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Characterizing Time Series Data Diversity for Wind Forecasting: Preprint
Brian Hodge
,
Cong Feng
, Jie Zhang
Power Systems Engineering
The University of Texas at Dallas
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Dive into the research topics of 'Characterizing Time Series Data Diversity for Wind Forecasting: Preprint'. Together they form a unique fingerprint.
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Computer Science
Data Diversity
100%
Principal Components
100%
Time Series Data
100%
forecasting accuracy
50%
Data Dimension
50%
Convex Polygon
50%
Geometric Distribution
50%
Component Analysis
50%
Engineering
Data Series
100%
Principal Components
100%
Wind Power
50%
Component Analysis
50%
Power Grid
50%
Forecaster
50%
Test Dataset
50%
Dimensional Convex Polytope
50%
Mathematics
Time Series Data
100%
Forecasting Model
50%
Polygon
50%
Polytope
50%
Power Grid
50%
Principal Components
50%
Forecaster
50%
Geometric Distribution
50%
Principal Component Analysis
50%