Bayesian Models Of The PM10 Atmospheric Urban Pollution
Price
Free (open access)
Transaction
Volume
47
Pages
10
Published
2001
Size
939 kb
Paper DOI
10.2495/AIR010141
Copyright
WIT Press
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
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