Spectral Analysis via Supervised Genetic Search with Application-specific Mutations

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Janet Taylor and Jem J. Rowland and Douglas B. Kell",
  title =        "Spectral Analysis via Supervised Genetic Search with
                 Application-specific Mutations",
  booktitle =    "Proceedings of the 2001 Congress on Evolutionary
                 Computation CEC2001",
  year =         "2001",
  pages =        "481--486",
  address =      "COEX, World Trade Center, 159 Samseong-dong,
                 Gangnam-gu, Seoul, Korea",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "27-30 " # may,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming,
                 biotechnology, supervised, spectroscopy, calibration,
                 IR analytical spectra interpretation, adaptive
                 averaging, application-specific mutations, chemical
                 constituent concentration, complex biological sample,
                 explanatory, expression optimisation, optical spectra,
                 output expression, quasi-continuous properties,
                 selective optimisation, signal-to-noise ratio, spectral
                 analysis, spectral regions, spectral resolution,
                 supervised genetic search, biology computing, genetic
                 algorithms, infrared spectra, learning (artificial
                 intelligence), spectrochemical analysis, spectroscopy
  ISBN =         "0-7803-6658-1",
  DOI =          "doi:10.1109/CEC.2001.934430",
  abstract =     "We present a method in which a genetic algorithm is
                 used to optimise an expression in order to provide a
                 supervised method for interpretation of the infrared
                 analytical spectra of complex biological samples. The
                 aim is to produce a model that can predict the value of
                 a measurand of interest, such as the concentration of a
                 particular chemical constituent, from a complex
                 infrared spectrum of biological material. The method we
                 describe is in some ways analogous to genetic
                 programming but it more readily allows the output
                 expression to be constrained in complexity and permits
                 its general form to be specified by the user, thereby
                 enhancing its explanatory ability. The quasi-continuous
                 properties of optical spectra are exploited by
                 mutations that explore spectral regions adjacent to
                 selected variables, and provide adaptive averaging of
                 spectral regions so as to provide selective
                 optimisation of the tradeoff between spectral
                 resolution and signal-to-noise ratio",
  notes =        "CEC-2001 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 IEEE Catalog Number = 01TH8546C,

                 Library of Congress Number =

                 Hybrid GA-GP? High throughput screening. Fourier
                 transform. E. Coli. Hill climbing. Exponent not useful?
                 Discusses comparison with authors' previous GP

Genetic Programming entries for Janet Taylor Jem J Rowland Douglas B Kell