Non-linear Principal Components Analysis Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @TechReport{hiden:1996:npcaGP,
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author = "H. G. Hiden and M. J. Willis and P. Turner and
M. T. Tham and G. A. Montague",
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title = "Non-linear Principal Components Analysis Using Genetic
Programming",
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institution = "Chemical Engineering, Newcastle University",
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year = "1996",
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address = "UK",
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note = "Extended Abstract, ICANNGA '97, Norwich, UK",
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keywords = "genetic algorithms, genetic programming",
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broken = "http://lorien.ncl.ac.uk/sorg/paper9a.ps",
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abstract = "The recent explosion of low-cost computing power and
information storage has brought with it a corresponding
mushrooming in the amount of data on almost any subject
conceivable that is available. The philosophy that you
cant have enough information seems to have been applied
to every situation with great enthusiasm. By adopting
such an approach, much useful data can be gathered,
however it is all too frequently swamped by irrelevant
information. The distinction must be made between
useful information and information for the sake of
having it. The chemical industry also has not been
immune to the data collection bug. The equipment
required to collect, process and store data is more
affordable than ever, a fact which the designers of
chemical processes are beginning to exploit.
Unfortunately, this data is not particularly useful on
its own. It is very easy to collect data, but difficult
to analyse it productively. It is this situation that
has spawned a wide variety of data analysis tools, the
objective of which is to determine underlying
relationships and structures within large data sets.",
-
notes = "MSword postscript not compatible with unix.
",
- }
Genetic Programming entries for
Hugo Hiden
Mark J Willis
Paul Turner
Ming T Tham
Gary A Montague
Citations