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ISSN 1822-427X print
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"The Baltic Journal of Road and Bridge Engineering"
Vilnius: Technika, 2017, Vol XII, No 1, p. 57-63


Mario De Luca, Daiva Žilionienė, Saulius Gadeikis, Gianluca Dell’Acqua

Traffic pollution assessment using artificial neural network and multivariate analysis

DOI: 10.3846/bjrbe.2017.07
 
The work addressed a study on pollution caused by traffic on the highway. In particular, it was considered the concentration of pollutant, resulting from the passage of vehicles on the freeway. Five different stations (sensors and samples) used to collect data. The data collection period around six months. Also, the following parameters were detected: wind speed and direction, temperature and traffic flow rate. Data processed with Multivariate Analysis and Artificial Neural Network approach. The best model it obtained with Artificial Neural Network approach. In fact, this model presented the best fit to the experimental data.
 
Keywords: Artificial Neural Network, concentration of pollutant, Multivariate Analysis, traffic flow rate, wind speed and direction, temperature.

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