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Advanced Data Integration and Data Mining for Enviromental Scenarios

Authors: Ladislav Hluchý; Peter Krammer; Ondrej Habala; Martin Seleng; Viet D. Tran;

Advanced Data Integration and Data Mining for Enviromental Scenarios

Abstract

The use of data mining techniques in environmental applications of IT, and specifically in hydro-meteorological predictions, is not a new topic. In this paper however we present the novel use of data mining in the ADMIRE Project and its scenarios. In Orava scenario we try to predict the change of water level and water temperature in the OravaRiver below the Orava reservoir, and how they react to discharge from the reservoir. In second scenario - Radar, we are predicting rainfall in short term. The last scenario - SVP, is modeling situation of melting snow and caused inflow into reservoir.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Top 10%
Average
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