Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/1209
Title: | Extraction of the Convective Day Category Index Using Data Mining Techniques |
Authors: | Tsagalidis, Evangelos Karamitopoulos, Leonidas Evangelidis, Georgios Dervos, Dimitris A. |
Type: | Conference Paper |
Subjects: | FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | hail suppression program convective day category index data mining classification decision trees |
Issue Date: | 2005 |
First Page: | 692 |
Last Page: | 698 |
Volume Title: | 2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications |
Abstract: | One of the tasks of the Hellenic Hail Suppression Program is the determination of the observed convective day category (CDC) index. This process is accomplished by having the meteorologists analyze the operational data manually. To automate and speed up this procedure we have developed an application in the CLIPS Expert System environment that calculates the observed CDC index. In this paper we examine the appropriate data mining techniques that could be used to extract this index from operational data automatically. |
URI: | https://doi.org/10.1109/IDAACS.2005.283074 https://ruomo.lib.uom.gr/handle/7000/1209 |
ISBN: | 0-7803-9446-1 0-7803-9445-3 |
Other Identifiers: | 10.1109/IDAACS.2005.283074 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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2005_idaacs.pdf | 462,04 kB | Adobe PDF | View/Open |
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