A Matlab Genetic Programming Approach to Topographic Mesh Surface Generation

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Katya Rodriguez V. and Rosalva Mendoza R.",
  title =        "A Matlab Genetic Programming Approach to Topographic
                 Mesh Surface Generation",
  booktitle =    "Engineering Education and Research Using MATLAB",
  publisher =    "INTECH Open Access Publisher",
  year =         "2011",
  editor =       "Ali H. Assi",
  chapter =      "18",
  month =        oct # "~10",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-953-307-656-0",
  URL =          "http://www.intechopen.com/articles/show/title/a-matlab-genetic-programming-approach-to-topographic-mesh-surface-generation",
  URL =          "http://www.intechopen.com/download/pdf/pdfs_id/21403",
  URL =          "http://www.intechopen.com/books/engineering-education-and-research-using-matlab",
  DOI =          "doi:10.5772/22376",
  size =         "16 pages",
  language =     "eng",
  oai =          "oai:intechopen.com:21403",
  bibsource =    "OAI-PMH server at www.intechopen.com",
  abstract =     "The problem of surface approximation by means of soft
                 mathematical functions is a relevant topic in
                 Hydrology. The generation of these functions allows
                 solving implicitly some of the most important
                 calculation in order to predict the behaviour of the
                 hydrological basin. Thus, this work proposes the use of
                 an Evolutionary Algorithm (EA) (Baeck, 1996) to
                 generate 3-D mesh surface from a set of topographic
                 data. In literature, there are only few existing works
                 about the use of Evolutionary Algorithms (EAs) applied
                 to the reconstruction of topographic surfaces, most of
                 them are based on Genetic Algorithms (GAs) (Holland,
                 1975; Goldberg, 1989) as an approximation polynomial
                 parameter estimator. Thus, this paper introduces a
                 Genetic Programming (GP) approach whose aim is to
                 obtain a mathematical function that allows a compact
                 representation of the surface of the topographic
                 information. This surface generation problem is then
                 formulated as symbolic regression. The use of EAs,
                 specifically GP (Koza, 1990; Banzhaf et al., 1998),
                 constitute a promise alternative for the traditional
                 interpolation techniques that employ approximation
                 polynomials, due to GP integrates in a natural way the
                 common non-linearities present in complex interpolation
                 problems. This proposal is then applied to a set of
                 topographic data corresponding to the Mezcalapa River
                 zone, which is the local name of the Grijalva River
                 located at the southeast of the Mexican Republic and it
                 is one of the most important rivers due to its flow and
                 generation of electric energy.

                 The GP algorithm is programmed in MATLAB and the
                 results produced by means of this GP approach give
                 indication of a significant improvement in terms of the
                 quality of the approximation in relation to the results
                 obtained by means of approximation polynomials method
                 applied to this region. In the following section a
                 brief review of some works on mathematical modelling
                 applied to Civil and Hydraulic Engineering are
                 detailed. After that, description of genetic
                 programming algorithm and its implementation in MATLAB
                 are presented. The application of this evolutionary
                 method to evolve mathematical models in order to
                 construct topographic surface is presented. Finally
                 results and conclusions are drawn.",
  notes =        "Published: October 10, 2011 under CC BY 3.0 license",

Genetic Programming entries for Katya Rodriguez-Vazquez Rosalva Mendoza Ramrez