Evolutionary Computing in Hydrology
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InCollection{Babovic:2010:ECinH,
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author = "Vladan Babovic and Raghuraj Rao",
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title = "Evolutionary Computing in Hydrology",
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booktitle = "Advances in Data-Based Approaches for Hydrologic
Modeling and Forecasting",
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publisher = "World Scientific Publishing Co.",
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year = "2010",
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editor = "Bellie Sivakumar and Ronny Berndtsson",
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chapter = "7",
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pages = "347--369",
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address = "Singapore",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "981-4307-97-1",
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URL = "http://ebooks.worldscinet.com/ISBN/9789814307987/9789814307987_0007.html",
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DOI = "doi:10.1142/9789814307987_0007",
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abstract = "Many hydrologic processes are believed to be highly
complex, nonlinear, time-varying, and spatially
distributed. Hence, the governing mechanisms are not
easily described by simple models. With unprecedented
growth in instrumentation technology, recent
investigations in hydrology are supported with immense
quantities of data. In order to take full advantage of
the information contained in such data, scientists are
increasingly relying on a suite of data-driven
techniques to understand the complex hydrologic
processes. Evolutionary computing (EC) techniques, with
a host of optimisation and modelling tools, can
contribute significantly to achieve the objectives of
this knowledge-discovery exercise in hydrology. This
chapter discusses the utility of these EC techniques in
attempting data analysis and modeling problems
associated with hydrologic systems. It introduces the
concept and working principle of EC techniques in
general and reviews their applications to different
domains of hydrology. The study also illustrates
different case studies of genetic programming (GP)
technique as a modelling, data assimilation, and model
emulation tool",
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notes = "http://www.worldscibooks.com/environsci/7783.html",
- }
Genetic Programming entries for
Vladan Babovic
K Rao Raghuraj
Citations