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FLAIRS
2007

Mining Sequences in Distributed Sensors Data for Energy Production

10 years 28 days ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is concerned with sequence mining on power generation data and has the intent of modeling power generation. The data streams analyzed are average hourly power generation that is reported to the EPA. A global statistical model is proven impractical for the data streams, and local modeling via sequence mining is performed. The methodology presented, Uniform Sequence Discovery, implements the idea of uniform population coding, stream mining, and cross-stream mining. 1671 streams from years 2002 through 2004 are coded, mined for sequences, and cross-mined for matching sequences. 486 and 270 frequent sequences were extracted from the learning and testing data respectively. Association rules and the accompanying confidence and support values are used to create local models for power generation prediction. 159 local models ...
Mehmed M. Kantardzic, John Gant
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where FLAIRS
Authors Mehmed M. Kantardzic, John Gant
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