Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: Application to geophysical prospecting

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@Article{Valdes2007498,
  author =       "Julio J. Valdes and Alan J. Barton",
  title =        "Multi-objective evolutionary optimization for
                 constructing neural networks for virtual reality visual
                 data mining: Application to geophysical prospecting",
  journal =      "Neural Networks",
  volume =       "20",
  number =       "4",
  pages =        "498--508",
  year =         "2007",
  note =         "Computational Intelligence in Earth and Environmental
                 Sciences",
  ISSN =         "0893-6080",
  DOI =          "DOI:10.1016/j.neunet.2007.04.009",
  URL =          "http://www.sciencedirect.com/science/article/B6T08-4NMWR88-4/2/e4bffc079293e68dbe63509d3cfa17cc",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, Visual data mining, Virtual
                 reality, Multi-objective optimization, Neural networks,
                 Geophysical prospecting",
  abstract =     "A method for the construction of virtual reality
                 spaces for visual data mining using multi-objective
                 optimization with genetic algorithms on nonlinear
                 discriminant (NDA) neural networks is presented. Two
                 neural network layers (the output and the last hidden)
                 are used for the construction of simultaneous solutions
                 for: (i) a supervised classification of data patterns
                 and (ii) an unsupervised similarity structure
                 preservation between the original data matrix and its
                 image in the new space. A set of spaces are constructed
                 from selected solutions along the Pareto front. This
                 strategy represents a conceptual improvement over
                 spaces computed by single-objective optimization. In
                 addition, genetic programming (in particular gene
                 expression programming) is used for finding analytic
                 representations of the complex mappings generating the
                 spaces (a composition of NDA and orthogonal principal
                 components). The presented approach is domain
                 independent and is illustrated via application to the
                 geophysical prospecting of caves.",
}

Genetic Programming entries for Julio J Valdes Alan J Barton

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