Abstract
Diffusion Maps is a new powerful technique for dimensionality reduction that can capture geometric structure while taking into account data distribution. In this work we will apply it to time and spatial compression of numerical weather forecasts, showing how it is capable to greatly reduce the initial dimension while still capturing relevant information in the original data.
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Fernández, Á., González, A.M., Díaz, J., Dorronsoro, J.R. (2012). Diffusion Maps for the Description of Meteorological Data. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_25
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DOI: https://doi.org/10.1007/978-3-642-28942-2_25
Publisher Name: Springer, Berlin, Heidelberg
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