ADAPTIVE NEURO-FUZZY COMPUTING TECHNIQUE FOR DETERMINING TURBULENT FLOW FRICTION COEFFICIENT

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GIVEHCHI MOHAMMAD; BARDESTANI SOGHRA

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Journal: WATER AND WASTEWATER Year:2013 | Volume:24 | Issue:2 (86) Page(s): 117-122

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Title

ADAPTIVE NEURO-FUZZY COMPUTING TECHNIQUE FOR DETERMINING TURBULENT FLOW FRICTION COEFFICIENT

Author(s)

GIVEHCHI MOHAMMAD | BARDESTANI SOGHRA | Issue Writer Certificate

Keywords

FRICTION COEFFICIENTQ2

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMQ2

COLEBROOK’S EQUATIONQ2

PIPE RELATIVE ROUGHNESSQ2

REYNOLDS NUMBERQ2

Abstract

Estimation of the FRICTION COEFFICIENT in pipes is very important in many water and wastewater engineering issues, such as distribution of velocity and shear stress, erosion, sediment transport and head loss. In analyzing these problems, knowing the FRICTION COEFFICIENT, can obtain estimates that are more accurate. In this study in order to estimate the FRICTION COEFFICIENT in pipes, using ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMs (ANFIS), grid partition method was used. For training and testing of neuro-fuzzy model, the data derived from the Colebrook's equation was used. In the neuro-fuzzy approach, PIPE RELATIVE ROUGHNESS and REYNOLDS NUMBER are considered as input variables and FRICTION COEFFICIENT as output variable is considered. Performance of the proposed approach was evaluated by using of the data obtained from the COLEBROOK’S EQUATION and based on statistical indicators such as coefficient determination (R2), root mean squared error (RMSE) and mean absolute error (MAE). The results showed that the adaptive nerou-fuzzy inference system with grid partition method and gauss model as an input membership function and linear as an output function could estimate FRICTION COEFFICIENT more accurately than other conditions. The new proposed approach in this paper has capability of application in the practical design issues and can be combined with mathematical and numerical models of sediment transfer or real-time updating of these models.

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APA: Copy

GIVEHCHI, MOHAMMAD, & BARDESTANI, SOGHRA. (2013). ADAPTIVE NEURO-FUZZY COMPUTING TECHNIQUE FOR DETERMINING TURBULENT FLOW FRICTION COEFFICIENT. WATER AND WASTEWATER, 24(2 (86)), 117-122. SID. https://sid.ir/paper/104152/en

Vancouver: Copy

GIVEHCHI MOHAMMAD, BARDESTANI SOGHRA. ADAPTIVE NEURO-FUZZY COMPUTING TECHNIQUE FOR DETERMINING TURBULENT FLOW FRICTION COEFFICIENT. WATER AND WASTEWATER[Internet]. 2013;24(2 (86)):117-122. Available from: https://sid.ir/paper/104152/en

IEEE: Copy

MOHAMMAD GIVEHCHI, and SOGHRA BARDESTANI, “ADAPTIVE NEURO-FUZZY COMPUTING TECHNIQUE FOR DETERMINING TURBULENT FLOW FRICTION COEFFICIENT,” WATER AND WASTEWATER, vol. 24, no. 2 (86), pp. 117–122, 2013, [Online]. Available: https://sid.ir/paper/104152/en

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