Prediction of Flow Friction Coefficient using GEP and ANN Methods

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Research areas:
Year:
2015
Type of Publication:
Article
Keywords:
Artificial Neural Network, Friction Coefficient, Gene Expression Programming, Water Distribution Networks, Wastewater Engineering
Authors:
Kiyoumars Roushangar; Farzin Homayounfar
Journal:
IJAIM
Volume:
4
Number:
2
Pages:
65-68
Month:
September
Abstract:
The main parameters in the analysis of water distribution networks are the friction coefficients, lengths and diameters of pipes. Estimation of the friction coefficient of pipes is very important in the field of water and wastewater engineering, such as distribution of velocity and shear stress, erosion, sediment transport and head loss. Several relations have been proposed to estimate the friction coefficient of pipes, but the results of the mentioned equations are not general and acceptable. The aim of present study is to apply Gene Expression Programming (GEP) and Artificial Neural Network (ANN) methods to prediction the friction coefficient of pipes and sensitivity analysis of input parameters. Comparison between Gene Expression Programming and Artificial Neural Network shows the noticeable efficiency of the Gene Expression Programming.
Full text: IJAIM_477_Final.pdf

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