Online modelling based on Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{oai:inderscience.com:12487,
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title = "Online modelling based on Genetic Programming",
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author = "Stephan Winkler and Hajrudin Efendic and
Luigi {Del Re} and Michael Affenzeller and Stefan Wagner",
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journal = "International Journal of Intelligent Systems
Technologies and Applications",
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year = "2007",
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volume = "2",
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number = "2/3",
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pages = "255--270",
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month = "19 " # feb,
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publisher = "Inderscience Publishers",
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ISSN = "1740-8873",
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bibsource = "OAI-PMH server at www.inderscience.com",
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language = "eng",
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oai = "oai:inderscience.com:12487",
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relation = "ISSN online: 1740-8873 ISSN print: 1740-8865 DOI:
10.1504/07.12487",
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rights = "Inderscience Copyright",
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source = "IJISTA (2007), Vol 2 Issue 2/3, pp 255 - 270",
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keywords = "genetic algorithms, genetic programming, GP, data
driven model identification, self-adaption, machine
learning, online modelling, fault diagnosis, automatic
learning, real time",
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URL = "http://www.inderscience.com/link.php?id=12487",
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DOI = "doi:10.1504/IJISTA.2007.012487",
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abstract = "Genetic Programming (GP), a heuristic optimisation
technique based on the theory of Genetic Algorithms
(GAs), is a method successfully used to identify
non-linear model structures by analysing a system's
measured signals. Mostly, it is used as an offline tool
that means that structural analysis is done after
collecting all available identification data. In this
paper, we propose an enhanced on-line GP approach that
is able to adapt its behaviour to new observations
while the GP process is executed. Furthermore, an
approach using GP for online Fault Diagnosis (FD) is
described, and finally test results using measurement
data of NOx (nitrogen oxide, nitrogen dioxide)
emissions of a BMW diesel engine are discussed.",
- }
Genetic Programming entries for
Stephan M Winkler
Hajrudin Efendic
Luigi del Re
Michael Affenzeller
Stefan Wagner
Citations