General Method Of Multivariate Non-Linear Regression Based On Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{trivino:2012:IJBAS-IJENS,

• author = "Jorge Eduardo {Ortiz Trivino} and Mauro {Florez Calderon}",
• title = "General Method Of Multivariate Non-Linear Regression Based On Genetic Programming",
• journal = "International Journal of Basic and Applied Sciences",
• year = "2012",
• volume = "12",
• number = "3",
• month = "10 " # jun,
• ISSN = "2077-1223",
• keywords = "genetic algorithms, genetic programming, Model, non linear function, structure",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.418.6751",
• 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",
• URL = "https://www.ijens.org/IJBASVol12Issue03.html",
• URL = "http://www.ijens.org/Vol_12_I_03/121803-6464-IJBAS-IJENS.pdf",
• size = "12 pages",
• 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",
• notes = "Universidad Nacional de Colombia",

}

Genetic Programming entries for Jorge Eduardo Ortiz Trivino Mauro Florez Calderon

Citations