Abstract
We present a Decision-Aided System for an early prediction (at 2:00 pm, in Universal Time) of ozone peaks for the next day. For better reliability, two tools are associated: a Kohonen Self-Organizing Map, for classification and immediate graphical visualization of the risk level, and a Fuzzy Inference System for sensor modeling. This system provides good results. Its main features are missing data management, characterization of situations just before a polluted day and prediction of the maximum value of an ozone sensor. The forecasting system can be used, using on-line learning, even in case of lack of historical data.
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