Vol.9, No.3, August 2020.                                                                                                                                                                                ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction


Mirza Pasic, Izet Bijelonja, Edin Kadric, Hadis Bajric


© 2020 Mirza Pasic, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 3, Pages 852-861, ISSN 2217-8309, DOI: 10.18421/TEM93-03, August 2020.


Received: 07 May 2020.

Revised:   24 June 2020.
Accepted: 01 July 2020.
Published: 28 August 2020.




In this paper five neural network models were developed using NARX-SP neural network type in order to predict air pollutants concentrations (SO2, PM10, NO2, O3 and CO ) for the 72nd hour ahead for Sarajevo. Hourly values of air pollutants concentrations and meteorological parameters (air temperature, pressure and humidity, wind speed and direction) for Sarajevo were used. Optimal model was selected based on the values of R2, MSE and the complexity of models. Optimal neural network model can predict air pollutants concentrations for the 72nd hour ahead with high accuracy, as well as for all hours up to 72nd hour.


Keywords –NARX-SP, neural network, air pollutant concentration, meteorological parameters.



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