Modeling of PM10 emission with genetic programming

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@Article{Kovacic:2012:MT,
  author =       "Miha Kovacic and Sandra Sencic",
  title =        "Modeling of PM10 emission with genetic programming",
  journal =      "Materials and technology",
  journal_serbo_croat = "Materiali in tehnologije",
  year =         "2012",
  volume =       "46",
  number =       "5",
  pages =        "453--457",
  month =        sep # "-" # oct,
  keywords =     "genetic algorithms, genetic programming, steel plant,
                 PM10 concentrations, pollution, environment, modelling,
                 rainfall",
  ISSN =         "1580-2949",
  URL =          "http://mit.imt.si/Revija/izvodi/mit125/kovacic.pdf",
  URL =          "http://mit.imt.si/Revija/izvodi/mit125/kovacic.htm",
  size =         "5 pages",
  abstract =     "To implement sound air-quality policies, regulatory
                 agencies require tools to evaluate the outcomes and
                 costs associated with various emission-reduction
                 strategies. However, 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 modelling carried close to a
                 steel production area with the genetic programming
                 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 good agreement with measured
                 daily PM10 concentrations. In future we will carry out
                 genetic programming based dispersion modelling
                 according to the calculated wind field, air
                 temperature, humidity and rainfall in a 3D Cartesian
                 coordinate system. The prospects for arriving at a
                 robust and faster alternative to the well-known
                 Lagrangian and Gaussian dispersion models are
                 optimistic.",
  abstract_si =  "V okviru uveljavljanja uredb o kvaliteti zraka, s
                 ciljem zmanjsevanja emisij, nadzorne agencije zahtevajo
                 ovrednotenje emisij in stroskov, povezanih z njimi.
                 Uporabnost takih orodij je v splosnem negotova. Prav
                 tako je znano, da pri modelih tipa vir-sprejemnik tezko
                 uporabimo deterministicno modeliranje. V clanku je
                 predstavljen poskus modeliranja emisije delcev PM10 na
                 podrocju zelezarne z metodo genetskega programiranja.
                 Osnova za modeliranje so bili podatki, zbrani v obdobju
                 vec kot pol leta (od 23. 6. 2010 do 12. 12. 2010):
                 dnevne koncentracije PM10, produktivnost jeklarne,
                 valjarne, meteoroloski podatki (hitrost in smer vetra,
                 temperatura zraka - urno povprecje ter padavine -
                 dnevno povprecje) ter dan v tednu in zaporedna stevilka
                 meseca. Rezultati modeliranja dnevnih koncentracij PM10
                 z genetskim programiranjem kazejo na dobro ujemanje z
                 eksperimentalnimi podatki. V prihodnosti bomo izvedli
                 modeliranje z genetskim programiranjem v kartezijskem
                 3D koordinatnem sistemu z upostevanjem izracunanega
                 vetrovnega polja, temperature zraka, vlaznosti in
                 padavin. Moznosti za uporabo robustnih in hitrejsih
                 alternativ Lagrangovih in Gaussovih disperzijskih
                 modelov so optimisticne.

                 Kljucne besede: zelezarna, koncentracije PM10,
                 modeliranje, genetsko programiranje",
  notes =        "In English. MTAEC9 UDK 669:519.61/.64:351.777.6
                 http://mit.imt.si/Revija/",
}

Genetic Programming entries for Miha Kovacic Sandra Sencic

Citations