Traffic Pollution Assessment Using Artificial Neural Network and Multivariate Analysis

Autor:	Mario De Luca, Daiva Žilionienė, Saulius Gadeikis, Gianluca Dell’Acqua
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	artificial neural network concentration of pollutant multivariate analysis traffic flow rate wind speed and direction temperature. Highway engineering. Roads and pavements TE1-450 Bridge engineering TG1-470
Zdroj:	The Baltic Journal of Road and Bridge Engineering, Vol 12, Iss 1 (2017)
Druh dokumentu:	article
ISSN:	1822-427X 1822-4288
DOI:	10.3846/bjrbe.2017.07
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/868e33e035f64403b31e853a0a1aa1b4 Zobrazit plný text záznamu View record in DOAJ