New product design via analysis of historical databases

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "S. Lakshminarayanan and H. Fujii and B. Grosman and 
                 E. Dassau and D. R. Lewin",
  title =        "New product design via analysis of historical
  journal =      "Computers \& Chemical Engineering",
  year =         "2000",
  volume =       "24",
  pages =        "671--676",
  number =       "2-7",
  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 =          "",
  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