01481naa a2200277 a 450000100080000000500110000800800410001910000170006024501090007726000090018652006250019565000120082065000210083265000320085365000250088565300200091065300220093065300250095265300220097770000210099970000200102070000220104070000230106270000210108577300970110618983652012-01-06       2011    bl uuuu     u00u1 u    #d1 aNUNES, S. A.  aFractal-based analysis to identify trend changes in multiple climate time series.h[electronic resource]  c2011  aAbstract. In the last few decades, huge amounts of climate data have been gathered and stored by several institutions. The analysis of these data has become an important task due to worldwide climate changes and the consequent social and economic effects. In this work, we propose an approach to analyzing multiple climate time series in order to identify intrinsic temporal patterns and trend changes. By dealing with multiple time series as multidimensional data streams and combining fractal-based analysis with clustering, we can integrate different climate variables and discover general behavior changes over time.  aClimate  aCluster analysis  aMeteorology and climatology  aTime series analysis  aClusterização  aDados climáticos  aMineração de dados  aSéries temporais1 aROMANI, L. A. S.1 aAVILA, A. M. H.1 aTRAINA JUNIOR, C.1 aSOUSA, E. P. M. de1 aTRAINA, A. J. M.  tJournal of Information and Data Management, Belo Horizontegv. 2, n. 1, p. 51-57, Feb. 2011.