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Estimating shear stress in a rectangular channel with rough boundaries using an optimized SVM method

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Abstract

The accurate simulation of wall and bed shear stresses in rectangular channels is one of the most important topics in hydraulic engineering. In this study, the support vector machine (SVM) soft computing technique is utilized to simulate the shear stress in a rectangular channel with rough boundaries. In the modeling procedure, eight different SVM models with linear, sigmoid, polynomial, multi-quadratic, Gaussian, rational quadratic, exponential and Laplacian kernel functions are examined. Finally, the different input combinations are assessed to introduce the most accurate SVM models in wall and bed shear stress prediction, whose output programs are also presented. The results are compared with experimental data and other researchers’ equations, and it is found that the SVM models with RMSE of 0.0447 and 0.0566 in wall and bed stress prediction, respectively, outperform previous equations.

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Authors and Affiliations

  1. Department of Civil Engineering, Razi University, Kermanshah, Iran

    Zohreh Sheikh Khozani, Hossein Bonakdari & Amir Hossein Zaji

Authors
  1. Zohreh Sheikh Khozani
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  2. Hossein Bonakdari
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  3. Amir Hossein Zaji
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Correspondence to Hossein Bonakdari.

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Khozani, Z.S., Bonakdari, H. & Zaji, A.H. Estimating shear stress in a rectangular channel with rough boundaries using an optimized SVM method. Neural Comput & Applic 30, 2555–2567 (2018). https://doi.org/10.1007/s00521-016-2792-8

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  • DOI: https://doi.org/10.1007/s00521-016-2792-8

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