A neural-network approach to radon short-range forecasting from concentration time series

The relevance of particulate radon progeny measurements for an estimation of the mixing height was recently established. Here, an attempt at a short-range forecast of radon concentration is presented using a neural-network model applied at a 2-hour based time series. This forecasting activity leads to useful predictions of the mixing height during stability conditions.