Using Prior Knowledge and Obtaining Process Insight in Data Based Modelling of Bioprocesses

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Article{Marenbach1998,
  author =       "Peter Marenbach",
  title =        "Using Prior Knowledge and Obtaining Process Insight in
                 Data Based Modelling of Bioprocesses",
  journal =      "System Analysis Modelling Simulation",
  year =         "1998",
  howpublished = "Overseas Publishers association",
  volume =       "31",
  pages =        "39--59",
  keywords =     "genetic algorithms, genetic programming,
                 biotechnology, bioprocesses, data based modelling,
                 SMOG",
  URL =          "http://www.rt.e-technik.tu-darmstadt.de/~mali/GP/publications.html#SAMS98",
  abstract =     "In biotechnology, as is many other fields of
                 technology, the development of a appropriate process
                 model is one of the most important engineering tasks.
                 Data driven modelling becomes an attractive approach
                 whenever analytical modelling is difficult or too time
                 consuming. Disadvantages of the often used artificial
                 neural networks are their missing transparency and the
                 difficulty to integrate prior knowledge. The paper at
                 hand gives an overview of several common modelling
                 techniques with focus on their application to
                 bioprocesses and presents a novel modelling technique
                 that uses genetic programming for the construction and
                 refinement of transparent structured models.",
  notes =        "

                 Reprints available from P. Marenbach.",
}

Genetic Programming entries for Peter Marenbach