Extruder Modelling: A Comparison of two Paradigms

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

@InProceedings{mckay:1996:exmc2p,
  author =       "Ben McKay and Barry Lennox and Mark Willis and 
                 Geoffrey W. Barton and Gary Montague",
  title =        "Extruder Modelling: A Comparison of two Paradigms",
  booktitle =    "UKACC International Connference on Control'96",
  year =         "1996",
  volume =       "2",
  pages =        "734--739",
  address =      "Exeter, UK",
  publisher_address = "Savoy House, London, UK",
  month =        "2-5 " # sep,
  publisher =    "IEE",
  note =         "Conference publication No. 427",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-85296-668-7",
  URL =          "http://scitation.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=IEECPS0019960CP427000734000001&idtype=cvips&prog=normal",
  DOI =          "doi:10.1049/cp:19960643",
  URL =          "http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=656018",
  size =         "6 pages",
  abstract =     "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 =        "see also tech report \cite{mckay:1996:cmc2p}",
}

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

Citations