Data mining in earth system science (DMESS 2011)
From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques-such as cluster analysis, singular value decomposition, block entropy, Fourier and wavelet analysis, phase-space reconstruction, and artificial neural networks-are being applied to problems of segmentation, feature...[Show more]
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|Source:||Block-Entropy Analysis of Climate Data|
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