New product design via analysis of historical databases
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Lakshminarayanan:2000:CCE,
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author = "S. Lakshminarayanan and H. Fujii and B. Grosman and
E. Dassau and D. R. Lewin",
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title = "New product design via analysis of historical
databases",
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journal = "Computers \& Chemical Engineering",
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year = "2000",
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volume = "24",
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pages = "671--676",
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number = "2-7",
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abstract = "A methodology is presented to define a set of
operating conditions to produce a desired product,
given a database of historical operating conditions and
the product quality that they produced. This approach
relies on the generation of a reliable model that can
be used to predict the quality variables (the Y block)
from the decision variables (the X block). Genetic
programming (GP) is used to automatically generate
accurate nonlinear models relating latent vectors for
the X and Y blocks. The GP has the capability to carry
out simultaneous optimisation of model relationship
structures and parameters, as well as to identify the
most important basis functions. Once an adequate model
is generated, it is used to predict the required
process conditions to meet the new quality target by
reverse mapping.",
-
owner = "wlangdon",
-
URL = "http://www.sciencedirect.com/science/article/B6TFT-448HNR0-2P/2/eecc15ac2e7cad2e662af963aa783893",
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keywords = "genetic algorithms, genetic programming, Product
design, PLSR, PCR",
-
DOI = "doi:10.1016/S0098-1354(00)00406-3",
- }
Genetic Programming entries for
S Lakshminarayanan
H Fujii
Benyamin Grosman
Eyal Dassau
Daniel R Lewin
Citations