%0 Journal Article
%T Estimation of van Genuchten SWCC model for unsaturated sands by means of the genetic programming
%J Scientia Iranica
%I Sharif University of Technology
%Z 1026-3098
%A Taban, A.
%A Sadeghi, M . Mirmohammad
%A Rowshanzamir, M.A.
%D 2018
%\ 08/01/2018
%V 25
%N 4
%P 2026-2038
%! Estimation of van Genuchten SWCC model for unsaturated sands by means of the genetic programming
%K SWCC
%K van Genuchten Model
%K Unsaturated soils
%K Genetic programming
%K Fitting Parameters
%R 10.24200/sci.2017.4206
%X The van Genuchten Model (1980) is widely-used for the description of the Soil-Water Characteristic Curve (SWCC) of a variety of soils. This study uses the Genetic Programming (GP) for the presentation of equations estimating the van Genuchten (vG) Model fitting parameters for unsaturated clean sand soils. Moreover, this study uses the data derived from the valid dataset of Benson et al. (2014), including 95 measured SWCCs in both drying and wetting phases. The data on the particle size distributions includes the fine-grain percentage (Fines %), d60, d10, besides the residual and saturated volumetric water content andÂ ), as the GP model inputs of set of terminal. As for the model outputs of set of terminal, the fitting parameters for the vG model include a and n. The functions used in the GP training were 'plus', 'minus', 'times', taken from the MATLAB default functions, 'mydivide' proposed by Silva (2007), and some other new power functions included by this study. Accordingly, new equations were presented for the estimation of vG Model fitting parameters for both forms of wetting and drying. Finally, to evaluate the accuracy of the proposed estimation equations, the GP results were evaluated and verified in different procedures.
%U http://scientiairanica.sharif.edu/article_4206_941a3b4ae8ad623078c06dc2c5d32da0.pdf