Rainfall Runoff Modelling based on Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7175
- @Article{NordicHy,
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author = "Vladan Babovic and Maarten Keijzer",
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title = "Rainfall Runoff Modelling based on Genetic
Programming",
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journal = "Nordic Hydrology",
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year = "2002",
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volume = "33",
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number = "5",
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pages = "331--346",
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month = oct,
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keywords = "genetic algorithms, genetic programming",
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ISSN = "0029-1277",
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URL = "
http://www.iwaponline.com/nh/033/0331/0330331.pdf",
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DOI = "
doi:10.2166/nh.2002.0012",
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size = "16 pages",
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abstract = "The runoff formation process is believed to be highly
non-linear, 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
use of genetic programming for creating rainfall-runoff
models on the basis of data alone, as well as in
combination with conceptual models (i.e taking
advantage of knowledge about the problem domain).",
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notes = "2021 journal called Hydrology Research",
- }
Genetic Programming entries for
Vladan Babovic
Maarten Keijzer
Citations