Modelling the dynamics of the evapotranspiration process using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Parasuraman:2007:HSJ,
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author = "Kamban Parasuraman and Amin Elshorbagy and
Sean K. Carey",
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title = "Modelling the dynamics of the evapotranspiration
process using genetic programming",
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journal = "Hydrological Sciences Journal",
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year = "2007",
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volume = "52",
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number = "3",
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pages = "563--578",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "0262-6667",
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URL = "http://www.tandfonline.com/doi/abs/10.1623/hysj.52.3.563",
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DOI = "doi:10.1623/hysj.52.3.563",
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size = "16 pages",
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abstract = "Evapotranspiration constitutes one of the major
components of the hydrological cycle and hence its
accurate estimation is of vital importance to assess
water availability and requirements. This study
explores the utility of genetic programming (GP) to
model the evapotranspiration process. An important
characteristic of GP is that both the model structure
and coefficients are simultaneously optimized. The
method is applied in modelling eddy-covariance
(EC)-measured latent heat (LE) as a function of net
radiation (NR), ground temperature (GT), air
temperature (AT), wind speed (WS) and relative humidity
(RH). Two case studies having different climatic and
topographic conditions are considered. The performance
of the GP model is compared with artificial neural
network (ANN) models and the traditional
Penman-Monteith (PM) method. Results from the study
indicate that both the datadriven models, GP and ANNs,
performed better than the PM method. However,
performance of the GP model is comparable with that of
the ANN model. The GP-evolved models are dominated by
NR and GT, indicating that these two inputs can
represent most of the variance in LE. The results show
that the GP-evolved equations are parsimonious and
understandable, and are well suited to modelling the
dynamics of the evapotranspiration process.",
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notes = "Journal of the International Association of
Hydrological Sciences",
- }
Genetic Programming entries for
Kamban Parasuraman
Amin Elshorbagy
Sean K Carey
Citations