Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels

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Title:Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels
Creators:
Ebtehaj, Isa ; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Bonakdari, Hossein ; bonakdari at yahoo dot com; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Zaji , Amir Hossein; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Hin Joo Bong, Charles ; Department of Civil Engineering, Faculty of Engineering, University Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia.
Ab Ghani, Aminuddin ; River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Pulau Pinang, Malaysia.
Journal or Publication Title:
Journal of Hydrology and Hydromechanics, 64, 3, pp. 252-260
Uncontrolled Keywords:decision tree, incipient motion, multilayer perceptron (MLP), Froude number

Abstract

A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range of hydraulic parameters. Because existing equations do not consider the effect of sediment bed thickness on incipient motion estimation, this parameter is applied in this study along with the multilayer perceptron (MLP), a hybrid method based on decision trees (DT) (MLP-DT), to estimate incipient motion. According to a comparison with the observed experimental outcome, the proposed method performs well (MARE = 0.048, RMSE = 0.134, SI = 0.06, BIAS = –0.036). The performance of MLP and MLP-DT is compared with that of existing regression-based equations, and significantly higher performance over existing models is observed. Finally, an explicit expression for practical engineering is also provided.

Official URL: http://147.213.145.2/vc/vc1.asp

Title:Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels
Translated title:Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels
Creators:
Ebtehaj, Isa ; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Bonakdari, Hossein ; bonakdari at yahoo dot com; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Zaji , Amir Hossein; Department of Civil Engineering, Razi University, 67149-67346 Baghe Abrisham, Kermanshah, Iran.
Hin Joo Bong, Charles ; Department of Civil Engineering, Faculty of Engineering, University Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia.
Ab Ghani, Aminuddin ; River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Pulau Pinang, Malaysia.
Uncontrolled Keywords:decision tree, incipient motion, multilayer perceptron (MLP), Froude number
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Mathematics, Physics and Earth Sciences > Institute of Hydrodynamics > Journal of Hydrology and Hydromechanics
Journal or Publication Title:Journal of Hydrology and Hydromechanics
Volume:64
Number:3
Page Range:pp. 252-260
ISSN:0042-790X
Publisher:Institute of Hydrology of the Slovak Academy of Sciences and the Institute of Hydrodynamics of the Academy of Sciences of the Czech Republic
Related URLs:
URLURL Type
http://avi.lib.cas.cz/node/55Publisher
ID Code:8667
Item Type:Article
Deposited On:18 Aug 2016 14:26
Last Modified:18 Aug 2016 12:26

Citation

Ebtehaj, Isa; Bonakdari, Hossein; Zaji , Amir Hossein; Hin Joo Bong, Charles; Ab Ghani, Aminuddin (2016) Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels. Journal of Hydrology and Hydromechanics, 64 (3). pp. 252-260. ISSN 0042-790X

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