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- W2540083950 abstract "This paper introduces a new interpolation method that fills the gap in missing solar filament big data that are captured every day from numerous ground-based and space-based observatories. It proposes a new algorithm that takes two filament event instances and interpolates between them given a cadence. The method combines K-means clustering algorithm, time series shape representation, and linear interpolation to generate the missing filament polygons. This is the first research of this kind that attempts to address the problem of solar big data interpolation. We evaluate the proposed method using area, shape, and distance accuracy criteria. Finally, we outline future improvements and opportunities for solar data interpolation." @default.
- W2540083950 created "2016-11-04" @default.
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- W2540083950 date "2016-10-01" @default.
- W2540083950 modified "2023-09-28" @default.
- W2540083950 title "Filling the Gaps in Solar Big Data: Interpolation of Solar Filament Event Instances" @default.
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- W2540083950 doi "https://doi.org/10.1109/bdcloud-socialcom-sustaincom.2016.25" @default.
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