Modeling of Dissolved Oxygen Using Genetic Programming Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "S. Vanitha and C. Sivapragasam and 
                 N. V. N. Nampoothiri",
  title =        "Modeling of Dissolved Oxygen Using Genetic Programming
  booktitle =    "International Conference on Theoretical Computer
                 Science and Discrete Mathematics",
  year =         "2016",
  editor =       "S. Arumugam and Jay Bagga and Lowell W. Beineke and 
                 B. S. Panda",
  volume =       "10398",
  series =       "Lecture Notes in Computer Science",
  pages =        "445--452",
  address =      "Krishnankoil, India",
  month =        "19-21 " # dec,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, dissolved
                 oxygen, mathematical modelling",
  bibsource =    "DBLP,
  isbn13 =       "978-3-319-64419-6",
  DOI =          "doi:10.1007/978-3-319-64419-6_56",
  size =         "8 pages",
  abstract =     "Genetic Programming (GP) based modelling is suggested
                 for modelling the variation of Dissolved Oxygen (DO)
                 under controlled conditions in the presence and absence
                 of toxicant. The results indicated that GP is able to
                 evolve robust physically meaningful models even with
                 small dataset by selecting the most relevant functions
                 from the set of functions given for the modelling. It
                 is interesting to note that the evolved models clearly
                 reflect the underlying non-linearity of the process
                 distinctly for both the case studies.",
  notes =        "Vanitha Sankararajan

                 Also known as \cite{conf/ictcsdm/VanithaSN16}",

Genetic Programming entries for Sankararajan Vanitha C Sivapragasam N V N Nampoothiri