Prediction of local scour around bridge piers using artificial neural networks

Sung Uk Choi, Sanghwa Cheong

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

This paper describes a method for predicting local scour around bridge piers using an artificial neural network (ANN). Methods for selecting input variables, calibrations of network control parameters, learning process, and verifications are also discussed. The ANN model trained by laboratory data is applied to both laboratory and field measurements. The results illustrate that the ANN model can be used to predict local scour in the laboratories and in the field better than other empirical relationships that are currently in use. A parameter study is also carried out to investigate the importance of each input variable as reflected in data.

Original languageEnglish
Pages (from-to)487-494
Number of pages8
JournalJournal of the American Water Resources Association
Volume42
Issue number2
DOIs
Publication statusPublished - 2006 Apr 1

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pier
scour
artificial neural network
prediction
learning
calibration
laboratory
method
parameter

All Science Journal Classification (ASJC) codes

  • Ecology
  • Water Science and Technology
  • Earth-Surface Processes

Cite this

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Prediction of local scour around bridge piers using artificial neural networks. / Choi, Sung Uk; Cheong, Sanghwa.

In: Journal of the American Water Resources Association, Vol. 42, No. 2, 01.04.2006, p. 487-494.

Research output: Contribution to journalArticle

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