Modeling the sprinkler water distribution uniformity by data-driven methods based on effective variables
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gp-bibliography.bib Revision:1.7954
- @Article{Maroufpoor:2019:AWM,
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author = "Saman Maroufpoor and Jalal Shiri and Eisa Maroufpoor",
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title = "Modeling the sprinkler water distribution uniformity
by data-driven methods based on effective variables",
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journal = "Agricultural Water Management",
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year = "2019",
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volume = "215",
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pages = "63--73",
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month = "20 " # apr,
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keywords = "genetic algorithms, genetic programming, gene
expression programming, coefficient of uniformity,
k-fold testing, support vector machines, SVM, neural
networks, ANN, neuro-fuzzy, sprinkler irrigation",
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ISSN = "0378-3774",
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identifier = "RePEc:eee:agiwat:v:215:y:2019:i:c:p:63-73",
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oai = "oai:RePEc:eee:agiwat:v:215:y:2019:i:c:p:63-73",
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URL = "https://www.sciencedirect.com/science/article/pii/S0378377418313258",
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DOI = "doi:10.1016/j.agwat.2019.01.008",
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abstract = "The coefficient of uniformity (CU), an important
parameter in design of irrigation systems, affects the
quality and return of investment in irrigation projects
significantly, and is a good indicator of water losses.
In this paper, a single model was proposed to obtain
the CU values in four sprinkler types of ZK30, ZM22,
AMBO, and LUXOR. Average wind speed, coarseness index
(large and small nozzle diameters), and
sprinkler/lateral spacing were used as input parameters
to obtain the CU values through employing the
artificial neural networks (ANN), neuro-fuzzy grid
partitioning (NF-GP), neuro-fuzzy sub-clustering
(NF-SC), least square support vector machine (LS-SVM)
and gene expression programming (GEP) techniques. The
available data set consisted of 294 samples that were
used to evaluate the proposed methodology. The applied
techniques were assessed through the robust k-fold
testing data assignment mode. Based on the results, all
the applied models presented good capability in
estimating CU. The obtained results revealed that the
coarseness index (large nozzle diameter) had the lowest
impact on modelling CU is sprinkler irrigation
systems.",
- }
Genetic Programming entries for
Saman Maroufpoor
Jalal Shiri
Eisa Maroufpoor
Citations