Prediction of added resistance using genetic programming

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@Article{LEE:2018:OE,

• author = "Jong-hyun Lee and Sung-soo Kim and Soon-sup Lee and Donghoon Kang and Jae-chul Lee",
• title = "Prediction of added resistance using genetic programming",
• journal = "Ocean Engineering",
• year = "2018",
• volume = "153",
• pages = "104--111",
• month = "1 " # apr,
• keywords = "genetic algorithms, genetic programming, Hydrodynamic design, Added resistance",
• ISSN = "0029-8018",
• URL = "http://www.sciencedirect.com/science/article/pii/S0029801818300970",
• DOI = "doi:10.1016/j.oceaneng.2018.01.089",
• size = "8 pages",
• abstract = "In recent years, the increasing demand for a reduction of carbon emission has made hydrodynamic design and the optimization of hull design more important. For appropriate hydrodynamic design, the added resistance needs to be predicted. However, as existing methods including computer simulations or experiments require considerable amounts of time and money, it is difficult to consider the prediction result at the initial design stage. Therefore, we propose a prediction method that can be used in the initial design stage for predicting the added resistance in waves, thereby contributing to the optimization of hull design and saving time and money. The proposed method is a nonlinear mathematical function and is based on genetic programming. For verification, the predicted results are compared with the experimental results and the strip theory results",
• notes = "Department of Ocean System Engineering, Institute of Marine Industry, Gyeongsang National University, South Korea",

}

Genetic Programming entries for Jonghyun Lee Sung-soo Kim Soon-sup Lee Donghoon Kang Jae-chul Lee

Citations