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Earth Science Informatics

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01.12.2014 | Research Article

Group Method of Data Handling to Predict Scour at Downstream of a Ski-Jump Bucket Spillway

verfasst von: Mohammad Najafzadeh, Gholam-Abbas Barani, Masoud-Reza Hessami-Kermani

Erschienen in: Earth Science Informatics | Ausgabe 4/2014

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Abstract

This study introduces a method to predict scour hole geometry at downstream of a ski-jump bucket by group method of data handling (GMDH). The GMDH network was developed using evolutionary and iterative algorithms including those of genetic programming (GP), particle swarm optimization (PSO), and back propagation (BP) algorithms. Results of alternative GMDH networks were compared with those obtained using artificial neural networks, genetic programming, ANFIS, empirical equations, and regression-based equations. Performances indicated that proposed GMDH-BP produced more accurate results in comparison with other methods. Moreover, the most effective independent parameters on scour hole geometry were determined using sensitivity analysis. Finally, combination of evolutionary and iterative algorithms has been confirmed that the GMDH network is a useful soft computing tool for prediction of scour hole geometry at downstream of a ski-jump bucket.

Vorheriger Artikel Successive-station monthly streamflow prediction using neuro-wavelet technique

Nächster Artikel SWEET ontology coverage for earth system sciences

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Titel: Group Method of Data Handling to Predict Scour at Downstream of a Ski-Jump Bucket Spillway
verfasst von: Mohammad Najafzadeh
Gholam-Abbas Barani
Masoud-Reza Hessami-Kermani
Publikationsdatum: 01.12.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 4/2014
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-013-0140-4

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