Artificial Intelligence Approach of Modeling of PM10 Emission close to a Steel Plant
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- @InProceedings{Kovacic:2013:QUALITY,
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author = "Miha Kovacic and Sandra Sencic and Uros Zuperl",
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title = "Artificial Intelligence Approach of Modeling of {PM10}
Emission close to a Steel Plant",
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booktitle = "8th Research/Expert Conference with International
Participations, QUALITY 2013",
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year = "2013",
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editor = "Safet Brdarevic and Sabahudin Jasarevic",
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pages = "305--310",
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address = "Neum, Bosnia and Herzegovina",
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month = "06-08 " # jun,
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organisation = "University of Zenica and Erlangen University and
Quality Association of Bosnia and Herzegovina",
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keywords = "genetic algorithms, genetic programming, Steel plant,
PM10 concentrations, modeling, genetic programming",
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URL = "http://www.quality.unze.ba/zbornici/QUALITY%202013/050-Q13-013.pdf",
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size = "6 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. 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
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.",
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notes = "http://quality.unze.ba/e/final.phps Kvalitet 2013
COBISS.SI-ID 2933499 jasarevic@mf.unze.ba;
sabahudinjasarevic@yahoo.com; sbrdarevic@mf.unze.ba
ASOCIJACIJA ZA KVALITET U BOSNI I HERCEGOVINI",
- }
Genetic Programming entries for
Miha Kovacic
Sandra Sencic
Uros Zuperl
Citations