This paper presents a novel method for the system
identification of the fed-batch fermentation process
defined in the problem statement of the
Biotechnological Control Forum Modelling and Control
Competition. The identification methodology involves a
hybrid of mechanistic modelling and Genetic Programming
techniques. It provides an accurate model of the system
which should be extremely useful in both the
optimisation and control of this process. The
performance of the model as a 25 time unit ahead
predictor of product concentration (on unseen
verification data) is such that the root mean square
error between the actual and predicted output is less
than 5% over the range of interest.
%0 Report
%1 mckay:1996:ehmffp
%A McKay, B.
%A Sanderson, C.
%A Willis, M. J.
%A Barford, J.
%A Barton, G.
%C UK
%D 1996
%K algorithms, genetic programming
%T Evolving a Hybrid Model of a Fed-batch Fermentation
Process
%U http://lorien.ncl.ac.uk/sorg/paper6.ps broken
%X This paper presents a novel method for the system
identification of the fed-batch fermentation process
defined in the problem statement of the
Biotechnological Control Forum Modelling and Control
Competition. The identification methodology involves a
hybrid of mechanistic modelling and Genetic Programming
techniques. It provides an accurate model of the system
which should be extremely useful in both the
optimisation and control of this process. The
performance of the model as a 25 time unit ahead
predictor of product concentration (on unseen
verification data) is such that the root mean square
error between the actual and predicted output is less
than 5% over the range of interest.
@techreport{mckay:1996:ehmffp,
abstract = {This paper presents a novel method for the system
identification of the fed-batch fermentation process
defined in the problem statement of the
Biotechnological Control Forum Modelling and Control
Competition. The identification methodology involves a
hybrid of mechanistic modelling and Genetic Programming
techniques. It provides an accurate model of the system
which should be extremely useful in both the
optimisation and control of this process. The
performance of the model as a 25 time unit ahead
predictor of product concentration (on unseen
verification data) is such that the root mean square
error between the actual and predicted output is less
than 5% over the range of interest.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {UK},
author = {McKay, B. and Sanderson, C. and Willis, M. J. and Barford, J. and Barton, G.},
biburl = {https://www.bibsonomy.org/bibtex/2b0fae5be0cdf1564a216138ef79f415a/brazovayeye},
institution = {Chemical Engineering, Newcastle University},
interhash = {1d10b00a30c5f3e99ea5dbb99629764d},
intrahash = {b0fae5be0cdf1564a216138ef79f415a},
keywords = {algorithms, genetic programming},
notes = {MSword postscript not camptible with unix},
size = {12 pages},
timestamp = {2008-06-19T17:46:38.000+0200},
title = {Evolving a Hybrid Model of a Fed-batch Fermentation
Process},
url = {http://lorien.ncl.ac.uk/sorg/paper6.ps broken},
year = 1996
}