Extruder Modelling: A Comparison of two Paradigms

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

@TechReport{mckay:1996:cmc2p,
  author =       "B. McKay and B. Lennox and M. J. Willis and 
                 G. W. Barton and G. A. Montague",
  title =        "Extruder Modelling: A Comparison of two Paradigms",
  institution =  "Chemical Engineering, Newcastle University",
  year =         "1996",
  address =      "UK",
  note =         "Appears in Control '96",
  keywords =     "genetic algorithms, genetic programming",
  broken =       "http://lorien.ncl.ac.uk/sorg/paper5.ps",
  abstract =     "In this contribution two data based modelling
                 paradigms are compared. Using measurements from an
                 industrial plasticating extrusion process, a locally
                 recurrent neural network and a genetic programming
                 algorithm are used to develop inferential models of the
                 polymer viscosity. It is demonstrated that both
                 techniques produce adequate non-linear dynamic
                 inferential models. However, for this application the
                 genetic programming technique adopted produces models
                 that perform better than the locally recurrent neural
                 network. Moreover, the final model produced by the
                 algorithm has a simple transparent structure.",
  notes =        "MSword postscript not compatible with unix, see also
                 \cite{mckay:1996:exmc2p}",
  size =         "6 pages",
}

Genetic Programming entries for Ben McKay Barry Lennox Mark J Willis Geoffrey W Barton Gary A Montague

Citations