Computer supported knowledge discovery - A case study in flow resistance induced by vegetation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{babovic:1999:cskd-veg,
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author = "Vladan Babovic and Maarten Keijzer",
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title = "Computer supported knowledge discovery - A case study
in flow resistance induced by vegetation",
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booktitle = "Proceedings of the XXVIII Congress of International
Association for Hydraulic Research",
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year = "1999",
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address = "Graz, Austria",
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month = "22-27 " # aug,
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keywords = "genetic algorithms, genetic programming",
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URL = "http://www.iahr.org/membersonly/grazproceedings99/pdf/C021.pdf",
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size = "7 pages",
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abstract = "Data Mining and Knowledge Discovery aims at providing
tools to facilitate the conversion of data to a better
understanding of processes that generated or produced
those data. We call this the mining of data for
knowledge. Data mining extracts patterns from data. It
creates models from data, by using for example, genetic
programming, polynomial or artificial neural networks,
or even support vector machines. These new models,
combined with the understanding of the physical
processes - the theory - can result in an improved
understanding and novel formulations of physical laws
and an improved predictive capability.
The present paper describes some of the very first
efforts under the D2K (Data to Knowledge) Research
Project currently conducted at Danish Hydraulic
Institute with a support from the Danish Technical
Research Council (STVF). The paper firstly outlines
elementary data mining principles, particularly when
applied to analysis of scientific data. In the second
half of the contribution, results obtained through
analysis of the data related to the additional
resistance to the flow induced by flexible vegetation
are presented. The data are analysed by the means of
genetic programming (GP). Induced formulations and
discussed in terms of accuracy and physical
interpretability.",
- }
Genetic Programming entries for
Vladan Babovic
Maarten Keijzer
Citations