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Prediction of soil erodibility factor for Peninsular Malaysia soil series using ANN

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Abstract

Soil erodibility factor (susceptibility of soil to be lost to erosion) is one of the components of the universal soil loss equation. This study presents an artificial neural network (ANN) model using 74 soil series provided by the Department of Agriculture, Malaysia. The ANN model produces acceptable results: the K values for 74 soil series of Peninsular Malaysia give much better information to engineers in determining the soil loss and sediment yield for a given development area.

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Acknowledgments

We would like to thank Department of Irrigation and Drainage (DID) Malaysia and Department of Agriculture (DOA) Malaysia and REDAC, Universiti Sains Malaysia for giving the opportunity in carry out the research and study. This is part of MSc Thesis progress report of first author.

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Authors and Affiliations

  1. River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Engineering Campus, Seri Ampangan, 14300, Nibong Tebal, Penang, Malaysia

    Mohd Fazly Yusof & H. Md. Azamathulla

  2. School of Civil Engineering, Universiti Sains Malaysia, Engineering Campus, Seri Ampangan, 14300, Nibong Tebal, Penang, Malaysia

    Rozi Abdullah

Authors
  1. Mohd Fazly Yusof
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  2. H. Md. Azamathulla
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  3. Rozi Abdullah
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Correspondence to Mohd Fazly Yusof.

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Yusof, M.F., Azamathulla, H.M. & Abdullah, R. Prediction of soil erodibility factor for Peninsular Malaysia soil series using ANN. Neural Comput & Applic 24, 383–389 (2014). https://doi.org/10.1007/s00521-012-1236-3

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  • DOI: https://doi.org/10.1007/s00521-012-1236-3

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