Ground Level Ozone Peak Forecast using Neural Networks and Kalman Filter

0404081 - UIVT-O 20000202 RIV SK eng J - Článek v odborném periodiku
Pelikán, Emil - Eben, Kryštof - Vondráček, Jiří - Krejčíř, Pavel - Keder, J.
Ground Level Ozone Peak Forecast using Neural Networks and Kalman Filter.
Meteorologický časopis. Roč. 3, č. 2 (2000), s. 3-8. ISSN 1335-339X
Grant ostatní: APPETISE(XE) IST-99-11764; MŽP ČR(CZ) ZZ520/2/97; MŠMT ČR(CZ) VS96008
Výzkumný záměr: AV0Z1030915
Klíčová slova: ozone forecast * neural classifications * Kalman filter * genetic algorithms * Kohonen maps * Czech Republic
Kód oboru RIV: BB - Aplikovaná statistika, operační výzkum

A forecasting system for the maximum ozone concent. for the following day based on statistical methods has been developed and tested within the framework of cooperation between the Czech Hydromet. Inst. and Inst. of Computer Science. Predictors based on neural networks and Kalman filter have been developed for urban, rural and mountain types of measurement stations.The stations were clustered with the help of Kohonen maps. Input variables were selected by statistical tests and a genetic algorithm.
Trvalý link: http://hdl.handle.net/11104/0124352