Traffic Pollution Assessment Using Artificial Neural Network and Multivariate Analysis

Authors

  • Mario De Luca Dept of Civil, Construction and Environmental Engineering, University of Naples Federico II, Via Claudio 21, I–80125 Naples, Italy
  • Daiva Žilionienė Dept of Roads, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT–10223 Vilnius, Lithuania
  • Saulius Gadeikis Dept of Hydrogeology and Engineering Geology, Vilnius University, M.K.Čiurlionio g. 21/27, LT–03101 Vilnius, Lithuania
  • Gianluca Dell’Acqua Dept of Civil, Construction and Environmental Engineering, University of Naples Federico II, Via Claudio 21, I–80125 Naples, Italy

DOI:

https://doi.org/10.3846/bjrbe.2017.07

Keywords:

Artificial Neural Network, concentration of pollutant, Multivariate Analysis, traffic flow rate, wind speed and direction, temperature.

Abstract

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.

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Published

27.03.2017

How to Cite

Luca, M. D., Žilionienė, D., Gadeikis, S., & Dell’Acqua, G. (2017). Traffic Pollution Assessment Using Artificial Neural Network and Multivariate Analysis. The Baltic Journal of Road and Bridge Engineering, 12(1), 57–63. https://doi.org/10.3846/bjrbe.2017.07