2014 NovelGeospatialInterpolationAna

• (Wang & Xiong, 2014) ⇒ Bingsheng Wang, and Jinjun Xiong. (2014). “Novel Geospatial Interpolation Analytics for General Meteorological Measurements.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623367

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222014%22+Novel+Geospatial+Interpolation+Analytics+for+General+Meteorological+Measurements
• http://dl.acm.org/citation.cfm?id=2623330.2623367&preflayout=flat#citedby

Quotes

Author Keywords

• Analytics; bayesian inference; data mining; geospatial interpolation; meteorological measurements; signal processing; smart grid

Abstract

This paper addresses geospatial interpolation for meteorological measurements in which we estimate the values of climatic metrics at unsampled sites with existing observations. Providing climatological and meteorological conditions covering a large region is potentially useful in many applications, such as smart grid. However, existing research works on interpolation either cause a large number of complex calculations or are lack of high accuracy. We propose a Bayesian compressed sensing based non-parametric statistical model to efficiently perform the spatial interpolation task. Student-t priors are employed to model the sparsity of unknown signals' coefficients, and the Approximated Variational Inference (AVI) method is provided for effective and fast learning. The presented model has been deployed at IBM, targeting for aiding the intelligent management of smart grid. The evaluations on two real world datasets demonstrate that our algorithm achieves state-of-the-art performance in both effectiveness and efficiency.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 NovelGeospatialInterpolationAna	Bingsheng Wang Jinjun Xiong			Novel Geospatial Interpolation Analytics for General Meteorological Measurements				10.1145/2623330.2623367		2014