Prediction of Flow Friction Coefficient using GEP and ANN Methods

Research areas:

• Volume 4,Issue 2, Sept. 2015

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