Genetic programming and artificial neural network modeling of PM10 emission close to a steel plant

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@Article{Kovacic:2013:RMZ,
  author =       "Miha Kovacic and Sandra Sencic and Uros Zuperl",
  title =        "Genetic programming and artificial neural network
                 modeling of {PM10} emission close to a steel plant",
  title2 =       "Modeliranje emisij PM10 ob zelezarni z genetskim
                 programiranjem in nevronskimi mrezami",
  journal =      "RMZ -- Materials and Geoenvironment",
  year =         "2013",
  volume =       "60",
  number =       "1",
  pages =        "9--16",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, steel plant,
                 PM10 concentrations, modelling, artificial neural
                 network",
  ISSN =         "1408-7073",
  URL =          "http://www.rmz-mg.com/contents.htm#Volume%2060,%20No.%201%20%28July%202013%29",
  URL =          "http://www.rmz-mg.com/letniki/rmz60/RMZ60_0009-0016.pdf",
  size =         "8 pages",
  abstract =     "To implement sound air quality policies, regulatory
                 agencies require tools to evaluate the outcomes and
                 costs associated with various emission reduction
                 strategies. The applicability of such tools can also
                 remain uncertain. It is furthermore known that
                 source-receptor models cannot be implemented through
                 deterministic modelling. The article presents an
                 attempt of PM10 emission modeling carried close to a
                 steel production area with the genetic programming and
                 artificial neural network method. The daily PM10
                 concentrations, daily rolling mill and steel plant
                 production, meteorological data (wind speed and
                 direction - hourly average, air temperature - hourly
                 average and rainfall - daily average), weekday and
                 month number were used for modelling during a
                 monitoring campaign of almost half a year (23. 6. 2010
                 to 12. 12. 2010). The genetic programming modelling
                 results show superior agreement with measured daily
                 PM10 concentrations.",
  notes =        "In english.

                 1Store Steel, d. o. o., Zelezarska cesta 3, SI-3220
                 Store, Slovenia 2Kova, d. o. o., Teharska cesta 4,
                 SI-3000 Celje, Slovenia 3University of Maribor, Faculty
                 of Mechanical Engineering, Smetanova ulica 17, SI-2000
                 Maribor, Slovenia

                 ",
}

Genetic Programming entries for Miha Kovacic Sandra Sencic Uros Zuperl

Citations