Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1268
Title: Hail Size Estimation and Prediction using Data Mining Techniques
Authors: Tsagalidis, Evangelos
Tsitouridis, Kyriakos
Dervos, Dimitris A.
Evangelidis, Georgios
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Issue Date: 2008
Volume Title: Proceedings of the 5th European Conference on Radar in Meteorology and Hydrology (ERAD), Helsinki, Finland
Abstract: In this study we examine the existence of interesting patterns among the Greek National Hail Suppression Program data using Data Mining techniques. More specifically, we focus on hail size estimation and prediction from meteorological radar and sounding data. The sought objective is to examine existing relationships and, by doing so, construct a hail size prediction model. Two data mining techniques are applied in order to identify the optimum number of independent variables and, consequently, build a simple, yet effective, model. A model easily applied by the meteorologist in order to quickly interpret radar and atmospheric measurements to possible hail size on the ground.
URI: http://erad2008.fmi.fi/proceedings/extended/erad2008-0072-extended.pdf
https://ruomo.lib.uom.gr/handle/7000/1268
Appears in Collections:Department of Applied Informatics

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