Genetic Programming and Its Application in Real-Time Runoff Forecasting
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{khu:2001:JASRA,
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author = "Soon Thiam Khu and Shie-Yui Liong and
Vladan Babovic and Henrik Madsen and Nitin Muttil",
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title = "Genetic Programming and Its Application in Real-Time
Runoff Forecasting",
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journal = "Journal of the American Water Resources Association",
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year = "2001",
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volume = "37",
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number = "2",
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pages = "439--451",
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month = apr,
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publisher = "American Water Resources Association",
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keywords = "genetic algorithms, genetic programming, Runoff
forecasting, Rainfall-runoff models, Storms, NAM
rainfall-runoff simulation model, MIKE II hydrodynamic
model, NAMKAL, France, Orgeval River, Ru des Avenelles,
Ru de Bourgogne, Ru de Rognon",
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DOI = "doi:10.1111/j.1752-1688.2001.tb00980.x",
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size = "13 pages",
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abstract = "Genetic programming (GP), a relatively new
evolutionary technique, is demonstrated in this study
to evolve codes for the solution of problems. First, a
simple example in the area of symbolic regression is
considered. GP is then applied to real-time runoff
forecasting for the Orgeval catchment in France. In
this study, GP functions as an error updating scheme to
complement a rainfall-runoff model, MIKE11/NAM. Hourly
runoff forecasts of different updating intervals are
performed for forecast horizons of up to nine hours.
The results show that the proposed updating scheme is
able to predict the runoff quite accurately for all
updating intervals considered and particularly for
updating intervals not exceeding the time of
concentration of the catchment. The results are also
compared with those of an earlier study, by the World
Meteorological Organization, in which autoregression
and Kalman filter were used as the updating methods.
Comparisons show that GP is a better updating tool for
real-time flow forecasting. Another important finding
from this study is that nondimensionalizing the
variables enhances the symbolic regression process
significantly.",
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notes = "AWRA Paper Number 99178",
- }
Genetic Programming entries for
Soon-Thiam Khu
Shie-Yui Liong
Vladan Babovic
Henrik Madsen
Nitin Muttil
Citations