Modeling of PM10 emission with genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Kovacic:2012:MT,
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author = "Miha Kovacic and Sandra Sencic",
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title = "Modeling of PM10 emission with genetic programming",
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journal = "Materials and technology",
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journal_serbo_croat = "Materiali in tehnologije",
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year = "2012",
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volume = "46",
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number = "5",
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pages = "453--457",
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month = sep # "-" # oct,
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keywords = "genetic algorithms, genetic programming, steel plant,
PM10 concentrations, pollution, environment, modelling,
rainfall",
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ISSN = "1580-2949",
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URL = "http://mit.imt.si/Revija/izvodi/mit125/kovacic.pdf",
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URL = "http://mit.imt.si/Revija/izvodi/mit125/kovacic.htm",
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size = "5 pages",
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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.",
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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",
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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