Bayesian Models Of The PM10 Atmospheric Urban Pollution
Author(s)
M. Cossentino, F.M. Raimondi & M. C. Vitale
Abstract
Bayesian models of the PM%o atmospheric
urban pollution
M. CossentW, P.M. Raimondi^ & M.C. Vitale^
' Dipartimento di Ingegneria Elettrica, University of Palermo, Italy
* Dipartimento di Ingegneria Automatica e Informatica, University of
Palermo, Italy
Abstract
In this paper we illustrate a forecast method of atmospheric pollution critical
events caused by particulate matter (specifically PMio) based upon the application
of Bayesian networks.
These Bayesian networks model the temporal series of the pollutant during the
day and the influence that meteorological parameters have upon them.
Each network has received some data (coming from historical records or
meteorological forecasts) and used them to calculate its own forecast. Typical
inputs of the networks have been the pollutant concentration at a certain hour and
the meteorological parameters at the further hours of the day. The output
provided by the networks is the estimate of the probability of reaching a certain
pollut
Keywords
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