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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/155-kovacic.pdf",
• broken = "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 Store 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

Citations