Two new soft computing models, namely genetic programming (GP) and genetic artificial algorithm (GAA) neural network (a combination of modified genetic algorithm and artificial neural network methods) were developed in order to predict the percentage of shear force in a rectangular channel with non-homogeneous roughness. The ability of these methods to estimate the percentage of shear force was investigated. Moreover, the independent parameters' effectiveness in predicting the percentage of shear force was determined using sensitivity analysis. According to the results, the GP model demonstrated superior performance to the GAA model. A comparison was also made between the GP program determined as the best model and five equations obtained in prior research. The GP model with the lowest error values (root mean square error ((RMSE) of 0.0515) had the best function compared with the other equations presented for rough and smooth channels as well as smooth ducts. The equation proposed for rectangular channels with rough boundaries (RMSE of 0.0642) outperformed the prior equations for smooth boundaries.
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Research Article|
September 15 2015
Application of a soft computing technique in predicting the percentage of shear force carried by walls in a rectangular channel with non-homogeneous roughness
Zohreh Sheikh Khozani;
Zohreh Sheikh Khozani
1Department of Civil Engineering, Razi University, Kermanshah, Iran
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Hossein Bonakdari;
1Department of Civil Engineering, Razi University, Kermanshah, Iran
E-mail: [email protected]
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Amir Hossein Zaji
Amir Hossein Zaji
1Department of Civil Engineering, Razi University, Kermanshah, Iran
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Water Sci Technol (2016) 73 (1): 124–129.
Article history
Received:
January 15 2015
Accepted:
September 01 2015
Citation
Zohreh Sheikh Khozani, Hossein Bonakdari, Amir Hossein Zaji; Application of a soft computing technique in predicting the percentage of shear force carried by walls in a rectangular channel with non-homogeneous roughness. Water Sci Technol 8 January 2016; 73 (1): 124–129. doi: https://doi.org/10.2166/wst.2015.470
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