GENETIC PROGRAMMING TO PREDICT SKI-JUMP BUCKET SPILLWAY SCOUR  

作　　者：AZAMATHULLA H. MD GHANI A. AB ZAKARIA N. A LAI S. H CHANG C. K LEOW C. S ABUHASAN Z 

机构地区：[1]River Engineering and Urban Drainage Research Centre, University Sains Malaysia

出　　处：《Journal of Hydrodynamics》2008年第4期477-484,共8页水动力学研究与进展B辑（英文版）

基　　金：University Sains Malaysia for funding a short term grant (304.PREDAC.6035262) to conduct this on-going research

摘　　要：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.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.

关 键 词：Genetic Programming （GP） neural networks spillway scour ski-jump bucket 

分 类 号：TV135.2[水利工程—水力学及河流动力学]