Neural Computing and Applications

, Volume 23, Issue 7–8, pp 2107–2112

Group method of data handling to predict scour depth around bridge piers

Original Article

DOI: 10.1007/s00521-012-1160-6

Cite this article as:
Najafzadeh, M. & Azamathulla, H.M. Neural Comput & Applic (2013) 23: 2107. doi:10.1007/s00521-012-1160-6

Abstract

In this study, group method of data handling network with quadratic polynomial was used to predict scour depth around bridge piers. Effective parameters on scour phenomena include sediment size, geometry of bridge pier, and upstream flow conditions. Different shapes of piers have been utilized to develop the GMDH network. Back propagation algorithm was performed to train the GHMD network which updated weighting coefficients of quadratic polynomial in each iteration of the training stage. The GMDH performed with the lowest errors of training and testing stages for cylindrical pier. Also, Richardson and Davis, Johnson’s equations produced relatively good performances for different types of piers. Finally, the results indicated that GMDH could be provided more accurate prediction than those obtained using traditional equations.

Keywords

GMDH Scour depth Bridge pier Traditional equations 

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Mohammad Najafzadeh
    • 1
  • Hazi Mohammad Azamathulla
    • 2
  1. 1.Department of Civil EngineeringShahid Bahonar UniversityKermanIran
  2. 2.River Engineering and Urban Drainage Research Centre (REDAC)Universiti Sains MalaysiaPenangMalaysia

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