An Evolutionary Approach to Modeling Radial Brightness Distributions in Elliptical Galaxies

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Li:PPSN:2004a,
  author =       "Jin Li and Xin Yao and Colin Frayn and 
                 Habib G. Khosroshahi and Somak Raychaudhury",
  title =        "An Evolutionary Approach to Modeling Radial Brightness
                 Distributions in Elliptical Galaxies",
  booktitle =    "Parallel Problem Solving from Nature - PPSN VIII",
  year =         "2004",
  editor =       "Xin Yao and Edmund Burke and Jose A. Lozano and 
                 Jim Smith and Juan J. Merelo-Guerv\'os and 
                 John A. Bullinaria and Jonathan Rowe and 
                 Peter Ti\v{n}o Ata Kab\'an and Hans-Paul Schwefel",
  volume =       "3242",
  pages =        "591--601",
  series =       "LNCS",
  address =      "Birmingham, UK",
  publisher_address = "Berlin",
  month =        "18-22 " # sep,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-23092-0",
  URL =          "http://www.cs.bham.ac.uk/~xin/papers/Li_ppsn314.pdf",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=3242&spage=591",
  DOI =          "doi:10.1007/b100601",
  abstract =     "A reasonably good description of the luminosity
                 profiles of galaxies is needed as it serves as a guide
                 towards understanding the process of galaxy formation
                 and evolution. To obtain a radial brightness profile
                 model of a galaxy, the way varies both in terms of the
                 exact mathematical form of the function used and in
                 terms of the algorithm used for parameters fitting for
                 the function given. Traditionally, one builds such a
                 model by means of fitting parameters for a functional
                 form assumed beforehand. As a result, such a model
                 depends crucially on the assumed functional form. In
                 this paper we propose an approach that enables one to
                 build profile models from data directly without
                 assuming a functional form in advance by using
                 evolutionary computation. This evolutionary approach
                 consists of two major steps that serve two goals. The
                 first step applies the technique of genetic programming
                 with the aim of finding a promising functional form,
                 whereas the second step takes advantage of the power of
                 evolutionary programming with the aim of fitting
                 parameters for functional forms found at the first
                 step. The proposed evolutionary approach has been
                 applied to modelling 18 elliptical galaxies profiles
                 and its preliminary results are reported.",
  notes =        "PPSN-VIII",
}

Genetic Programming entries for Jin Li Xin Yao Colin M Frayn Habib G Khosroshahi Somak Raychaudhury

Citations