|Title:||Time Series Prediction of Air Pollutants : A Case Study for Serbia, Bosnia and Herzegovina and Italy||Journal:||18th International Symposium INFOTEH-JAHORINA, INFOTEH 2019 - Proceedings||Conference:||18th International Symposium INFOTEH-JAHORINA, INFOTEH 2019; East Sarajevo; Bosnia and Herzegovina; 20 March 2019 through 22 March 2019||Issue Date:||16-May-2019||ISBN:||978-153867073-6||DOI:||10.1109/INFOTEH.2019.8717778||Abstract:||
Pollution levels are highly dependent on the meteorological parameters, as the weather conditions dictate pollution dispersion and concentration. With the rise of global environmental protection initiatives, there is also a need for accurate prediction of pollution levels. This paper presents a time series prediction of NO2 and CO given four meteorological parameters: (i) air pressure, (ii) relative humidity, (iii) average daily temperature, and (iv) wind speed, using a Nonlinear Autoregressive Exogenous (NARX) neural network. The research is a case study of three European countries: (i) Serbia, (ii) Bosnia and Herzegovina, and (iii) Italy, and involves data from 2014 to 2016 for a total of 1096 instances. The results show that the best prediction accuracy is obtained for CO for data regarding Italy and Bosnia and Herzegovina, and for NO2 for data regarding Serbia. Moreover, the best predictor variables of NO2 are air pressure and relative humidity, followed by the wind speed. The best predictor variables of CO are pressure and temperature for Bosnia and Italy, and wind speed for Serbia.
|Keywords:||air pollution | artificial neural network | data mining | prediction | time series||Publisher:||IEEE||Project:||Development of new information and communication technologies, based on advanced mathematical methods, with applications in medicine, telecommunications, power systems, protection of national heritage and education|
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