Estimating soil wetting patterns for drip irrigation using genetic programming
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gp-bibliography.bib Revision:1.7954
- @Article{Samadianfard:2012:SRAR,
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title = "Estimating soil wetting patterns for drip irrigation
using genetic programming",
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author = "S. Samadianfard and A. A. Sadraddini and
A. H. Nazemi and G. Provenzano and O. Kisi",
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journal = "Spanish Journal of Agricultural Research",
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year = "2012",
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volume = "10",
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number = "4",
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pages = "1155--1166",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, HYDRUS 2D, infiltration,
numerical models, soil texture triangle",
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publisher = "Instituto Nacional de Investigaci{\'o}n y
Tecnolog{\'i}a Agraria y Alimentaria (INIA)",
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URL = "http://revistas.inia.es/index.php/sjar/article/view/2224",
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DOI = "doi:10.5424/sjar/2012104-502-11",
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ISSN = "1695-971X",
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bibsource = "OAI-PMH server at dialnet.unirioja.es",
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language = "eng",
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oai = "oai:dialnet.unirioja.es:ART0000519218",
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rights = "free",
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URL = "http://dialnet.unirioja.es/servlet/oaiart?codigo=4091324",
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abstract = "Drip irrigation is considered as one of the most
efficient irrigation systems. Knowledge of the soil
wetted perimeter arising from infiltration of water
from drippers is important in the design and management
of efficient irrigation systems. To this aim, numerical
models can represent a powerful tool to analyse the
evolution of the wetting pattern during irrigation, in
order to explore drip irrigation management strategies,
to set up the duration of irrigation, and finally to
optimise water use efficiency. This paper examines the
potential of genetic programming (GP) in simulating
wetting patterns of drip irrigation. First by
considering 12 different soil textures of USDA.SCS soil
texture triangle, different emitter discharge and
duration of irrigation, soil wetting patterns have been
simulated by using HYDRUS 2D software. Then using the
calculated values of depth and radius of wetting
pattern as target outputs, two different GP models have
been considered. Finally, the capability of GP for
simulating wetting patterns was analysed using some
values of data set that were not used in training.
Results showed that the GP method had good agreement
with results of HYDRUS 2D software in the case of
considering full set of operators with R2 of 0.99 and
0.99 and root mean squared error of 2.88 and 4.94 in
estimation of radius and depth of wetting patterns,
respectively. Also, field experimental results in a
sandy loam soil with emitter discharge of 4 L h-1
showed reasonable agreement with GP results. As a
conclusion, the results of the study demonstrate the
usefulness of the GP method for estimating wetting
patterns of drip irrigation.",
- }
Genetic Programming entries for
Saeed Samadianfard
Seyed Ali Ashrafla Sadraddini
Amir Hossein Nazemi
Giuseppe Provenzano
Ozgur Kisi
Citations