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.
%0 Report
%1 mckay:1996:cmc2p
%A McKay, B.
%A Lennox, B.
%A Willis, M. J.
%A Barton, G. W.
%A Montague, G. A.
%C UK
%D 1996
%K algorithms, genetic programming
%T Extruder Modelling: A Comparison of two Paradigms
%X 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.
@techreport{mckay:1996:cmc2p,
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.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {UK},
author = {McKay, B. and Lennox, B. and Willis, M. J. and Barton, G. W. and Montague, G. A.},
biburl = {https://www.bibsonomy.org/bibtex/2f3518615a8cf305ac0fa85a57d06ec05/brazovayeye},
broken = {http://lorien.ncl.ac.uk/sorg/paper5.ps},
institution = {Chemical Engineering, Newcastle University},
interhash = {df25ce60589a0299ebc3caa7066a808b},
intrahash = {f3518615a8cf305ac0fa85a57d06ec05},
keywords = {algorithms, genetic programming},
note = {Appears in Control '96},
notes = {MSword postscript not compatible with unix, see also
\cite{mckay:1996:exmc2p}},
size = {6 pages},
timestamp = {2008-06-19T17:46:38.000+0200},
title = {Extruder Modelling: {A} Comparison of two Paradigms},
year = 1996
}