Discharge predicted in compound channels using adaptive neuro-fuzzy inference system (ANFIS)

Author:

Khattab Noor I.1,Mohammed Ahmed Y.1,Mala Obaida Arwa A.1

Affiliation:

1. Dams and Water Resources Engineering Department, University of Mosul , Mosul , Iraq

Abstract

Abstract Some hydraulic structures and phenomena, including compound channels, must be studied in relation to open channel flow. Despite the fact that the primary channel and watersheds share a similar degree of roughness, estimating discharge in composite channels with mainstreams and flood plains has proved tricky. The flow discharge for a compound channel with different roughness in the primary and flood plain channels has been studied, and the results computed experimentally using horizontal division level have been compared with those predicted using dimensional analysis and an adaptive neuro-fuzzy inference system. The results show good agreement between experimental and numerical for discharge calculation according to root-mean-square error, MARE, R 2, SI, and Nash–Sutcliffe efficiency, with a percentage error not exceeding ±5%.

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Aerospace Engineering,General Materials Science,Civil and Structural Engineering,Environmental Engineering

Reference21 articles.

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5. Sheikh Khozani Z, Khosravi K, Torabi M, Mosavi A, Rezaei B, Rabczuk T. Shear stress distribution prediction in symmetric compound channels using data mining and machine learning models. Front Struct Civ Eng. 2020;14(5):1097–109.

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