Genetic programming to predict ski-jump bucket spill-way scour

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{MDAZAMATHULLA2008477,

• author = "H. Md Azamathulla and A. {Ab. Ghani} and N. A. Zakaria and S. H. Lai and C. K. Chang and C. S. Leow and Z. Abuhasan",
• title = "Genetic programming to predict ski-jump bucket spill-way scour",
• journal = "Journal of Hydrodynamics, Ser. B",
• volume = "20",
• number = "4",
• pages = "477--484",
• year = "2008",
• ISSN = "1001-6058",
• DOI = "doi:10.1016/S1001-6058(08)60083-9",
• URL = "http://www.sciencedirect.com/science/article/B8CX5-4TCY8GV-B/2/f3004ab0cd7ed153a22b7f5d637afc89",
• month = aug,
• keywords = "genetic algorithms, genetic programming, neural networks, spillway scour, ski-jump bucket",
• abstract = "Researchers in the past had noticed that application of Artificial Neural Networks (ANN) in place of conventional statistics on the basis of data mining techniques predicts more accurate results in hydraulic predictions. Mostly these works pertained to applications of ANN. Recently, another tool of soft computing, namely, Genetic Programming (GP) has caught the attention of researchers in civil engineering computing. This article examines the usefulness of the GP based approach to predict the relative scour depth downstream of a common type of ski-jump bucket spillway. Actual field measurements were used to develop the GP model. The GP based estimations were found to be equally and more accurate than the ANN based ones, especially, when the underlying cause-effect relationship became more uncertain to model.",

}

Genetic Programming entries for Hazi Mohammad Azamathulla Aminuddin Ab Ghani Nor Azazi Zakaria Sai Hin Lai Chun Kiat Chang Cheng Siang Leow Zorkeflee Abu Hasan

Citations