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You are here : eLibrary : IAHR World Congress Proceedings : 32nd Congress - Venice (2007) : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness. : Estimation of the discharge coefficient of canal radial gate using artificial neural network
Estimation of the discharge coefficient of canal radial gate using artificial neural network
Author : AMIR AHMAD DEHGHANI, KOICHI SUZUKI, FAZLOLAH HASHEMI and S. AMIN SALAMATIAN
There is a need to define accurately the discharge coefficients of radial gates, when radial gates are used to control flow and water levels in a canal system. Recent developments in automatic flow regulation schemes for canal systems require accurate definition of canal radial gate discharge coefficients. In this study, dimensionless parameters were obtained by dimensional analysis, and then multilayer perceptron neural network is used for the estimation of the discharge coefficient of canal radial gate in submerged flow condition. Artificial Neural Network (ANN) is a mathematical tool, which is capable of making a non-linear mapping between input and output spaces.The comparison of the results with previous studies shows that the estimated discharge coefficients by the neural network are in good agreement with the experimental data.
File Size : 429,165 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 32nd Congress - Venice (2007)
Article : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness.
Date Published : 01/07/2007
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