Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{Rodriguez:2011:intech, 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