Energy-based numerical models for assessment of soil liquefaction
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{Alavi2012541,
-
author = "Amir Hossein Alavi and Amir Hossein Gandomi",
-
title = "Energy-based numerical models for assessment of soil
liquefaction",
-
journal = "Geoscience Frontiers",
-
volume = "3",
-
number = "4",
-
pages = "541--555",
-
year = "2012",
-
ISSN = "1674-9871",
-
DOI = "doi:10.1016/j.gsf.2011.12.008",
-
URL = "http://www.sciencedirect.com/science/article/pii/S167498711100137X",
-
keywords = "genetic algorithms, genetic programming, Soil
liquefaction, Capacity energy, Multi expression
programming, Sand, Formulation",
-
abstract = "This study presents promising variants of genetic
programming (GP), namely linear genetic programming
(LGP) and multi expression programming (MEP) to
evaluate the liquefaction resistance of sandy soils.
Generalised LGP and MEP-based relationships were
developed between the strain energy density required to
trigger liquefaction (capacity energy) and the factors
affecting the liquefaction characteristics of sands.
The correlations were established based on well
established and widely dispersed experimental results
obtained from the literature. To verify the
applicability of the derived models, they were employed
to estimate the capacity energy values of parts of the
test results that were not included in the analysis.
The external validation of the models was verified
using statistical criteria recommended by researchers.
Sensitivity and parametric analyses were performed for
further verification of the correlations. The results
indicate that the proposed correlations are effectively
capable of capturing the liquefaction resistance of a
number of sandy soils. The developed correlations
provide a significantly better prediction performance
than the models found in the literature. Furthermore,
the best LGP and MEP models perform superior than the
optimal traditional GP model. The verification phases
confirm the efficiency of the derived correlations for
their general application to the assessment of the
strain energy at the onset of liquefaction.",
- }
Genetic Programming entries for
A H Alavi
A H Gandomi
Citations