Genetic programming and soft annealing productivity

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@InProceedings{Kovacic:2010:IMT,
  author =       "Miha Kovacic and Bozidar Sarler",
  title =        "Genetic programming and soft annealing productivity",
  booktitle =    "Program and book of abstracts of the 18th Conference
                 on Materials and Technology",
  year =         "2010",
  editor =       "Monika Jenko",
  pages =        "74",
  address =      "Portoroz, Slovenia",
  publisher =    "Institute of metals and technology",
  month =        "15-17 " # nov,
  keywords =     "genetic algorithms, genetic programming, Steel, soft
                 annealing, furnace productivity, hardness, modelling",
  isbn13 =       "978-961-92518-2-9",
  broken =       "http://www.imt.si/portoroz/index.html",
  size =         "0.25 pages",
  abstract =     "The optimal thermo-mechanical processing in steel
                 industry is difficult because of the multi-constituent
                 and multiphase character of the commercial steels,
                 variety of the possible processing paths, and plant
                 specific equipment characteristics. This paper shows
                 successful implementation of the genetic programming
                 approach for increasing the furnace conveyor speed and
                 consequently productivity of the heat treatment furnace
                 in the soft annealing process. The data (222 samples
                 covering 24 different steel grades) on a furnace
                 conveyor speed, chemical composition of steel (weight
                 percent of C, Cr, Mo, Ni and V) and Brinell hardness
                 before and after the soft annealing were collected
                 during daily production. On the basis of the monitored
                 data a mathematical model for the hardness after the
                 soft annealing was developed by genetic programming.
                 According to the modeled influences on the hardness,
                 the higher furnace conveyor speed was attempted in
                 practice. The experimental results of the hardness
                 after the soft annealing with the increased conveyor
                 speed and the predictions of the mathematical model
                 were compared within the agreement of 3.24percent. The
                 genetic model was also compared and verified with
                 linear regression model. The productivity of the soft
                 annealing process increased (from the furnace conveyor
                 speed 3.2 m/h to 7 m/h) as a consequence of the used
                 computational intelligence approach.",
  notes =        "Laboratory for Multiphase Processes, University of
                 Nova Gorica, Vipavska 13, SI-5000, Nova Gorica,
                 Slovenia",
}

Genetic Programming entries for Miha Kovacic Bozidar Sarler

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