Neural Computing and Applications

, Volume 24, Issue 2, pp 383–389 | Cite as

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

  • Mohd Fazly Yusof
  • H. Md. Azamathulla
  • Rozi Abdullah
Original Article


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.


Soil erodibility ANN Wischmeier erodibility equation Tew erodibility equation Peninsular Malaysia soil series 



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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Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  • Mohd Fazly Yusof
    • 1
  • H. Md. Azamathulla
    • 1
  • Rozi Abdullah
    • 2
  1. 1.River Engineering and Urban Drainage Research Centre (REDAC)Universiti Sains MalaysiaNibong TebalMalaysia
  2. 2.School of Civil EngineeringUniversiti Sains MalaysiaNibong TebalMalaysia

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