Application of Artificial Neural Network, Kriging, and Inverse Distance Weighting Models for Estimation of Scour Depth around Bridge Pier with Bed Sill

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Application of Artificial Neural Network, Kriging, and Inverse Distance Weighting Models for Estimation of Scour Depth around Bridge Pier with Bed Sill

This paper outlines the application of the multi-layer perceptron artificial neural network (ANN), ordinary kriging (OK), and inverse distance weighting (IDW) models in the estimation of local scour depth around bridge piers. As part of this study, bridge piers were installed with bed sills at the bed of an experimental flume. Experimental tests were conducted under different flow conditions an...

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scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

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Predicting Bridge Pier Scour Depth with SVM

Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper attempts have been ma...

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combined effect of bed sill and collar in reduction of scour depth around cylindrical bridge piers

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ژورنال

عنوان ژورنال: Journal of Software Engineering and Applications

سال: 2010

ISSN: 1945-3116,1945-3124

DOI: 10.4236/jsea.2010.310112