Rainfall-Runoff Modeling Based on Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @InCollection{Babovic:2006:,
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author = "Vladan Babovic and Maarten Keijzer",
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title = "Rainfall-Runoff Modeling Based on Genetic
Programming",
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booktitle = "Encyclopedia of Hydrological Sciences",
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publisher = "Wiley",
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year = "2006",
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editor = "Malcolm G. Anderson and Keith Beven and et al.",
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month = "15 " # apr,
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keywords = "genetic algorithms, genetic programming,
Hydroinformatics, symbolic regression, empirical
equations, rainfall-runoff",
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isbn13 = "9780470848944",
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URL = "http://onlinelibrary.wiley.com/doi/10.1002/0470848944.hsa017/abstract",
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DOI = "doi:10.1002/0470848944.hsa017",
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abstract = "The runoff formation process is believed to be highly
nonlinear, time varying, spatially distributed, and not
easily described by simple models. Considerable time
and effort has been directed to model this process, and
many hydrologic models have been built specifically for
this purpose. All of them, however, require significant
amounts of data for their respective calibration and
validation. Using physical models raises issues of
collecting the appropriate data with sufficient
accuracy. In most cases, it is difficult to collect all
the data necessary for such a model. By using
data-driven models such as genetic programming (GP),
one can attempt to model runoff on the basis of
available hydrometeorological data. This work addresses
the use of GP for creating rainfall-runoff (R-R) models
both on the basis of data alone, as well as in
combination with conceptual models (i.e taking
advantage of knowledge about the problem domain).",
- }
Genetic Programming entries for
Vladan Babovic
Maarten Keijzer
Citations