General Method Of Multivariate Non-Linear Regression Based On Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{trivino:2012:IJBAS-IJENS,
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author = "Jorge Eduardo {Ortiz Trivino} and
Mauro {Florez Calderon}",
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title = "General Method Of Multivariate Non-Linear Regression
Based On Genetic Programming",
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journal = "International Journal of Basic and Applied Sciences",
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year = "2012",
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volume = "12",
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number = "3",
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month = "10 " # jun,
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ISSN = "2077-1223",
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keywords = "genetic algorithms, genetic programming, Model, non
linear function, structure",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.418.6751",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
-
URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.418.6751",
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URL = "https://www.ijens.org/IJBASVol12Issue03.html",
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URL = "http://www.ijens.org/Vol_12_I_03/121803-6464-IJBAS-IJENS.pdf",
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size = "12 pages",
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abstract = "In this paper we show the method phi to estimate the
structure and parameters of a non-linear function of
real value phi from a data set {(x1, x2,..., xj,...,
xn,; y1)}i=m i=n taken from that function. The
technique phi is based in the Holland's genetic
algorithm, this employ the genetic operations of
selection, crossover and mutation. But unlike this, the
individuals are dynamic structures called trees,
allowing its size can grow without restrictions and
these ones can become a better representation of the
desired response. The experimentation shows that the
method is efficient for both linear and nonlinear
functions as well as for multivaried cases",
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notes = "Universidad Nacional de Colombia",
- }
Genetic Programming entries for
Jorge Eduardo Ortiz Trivino
Mauro Florez Calderon
Citations