Fractal-based analysis to identify trend changes in multiple climate time series.

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dc.contributorSANTIAGO AUGUSTO NUNES, ICMC/USP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; ANA M. H. AVILA, Cepagri/Unicamp; CAETANO TRAINA JUNIOR, ICMC/USP; ELAINE P. M. DE SOUSA, ICMC/USP; AGMA J. M. TRAINA, ICMC/USP.
dc.creatorNUNES, S. A.
dc.creatorROMANI, L. A. S.
dc.creatorAVILA, A. M. H.
dc.creatorTRAINA JUNIOR, C.
dc.creatorSOUSA, E. P. M. de
dc.creatorTRAINA, A. J. M.
dc.date2011-08-19T11:11:11Z
dc.date2011-08-19T11:11:11Z
dc.date2011-08-19T11:11:11Z
dc.date2011-08-19T11:11:11Z
dc.date2011-08-19
dc.date2011
dc.date2012-01-06T11:11:11Z
dc.date.accessioned2026-07-07T04:12:47Z
dc.descriptionAbstract. 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.
dc.identifierJournal of Information and Data Management, Belo Horizonte, v. 2, n. 1, p. 51-57, Feb. 2011.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/898365
dc.identifier.urihttp://hdl.handle.net/123456789/454271
dc.languageeng
dc.rightsopenAccess
dc.subjectDados climáticos
dc.subjectSéries temporais
dc.subjectMineração de dados
dc.subjectClusterização
dc.subjectMeteorology and climatology
dc.subjectClimate
dc.subjectCluster analysis
dc.subjectTime series analysis
dc.titleFractal-based analysis to identify trend changes in multiple climate time series.
dc.typeArtigo de periódico

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