A Methodology for Combining Symbolic Regression and Design of Experiments to Improve Empirical Model Building
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Castillo:2003:gecco,
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author = "Flor Castillo and Kenric Marshall and James Green and
Arthur Kordon",
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title = "A Methodology for Combining Symbolic Regression and
Design of Experiments to Improve Empirical Model
Building",
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booktitle = "Genetic and Evolutionary Computation -- GECCO-2003",
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editor = "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and
D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and
R. Standish and G. Kendall and S. Wilson and
M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and
A. C. Schultz and K. Dowsland and N. Jonoska and
J. Miller",
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year = "2003",
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pages = "1975--1985",
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address = "Chicago",
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publisher_address = "Berlin",
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month = "12-16 " # jul,
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volume = "2724",
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series = "LNCS",
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ISBN = "3-540-40603-4",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming, symbolic
regression, design of experiments, Real World
Applications",
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DOI = "doi:10.1007/3-540-45110-2_96",
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abstract = "A novel methodology for empirical model building using
GP-generated symbolic regression in combination with
statistical design of experiments as well as undesigned
data is proposed. The main advantage of this
methodology is the maximum data usage when
extrapolation is necessary. The methodology offers
alternative non-linear models that can either linearize
the response in the presence of Lack or Fit or
challenge and confirm the results from the linear
regression in a cost effective and time efficient
fashion. The economic benefit is the reduced number of
additional experiments in the presence of Lack of
Fit.",
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notes = "GECCO-2003. A joint meeting of the twelfth
International Conference on Genetic Algorithms
(ICGA-2003) and the eights Annual Genetic Programming
Conference (GP-2003)",
- }
Genetic Programming entries for
Flor A Castillo
Kenric A Marshall
James Green
Arthur K Kordon
Citations