A Computational Intelligence-Based Genetic Programming Approach for the Simulation of Soil Water Retention Curves
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Garg:2014:TPM,
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author = "Ankit Garg and Akhil Garg and K. Tai and
S. Barontini and Alexia Stokes",
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title = "A Computational Intelligence-Based Genetic Programming
Approach for the Simulation of Soil Water Retention
Curves",
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journal = "Transport in Porous Media",
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year = "2014",
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volume = "103",
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number = "3",
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pages = "497--513",
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keywords = "genetic algorithms, genetic programming, multi-gene
genetic programming, soil water retention curves,
swelling soils, enveloppe potential, environmental
sciences/biodiversity and ecology",
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ISSN = "1573-1634",
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URL = "https://hal.archives-ouvertes.fr/hal-01268778",
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URL = "http://dx.doi.org/10.1007/s11242-014-0313-8",
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DOI = "doi:10.1007/s11242-014-0313-8",
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publisher = "HAL CCSD; Springer Verlag",
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annote = "Indian Institute of Technology; Nanyang Technological
University (NTU); Department of Civil, Environmental,
Architectural Engineering and Mathematics ;
Universit{\`a} degli Studi di Brescia; BotAnique et
BioinforMatique de l'Architecture des Plantes (AMAP) ;
Universit{\'e} Montpellier 2 - Sciences et Techniques
(UM2) - Institut national de la recherche agronomique
(INRA) - Institut de recherche pour le
d{\'e}veloppement [IRD] - Centre de coop{\'e}ration
internationale en recherche agronomique pour le
d{\'e}veloppement (CIRAD) - Centre National de la
Recherche Scientifique (CNRS); Singapore Ministry of
Education Academic Research Fund",
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bibsource = "OAI-PMH server at api.archives-ouvertes.fr",
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contributor = "BotAnique et BioinforMatique de l'Architecture des
Plantes",
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identifier = "hal-01268778; DOI : 10.1007/s11242-014-0313-8;
PRODINRA : 274701",
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language = "en",
-
oai = "oai:HAL:hal-01268778v1",
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relation = "info:eu-repo/semantics/altIdentifier/doi/10.1007/s11242-014-0313-8",
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abstract = "Soil water retention curves are a key constitutive law
used to describe the physical behaviour of an
unsaturated soil. Various computational modelling
techniques, that formulate retention curve models, are
mostly based on existing soil databases, which rarely
consider any effect of stress on the soil water
retention. Such effects are crucial in the case of
swelling soils. This study illustrates and explores the
ability of computational intelligence-based genetic
programming to formulate the mathematical relationship
between the water content, in terms of degree of
saturation, and two input variables, i.e., net stress
and suction for three different soils (sand--kaolin
mixture, Gaduk Silt and Firouzkouh clay). The
predictions obtained from the proposed models are in
good agreement with the experimental data. The
parametric and sensitivity analysis conducted validates
the robustness of our proposed model by unveiling
important parameters and hidden non-linear
relationships.",
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notes = "also known as \cite{oai:HAL:hal-01268778v1}",
- }
Genetic Programming entries for
Ankit Garg
Akhil Garg
Kang Tai
S Barontini
Alexia Stokes
Citations