A new computational approach for estimation of wilting point for green infrastructure
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{GARG2017351,
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author = "Ankit Garg and Jinhui Li and Jinjun Hou and
Christian Berretta and Akhil Garg",
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title = "A new computational approach for estimation of wilting
point for green infrastructure",
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journal = "Measurement",
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year = "2017",
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volume = "111",
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pages = "351--358",
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month = dec,
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keywords = "genetic algorithms, genetic programming, wilting
point, soil fractal dimension, s index, clay content,
organic matter, evolutionary algorithms",
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ISSN = "0263-2241",
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bibsource = "OAI-PMH server at eprints.whiterose.ac.uk",
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publisher = "Elsevier",
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URL = "http://eprints.whiterose.ac.uk/119632/",
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URL = "http://www.sciencedirect.com/science/article/pii/S026322411730461X",
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DOI = "doi:10.1016/j.measurement.2017.07.026",
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size = "8 pages",
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abstract = "Wilting point is an important parameter indicating the
inhibition of plant transpiration processes, which is
essential for green infrastructures. Generalization of
wilting point is very essential for analysing the
hydrological performance of green infrastructures (e.g.
green roofs, biofiltration systems) and ecological
infrastructures (wetlands). Wilting point of various
species is known to be affected by the factors such as
soil clay content, soil organic matter, slope of soil
water characteristic curve at inflection point (i.e., s
index) and fractal dimension. Therefore, its practical
usefulness forms the strong basis in developing the
model that quantify wilting point with respects to the
deterministic factors. This study proposes the wilting
point model development task based on optimisation
approach of Genetic programming (GP) with respect to
the input variables (soil clay content, soil organic
matter, s-index and fractal dimension) for various type
of soils. The GP model developed is further
investigated by sensitivity and parametric analysis to
discover the relationships between wilting point and
input variables and the dominant inputs. Based on newly
developed model, it was found that wilting point
increases with fractal dimension while behaves highly
non-linear with respect to clay and organic content.
The combined effect of the clay and organic content was
found to greatly influence the wilting point. It
implies that wilting point should not be generalised as
usually done in literature.",
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notes = "also known as
\cite{oai:eprints.whiterose.ac.uk:119632}
Department of Civil and Environmental Engineering,
Shantou University, Shantou 515063, China",
- }
Genetic Programming entries for
Ankit Garg
Jinhui Li
Jinjun Hou
Christian Berretta
Akhil Garg
Citations