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PREDICTION OF LOCAL SCOUR AROUND BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS 1
Author(s) -
Choi SungUk,
Cheong Sanghwa
Publication year - 2006
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2006.tb03852.x
Subject(s) - artificial neural network , bridge (graph theory) , field (mathematics) , pier , process (computing) , computer science , engineering , artificial intelligence , machine learning , civil engineering , mathematics , medicine , pure mathematics , operating system
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.