 279
Issue Date:: 2023-07-01

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Field	Value	Language
dc.contributor.author	Sadat Hosseini, A
dc.contributor.author	Kabiri, A
dc.contributor.author	Gandomi, AH
dc.contributor.author	Shafieefar, M
dc.date.accessioned	2024-04-25T02:16:24Z
dc.date.available	2024-04-25T02:16:24Z
dc.date.issued	2023-07-01
dc.identifier.citation	Ocean Engineering, 2023, 279
dc.identifier.issn	0029-8018
dc.identifier.issn	1873-5258
dc.identifier.uri	http://hdl.handle.net/10453/178360
dc.description.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.
dc.language	English
dc.publisher	PERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartof	Ocean Engineering
dc.relation.isbasedon	10.1016/j.oceaneng.2023.114465
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0405 Oceanography, 0905 Civil Engineering, 0911 Maritime Engineering
dc.subject.classification	Civil Engineering
dc.subject.classification	4005 Civil engineering
dc.subject.classification	4012 Fluid mechanics and thermal engineering
dc.subject.classification	4015 Maritime engineering
dc.title	Genetic programming for the prediction of berm breakwaters recession
dc.type	Journal Article
utslib.citation.volume	279
utslib.for	0405 Oceanography
utslib.for	0905 Civil Engineering
utslib.for	0911 Maritime Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
dc.date.updated	2024-04-25T02:15:38Z
pubs.publication-status	Published
pubs.volume	279

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.

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http://hdl.handle.net/10453/178360