Extruder Modelling: A Comparison of two Paradigms

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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