@InProceedings{NunesARTCSTC:2012:FrAnDa,
               author = "Nunes, Santiago A. and Avila, Ana M. H. and Romani, Luciana A. S. 
                         and Traina, Agma J. M. and Coltri, Priscila P. and Sousa, Elaine 
                         P. M. and Traina, Caetano and Chou, Sin C.",
          affiliation = "University of S{\~a}o Paulo, Brazil and University of Campinas, 
                         Brazil and Embrapa Agriculture Informatics, Brazil and University 
                         of S{\~a}o Paulo, Brazil and University of Campinas, Brazil and 
                         University of S{\~a}o Paulo, Brazil and University of S{\~a}o 
                         Paulo, Brazil and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "To be or not to be real: Fractal analysis of data streams from a 
                         regional climate change model",
            booktitle = "Proceedings...",
                 year = "2012",
                pages = "831--832",
         organization = "ACM Symposium on Applied Computing, 27. (SIGAPP).",
            publisher = "ACM Special Interest Group on Applied Computing (SIGAPP)",
              address = "New York",
             keywords = "Climate change - Data communication systems - Fractals.",
             abstract = "This paper proposes a new analysis process aimed at discriminating 
                         the temporal behavior of the data generated by climate models from 
                         the real climate observations gathered from ground-based 
                         meteorological stations. Our approach combines fractal data 
                         analysis and the monitoring of the real and the model-generated 
                         data streams to detect deviations considering the intrinsic 
                         correlation among climate time series. Experimental studies showed 
                         that our approach can discriminate the data either as real or as 
                         generated by a model. Those results suggest that there are yet 
                         space to improve the climate change models, and that the 
                         fractal-based concepts may contribute in this improvement.",
  conference-location = "Trento",
      conference-year = "26-30 Mar. 2012",
                  doi = "10.1145/2245276.2245438",
                  url = "http://dx.doi.org/10.1145/2245276.2245438",
                 isbn = "{13: 9781450308571}",
             language = "en",
           targetfile = "p831-nunes.pdf",
        urlaccessdate = "16 jun. 2024"
}