Created by W.Langdon from gp-bibliography.bib Revision:1.1944
@InProceedings{mckay:1996:GPidea,
author = "Ben McKay and Mark Willis and Gary Montague and
Geoffrey W. Barton",
title = "Using Genetic Programming to Develop Inferential
Estimation Algorithms",
booktitle = "Genetic Programming 1996: Proceedings of the First
Annual Conference",
editor = "John R. Koza and David E. Goldberg and
David B. Fogel and Rick L. Riolo",
year = "1996",
month = "28--31 " # jul,
keywords = "genetic algorithms, genetic programming",
pages = "157--165",
address = "Stanford University, CA, USA",
publisher = "MIT Press",
broken = "http://lorien.ncl.ac.uk/sorg/paper2.ps",
size = "9 pages",
abstract = "Genetic Programming (GP) is used to develop
inferential estimation algorithms for two industrial
chemical processes. Within this context, dynamic
modelling procedures (as opposed to static or
steady-state modelling) are often required if accurate
inferential models are to be developed. Thus, a simple
procedure is suggested so that the GP technique may be
used for the development of dynamic process models.
Using measurements from a vacuum distillation column
and an industrial plasticating extrusion process, it is
then demonstrated how the GP methodology can be used to
develop reliable cost effective process models. A
statistical analysis procedure is used to aid in the
assessment of GP algorithm settings and to guide in the
selection of the final model structure.",
URL = "
http://cognet.mit.edu/library/books/view?isbn=0262611279",
notes = "GP-96, MSWord postscript not cmpatible with Unix",
}
Genetic Programming entries for Ben McKay Mark J Willis Gary A Montague Geoffrey W Barton