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dc.contributor.authorMeyyappan, P L-
dc.contributor.authorSivapragasam, C-
dc.contributor.authorNeelamani, S-
dc.contributor.authorAl-Zaqah, Z K-
dc.contributor.authorAl-Khalidi, Md-
dc.identifier.issn2582-6727 (Online); 2582-6506 (Print)-
dc.description.abstractExperimental investigation on wave transmission, reflection and dissipation characteristics of rubble mound breakwater models are time consuming and expensive. However, such studies are required for designing the rubble mound breakwaters for marine structures in an optimal condition. In order to overcome such problems many researchers used various soft computing techniques such as Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Interference System (ANFIS), Genetic Programming (GP), Support Vector Machine (SVM) etc, in order to predict the design factors in the field of coastal engineering. The current work proposes Genetic Programming (GP) as a modeling tool to evolve mathematical models for the behavior of single and double breakwaters. Based on the detailed experimental data, GP models were performed to predict the reflected wave height (Hr), wave height on the breakwater (H5) and transmitted wave height (Ht) by considering with and without trigonometric effects of those breakwaters. The quality of predictability of the present model is measured by the statistical parameter, RMSE (Root Mean Square Error). Since the waves were more complex in nature, it is very essential in considering the trigonometric function’s effect in the modeling aspects. It is evident that, the GP model accurately described the non linear complex effects.en_US
dc.publisherNIScPR-CSIR, Indiaen_US
dc.sourceIJMS Vol.50(06) [June 2021]en_US
dc.subjectGenetic programmingen_US
dc.subjectRubble mound breakwateren_US
dc.titleModeling studies on the behavior of single and double rubble mound breakwaters using genetic programming toolen_US
dcterms.sourceIJMS Vol.50(06) [June 2021]en_US
Appears in Collections:IJMS Vol.50(06) [June 2021]

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