Modelling the Daily Concentration of Airborne Particles Using 1D Convolutional Neural Networks - Ivan Gudelj; Mario Lovrić; Emmanuel Karlo Nyarko (Engineering Proceedings)
This paper focuses on improving the prediction of the daily concentration of the pollutants, PM10 and nitrogen oxides (NO, NO2) in the air at urban monitoring sites using 1D convolutional neural networks (CNN). The results show that the 1D CNN model outperforms the other machine learning models (LSTM and Random Forest) in terms of the coefficients of determination and absolute errors.