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%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16d/2019/11.28.12.55
%2 sid.inpe.br/mtc-m16d/2019/11.28.12.55.20
%@issn 2179-4847
%A Souza, Felipe Carvalho de,
%A Santos, Rafael Duarte Coelho dos,
%A Ferreira, Karine R.,
%@electronicmailaddress felipe.carvalho@inpe.br
%@electronicmailaddress rafael.santos@inpe.br
%@electronicmailaddress karine.ferreira@inpe.br
%T GGSOM: ferramenta de visualização baseada em mapas auto-organizáveis
%B Simpósio Brasileiro de Geoinformática (GEOINFO)
%D 2019
%E Lisboa Filho, Jugurta,
%E Monteiro, Antonio Miguel Vieira,
%S Anais do 20º Simpósio Brasileiro de Geoinformática
%8 11 -13 nov. 2019
%J São José dos Campos
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%C São José dos Campos
%K geoinformatica.
%X Analysis of multidimensional and time series data is useful and pertinent to several different applications, being a challenge due to the volume and complexity of the data. A possible approach for analysis of this kind of data is to use clustering algorithms to reduce the dimensionality of the data. This paper presents a tool for clustering and visualization of data, called ggsom, which uses a technique for data dimensionality reduction through projection of the data in a smaller number of dimensions by the Kohonens Self-Organizing Map. The tool is evaluated with data from time series of vegetation coverage from Bahia state.
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%@language pt
%3 310-312.pdf


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