An investigation on stream temperature analysis based on evolutionary computing
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- @Article{Doglioni:2008:HP,
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author = "A. Doglioni and O. Giustolisi and D. A. Savic and
B. W. Webb",
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title = "An investigation on stream temperature analysis based
on evolutionary computing",
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journal = "Hydrological Processes",
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year = "2008",
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volume = "22",
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number = "3",
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pages = "315--326",
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month = "30 " # jan,
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publisher = "John Wiley & Sons, Ltd.",
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keywords = "genetic algorithms, genetic programming, data-driven,
evolutionary modelling, multiobjective optimisation,
thermal dynamics, on-line prediction, simulation",
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ISSN = "1099-1085",
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URL = "http://dx.doi.org/10.1002/hyp.6607",
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DOI = "doi:10.1002/hyp.6607",
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size = "12 pages",
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abstract = "The data-driven technique, evolutionary polynomial
regression, has been tested and used for the study of
water temperature behaviour in the River Barle
(south-west England). The study aimed to produce
multiple models for forecasting water temperature,
using air temperature as input. In addition, river
discharge data were used to describe the hydrological
regime of the study stream, even if they are not
involved in the modelling phase. The availability of
data sampled at hourly intervals allowed behaviour to
be studied at several time scales, including short-term
lags between air temperature and water temperature. The
approach to model building differs from previous
studies in that the relationship between air
temperature and water temperature is not evaluated on
the basis of a multi-parameter regression, nor does it
identify particular structures; rather the evolutionary
technique identifies the model by itself. In fact, the
non-linear relationship between air temperature and
water temperature is investigated by an evolutionary
search in the space of particular pseudo-polynomials
structures.",
- }
Genetic Programming entries for
Angelo Doglioni
Orazio Giustolisi
Dragan Savic
Bruce Webb
Citations