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The performance comparison of the soft computing methods on the prediction of soil compaction parameters

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Abstract

The compaction parameters of soils known as the optimum moisture content (OMC) and maximum dry density (MDD) are necessary for the geotechnical engineering applications such as the fills, embankments, and dams. However, it takes a long time to determine the compaction parameters due to the laboratory test procedure. It was aimed to estimate the compaction parameters of soils with four soft computing methods and also to compare the performance of the methods in this study. For this purpose, a wide database consisting the index and standard proctor (SP) test results were used. Although all AI methods used in this study are successful on estimation of the MDD and OMC parameters, it was seen that the ELM method was the most successful method on the prediction of compaction parameters.

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Authors and Affiliations

  1. Technical Sciences Vocational School, Transportation Services, Mersin University, Mersin, Turkey

    Talas Fikret Kurnaz

  2. Faculty of Engineering and Architecture, Computer Engineering, Siirt University, Siirt, Turkey

    Yilmaz Kaya

Authors
  1. Talas Fikret Kurnaz
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  2. Yilmaz Kaya
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Correspondence to Talas Fikret Kurnaz.

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Responsible Editor: Zeynal Abiddin Erguler

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Kurnaz, T.F., Kaya, Y. The performance comparison of the soft computing methods on the prediction of soil compaction parameters. Arab J Geosci 13, 159 (2020). https://doi.org/10.1007/s12517-020-5171-9

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  • DOI: https://doi.org/10.1007/s12517-020-5171-9

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