Artificial Neural Network Application for Predicting Drag Coefficient in Flexible Vegetated Channels

Authors

  • Muhammad Mujahid Muhammad Department of Civil and Environmental Engineering, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia. Department of Water Resources and Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria.
  • Khamaruzaman Wan Yusof Department of Civil and Environmental Engineering, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia.
  • Muhammad Raza Ul Mustafa Department of Civil and Environmental Engineering, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia.
  • Nor Azazi Zakaria River Engineering and Urban Drainage Research Center, Universiti Sains Malaysia, Pulau Pinang, Malaysia.
  • Aminuddin Ab. Ghani River Engineering and Urban Drainage Research Center, Universiti Sains Malaysia, Pulau Pinang, Malaysia.

Keywords:

Artificial Neural Network, Dimensional Analysis, Drag Coefficient, Flexible Vegetated Channels,

Abstract

Previously numerous equations were developed using conventional methods to estimate vegetal drag coefficient by treating submerged and emergent vegetation independently, there is need to derive a generalized relationship that can be applied irrespective of the vegetation submergence with respect to flow depth. In this regard, the present study uses artificial neural network (ANN) as an advanced tool for prediction of drag coefficient in flexible vegetated channels. The training and testing patterns of the proposed ANN model were based on experimental results from the field and laboratory studies that combined both the submerged and emergent grass. A functional relation based on flow parameters and vegetation properties was derived through the use of dimensional analysis. The ANN model developed herein showed significantly better results in several model performance criteria when applied for verification.

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Published

2018-03-01

How to Cite

Muhammad, M. M., Wan Yusof, K., Mustafa, M. R. U., Zakaria, N. A., & Ab. Ghani, A. (2018). Artificial Neural Network Application for Predicting Drag Coefficient in Flexible Vegetated Channels. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-12), 99–102. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3834

Issue

Vol. 10 No. 1-12: Gearing for a Greener Future

Section

Articles

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