@INPROCEEDINGS { Rsds1904,
author = {Suraj, Zbigniew and Rzasa, Wojciech}, 
title = {Volumetric storm cell classification with the use of rough set methods}, 
booktitle = {Proceedings of the Sixth International Conference on Soft Computing and Distributed Processing}, 
conference = {International Conference on Soft Computing and Distributed Processing}, 
pages = {67--69}, 
publisher = {Wydawnictwo Wyzszej Szkoly Informatyki i Zarzadzania}, 
address = {Rzeszow, Poland}, 
month = {June 24-25}, 
year = 2002, 
editor = {Suraj, Zbigniew}, 
abstract = {Meteorological volumetric radar data are used to detect thunderstorms that are responsible for nearly all severe summer weather. The classification of storm cells is a difficult problem due to their complex evolution, the high dimensionality of the weather data, and the imprecision and incompleteness of the data. In this paper, the cross-validation method based on the rough set approach [9] is used to classify different types of storm events. Several classification strategies and preprocessing techniques are tested to facilitate the discrimination between four or ten types of storm events. The volumetric storm cell data come from the Radar Decision Support System (RDSS) database of Environment Canada [16].}, 
keywords = {rough sets, cross-validation, data mining, knowledge discovery in databases, pattern recognition, }, 
}