Exploring The Use Of Soft-computing And Artificial Intelligence Techniques In Atmospheric Pollution Modelling
Author(s)
M. Cossentino, A. Damiani, S. Gaglio, F.M. Raimondi & M.C. Vitale
Abstract
Exploring the use of soft-computing and
artificial intelligence techniques in atmospheric
pollution modelling
M. cossentino1, A. ~arniani', S. ~ a ~ l i o ' , F.M. ~airnondi~
& M.C. vitale2
'~stituto di Calcolo e Reti ad -4lte Prestazioni, Consiglio Nazionale delle
Ricerche, Italy
2~ipartimento di Ingegneria dell Yutomazione e dei Sistemi, University of
Palerrno, Italy
Abstract
Many different mathematical models for monitoring and controlling the
atmospheric pollution have been applied in recent years.
In this paper we illustrate a method for the forecast of atmospheric pollution
caused by particulate matter (PMlo). This model has been developed using
Bayesian networks to represent the pollutant behaviour and then the parameters
of these networks have been optimized using genetic algorithms.
We adopted this approach because the probabilistic nature of the Bayesian
models well reflects the uncertainty characterizing the atmospheric pollution
data and meteorological parameters. Several experim
Keywords
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