Title:	Fractal-based analysis to identify trend changes in multiple climate time series.
Authors:	NUNES, S. A. ROMANI, L. A. S. AVILA, A. M. H. TRAINA JUNIOR, C. SOUSA, E. P. M. de TRAINA, A. J. M.
Affiliation:	SANTIAGO 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.
Date Issued:	2011
Citation:	Journal of Information and Data Management, Belo Horizonte, v. 2, n. 1, p. 51-57, Feb. 2011.
Description:	Abstract. 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.
NAL Thesaurus:	Meteorology and climatology Climate Cluster analysis Time series analysis
Keywords:	Dados climáticos Séries temporais Mineração de dados Clusterização
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPTIA)