Environmental Earth Sciences, ( ISI ), Volume (75), No (2), Year (2016-1) , Pages (261-272)

Title : ( Deriving an intelligent model for soil compression index utilizing multi-gene genetic programming )

Authors: danial mohammadzadeh shadmehri , Jafar Bolouri Bazaz , S. H. Vafaee Jani Yazd , Amir H. Alavi ,

Citation: BibTeX | EndNote

Multi-gene genetic programming (MGGP) is a new nonlinear system modeling approach that integrates the capabilities of standard GP and classical regression. This paper deals with the prediction of compression index of fine-grained soils using this robust technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. The prediction coefficients of determination were 0.856 and 0.840 for the training and testing data, respectively. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords

, Multi, gene genetic programming Soil compression index Soil engineering properties
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@article{paperid:1058656,
author = {Mohammadzadeh Shadmehri, Danial and Bolouri Bazaz, Jafar and S. H. Vafaee Jani Yazd and Amir H. Alavi},
title = {Deriving an intelligent model for soil compression index utilizing multi-gene genetic programming},
journal = {Environmental Earth Sciences},
year = {2016},
volume = {75},
number = {2},
month = {January},
issn = {1866-6280},
pages = {261--272},
numpages = {11},
keywords = {Multi-gene genetic programming Soil compression index Soil engineering properties Prediction},
}

[Download]

%0 Journal Article
%T Deriving an intelligent model for soil compression index utilizing multi-gene genetic programming
%A Mohammadzadeh Shadmehri, Danial
%A Bolouri Bazaz, Jafar
%A S. H. Vafaee Jani Yazd
%A Amir H. Alavi
%J Environmental Earth Sciences
%@ 1866-6280
%D 2016

[Download]