@InProceedings{PeñaAndeRochArag:2015:NoAlCl,
author = "Peña, Lorena Gayarre and Anderson, Liana Oighenstein and Rocha,
Guilherme Concei{\c{c}}{\~a}o and Arag{\~a}o, Luiz Eduardo
Oliveira e Cruz de",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and {}
and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Novo algoritmo de classifica{\c{c}}{\~a}o autom{\'a}tica de
dados multidimensionais para identifica{\c{c}}{\~a}o de
comportamentos, limiares de decis{\~a}o e outliers com potencial
utiliza{\c{c}}{\~a}o para dados de sensores remotos",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "5248--5255",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "A scientific research starts with a data processing. This process
can be divided in three steps which, depending on their
characteristics can be applied in a sequential fashion: 1)
Outliers research (data that can be considered erroneous), 2)
Behaviour identification, and 3) Behaviour threshold definition.
Most of the times, the success of a research depends on an
adequate accomplishment of the three steps mentioned above,
defining accurate thresholds which provide confiability and
decreases errors. Many times, this work is carried out by using
the manual trial and error methodology until the optimal
thresholds are found. Usually, these thresholds must be adjusted,
and this process may be repeated many times in case one wants to
apply the results to another dataset. This study proposes a new
multi-dimensional data automatic classification algorithm which
can be used in an exploratory analysis. This algorithm provides a
data characterization, pointing out outliers, determining
decisions thresholds and identifying data behaviours using less
time than the required to do it via the trial and error
methodology. In this research, the algorithm is applied to three
remote sensing study cases, demonstrating both time and human
resources economy and validating the results.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "1035",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM4DPQ",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4DPQ",
targetfile = "p1035.pdf",
type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
urlaccessdate = "28 abr. 2024"
}