Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: Application to geophysical prospecting
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- @Article{Valdes2007498,
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author = "Julio J. Valdes and Alan J. Barton",
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title = "Multi-objective evolutionary optimization for
constructing neural networks for virtual reality visual
data mining: Application to geophysical prospecting",
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journal = "Neural Networks",
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volume = "20",
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number = "4",
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pages = "498--508",
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year = "2007",
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note = "Computational Intelligence in Earth and Environmental
Sciences",
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ISSN = "0893-6080",
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DOI = "DOI:10.1016/j.neunet.2007.04.009",
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URL = "http://www.sciencedirect.com/science/article/B6T08-4NMWR88-4/2/e4bffc079293e68dbe63509d3cfa17cc",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, Visual data mining, Virtual
reality, Multi-objective optimization, Neural networks,
Geophysical prospecting",
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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
Citations