Data-driven Real-time Short-term Prediction of Air Quality: Comparison of ES, ARIMA, and LSTM. (arXiv:2211.09814v1 [cs.LG])

Air pollution is a worldwide issue that affects the lives of many people in
urban areas. It is considered that the air pollution may lead to heart and lung
diseases. A careful and timely forecast of the air quality could help to reduce
the exposure risk for affected people. In this paper, we use a data-driven
approach to predict air quality based on historical data. We compare three
popular methods for time series prediction: Exponential Smoothing (ES),
Auto-Regressive Integrated Moving …

arima arxiv comparison data data-driven lstm prediction quality real-time