Study of the volumetric water content based on density, suction and initial water content

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@Article{Zhou:2016:Measurement,
  author =       "Wan-Huan Zhou and Ankit Garg and Akhil Garg",
  title =        "Study of the volumetric water content based on
                 density, suction and initial water content",
  journal =      "Measurement",
  volume =       "94",
  pages =        "531--537",
  year =         "2016",
  ISSN =         "0263-2241",
  DOI =          "doi:10.1016/j.measurement.2016.08.034",
  URL =          "http://www.sciencedirect.com/science/article/pii/S026322411630495X",
  abstract =     "The practical application of determination of the soil
                 water retention curves (SWRC) is in seepage modelling
                 in unsaturated soil. The models based on the physics
                 behind the seepage mechanism has been developed for
                 predicting the SWRC. However, those models rarely
                 consider the combined effects of initial volumetric
                 water content and soil density. One of the best routes
                 to study these effects is to formulate the SWRC
                 models/functional relations with volumetric water
                 content as an output and the soil density, initial
                 volumetric water content and soil suction as input
                 parameters. In light of this, the present work
                 introduces the advanced soft computing methods such as
                 genetic programming (GP), artificial neural network and
                 support vector regression (SVR) to formulate the
                 volumetric water content models based on the suction,
                 density and initial volumetric water content. The
                 performance of the three models is compared based on
                 the standard measures and goodness-of-fit tests. The
                 findings from the statistical validation reveals that
                 the GP model performs the best in generalizing the
                 volumetric water content values based on the suction,
                 density and initial water content. Further, the 2-D and
                 3-D plots, evaluating the main and the interaction
                 effects of the three inputs on the volumetric water
                 content are generated based on the parametric procedure
                 of the best model. The study reveals that the
                 volumetric water content values behave non-linearly
                 with respect to soil suction because it first decreases
                 till a certain point of soil suction and then increases
                 suddenly.",
  keywords =     "genetic algorithms, genetic programming, Soil density,
                 SWRC, Soil suction, Initial water content",
}

Genetic Programming entries for Wan-Huan Zhou Ankit Garg Akhil Garg

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