Estimation of Pipeline Scour due to Waves by GMDH
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 5, Issue 3
Abstract
In the present study, the group method of data handling (GMDH) network is applied to predict scour depth below pipelines exposed to waves. The GMDH network is trained using a back-propagation (BP) algorithm. The pipeline scour is modeled as a function of three-dimensionless parameters, including the Keulegan-Carpenter number, the ratio of the initial gap to pipe diameter, and the Shields parameter. The performances of the GMDH network are compared with the adaptive neuro-fuzzy inference system (ANFIS) model, the model tree (MT), and empirical equation. The results indicated that the GMDH network produced a more accurate prediction of scour depth compared with other models.
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 5 • Issue 3 • August 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Sep 18, 2013
Accepted: Feb 26, 2014
Published online: May 2, 2014
Published in print: Aug 1, 2014
Discussion open until: Oct 2, 2014
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