Natural gas prediction in Slovenian industry using genetic programming - case studies

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@InProceedings{155-kovacic,
  author =       "Miha Kovacic and Bozidar Sarler and Franjo Dolenc",
  title =        "Natural gas prediction in Slovenian industry using
                 genetic programming - case studies",
  booktitle =    "8th International Scientific Conference Management of
                 Technology Step to Sustainable Production",
  year =         "2016",
  editor =       "Predrag Cosic",
  pages =        "155--kovacic.pdf",
  address =      "Porec, Istria, Croatia",
  month =        jun # " 1-3",
  publisher =    "Croatian Association for PLM",
  keywords =     "genetic algorithms, genetic programming, natural gas
                 consumption prediction, chemical processing,
                 modelling",
  URL =          "http://motsp2016.org/",
  URL =          "http://cobiss.izum.si/scripts/cobiss?command=DISPLAY&lani=en&base=COBIB&RID=4384251",
  ISSN =         "1849-7586",
  size =         "6 pages",
  abstract =     "In accordance with Energy Agency of the Republic of
                 Slovenia regulations, each natural gas supplier
                 regulates and determines the charges for the
                 differences between the ordered (predicted) and the
                 actually supplied quantities of natural gas. Yearly
                 charges for these differences represent up to 2percent
                 of supplied natural gas costs. All the natural gas
                 users, especially industry, have huge problems finding
                 the proper method for efficient natural gas consumption
                 prediction and consequently, decreasing of mentioned
                 costs. In this paper the prediction of the natural gas
                 consumption in Štore Steel ltd. (steel plant) and
                 Cinkarna ltd. (chemical processing plant) is presented.
                 Based on production data several models for natural gas
                 consumption have been developed using genetic
                 programming method. The developed approach is extremely
                 practical.",
  notes =        "MOTSP-2016 COBISS.SI-ID 4384251",
}

Genetic Programming entries for Miha Kovacic Bozidar Sarler Franjo Dolenc

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