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Title: Prediction of Hail Suppression Program Seeding Parameters using Data Mining Techniques
Authors: Tsagalidis, Evangelos
Evangelidis, Georgios
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Issue Date: 2006
First Page: 322
Last Page: 329
Volume Title: Proceedings of the 1st International Scientific Conference, eRA: The Contribution of Information Technology to Science, Economy, Society and Education, Tripolis, Greece
Abstract: In this study we examine the existence of interesting patterns among the Greek National Hail Suppression Program (GNHSP) data using Data Mining techniques. Two groups of GNHSP data are used. The hailstorms data, containing the values of some hailstorm attributes, such as type, life time, intensity, size, motion and the seeding data, containing the values of some seeding parameters, such as seeding time duration, seeding material mass consumption and mean seeding rate. The results we obtain in the form of association rules can contribute to the prediction of seeding parameters from storm data and the determination of hailstorm characteristics from seeding data.
Appears in Collections:Department of Applied Informatics

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