caa a22 4500 475834143 CHVBK 20180406123849.0 cr unu---uuuuu 170329e20000701xx s 000 0 eng 10.1007/s005210070020 doi (NATIONALLICENCE)springer-10.1007/s005210070020 Neural Networks for Sulphur Dioxide Ground Level Concentrations Forecasting [Elektronische Daten] [M. Andretta, A. Eleuteri, F. Fortezza, D. Manco, L. Mingozzi, R. Serra, R. Tagliaferri] In this paper we present the preliminary results on the use of neural networks to forecast SO: 2 concentration levels in the industrial area of Ravenna. Ground level concentrations of pollutants were analysed in the area of Ravenna, in particular the high levels of SO2 occurring during relatively rare episodes. These events are typically correlated with many different aspects, like complex local meteorology, topography, and industrial emissions parameters. In many cases, during these episodes, the deterministic models (e.g. Gaussian models) fail to explain the high ground level concentrations. The neural networks are trained with a Bayesian learning scheme. Springer-Verlag London Limited, 2000 Keywords:Air pollution nationallicence ARX models nationallicence Bayesian learning nationallicence Multi-layer Perceptrons nationallicence Andretta M. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut Eleuteri A. National Institute for Nuclear Physics, Complesso Universitario di Monte Sannt'Angelo, Napoli, Italy, IT aut Fortezza F. ARPA-RER, Agenzia Regionale Prevenzione e Ambiente, Regione Emilia Romagna, Ravenna, Italy, IT aut Manco D. Facoltá di Scienze Ambientali, University of Bologna, Ravenna, Italy, IT aut Mingozzi L. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut Serra R. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut Tagliaferri R. DMI, Universitá di Salerno and INFM unitá di Salerno, Baronissi, Italy, and IIASS ‘E.R. Caianello', Vietri s/m, Italy, IT aut https://doi.org/10.1007/s005210070020 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s005210070020 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Andretta M. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut NATIONALLICENCE 700 1- Eleuteri A. National Institute for Nuclear Physics, Complesso Universitario di Monte Sannt'Angelo, Napoli, Italy, IT aut NATIONALLICENCE 700 1- Fortezza F. ARPA-RER, Agenzia Regionale Prevenzione e Ambiente, Regione Emilia Romagna, Ravenna, Italy, IT aut NATIONALLICENCE 700 1- Manco D. Facoltá di Scienze Ambientali, University of Bologna, Ravenna, Italy, IT aut NATIONALLICENCE 700 1- Mingozzi L. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut NATIONALLICENCE 700 1- Serra R. Centro Ricerche Ambientali, Montecatini, Marina di Ravenna, Italy, IT aut NATIONALLICENCE 700 1- Tagliaferri R. DMI, Universitá di Salerno and INFM unitá di Salerno, Baronissi, Italy, and IIASS ‘E.R. Caianello', Vietri s/m, Italy, IT aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer