Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction
Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction
Author(s): Mirza Pašić, Izet Bijelonja , Edin Kadric, Hadis BajricSubject(s): ICT Information and Communications Technologies
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: meteorological parameters; neural network; air pollutant concentration; meteorological parameters;
Summary/Abstract: 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.
Journal: TEM Journal
- Issue Year: 9/2020
- Issue No: 3
- Page Range: 852-861
- Page Count: 10
- Language: English
