Title :
Prediction of significant meteorological phenomena using advanced data mining and integration methods
Author :
Ladislav Hluchý;Ondrej Habala;Juraj Bartok;Peter Bednár;Martin Gažák
Author_Institution :
Institute of Informatics of the Slovak Academy of Sciences, Dú
Abstract :
We present the design, goals, and current state of the project Data Mining Meteo1which is aimed towards using new data integration and data mining techniques in prediction of several meteorological phenomena, whose prediction is so far difficult, yet very useful for planning and coordinated, for example in traffic management. The paper focuses on the description of the meteorological prediction scenarios, and how the data mining and integration technologies are used to make them feasible in a day-to-day production environment.
Keywords :
"Data mining","Clouds","Data models","Atmospheric modeling","Predictive models","Biological system modeling","Meteorology"
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569281