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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3J9MAD8
Repositorysid.inpe.br/mtc-m21b/2015/04.06.16.40
Last Update2015:04.06.16.41.18 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2015/04.06.16.40.56
Metadata Last Update2018:06.04.02.55.19 (UTC) administrator
DOI10.5923/s.ajee.201501.13
ISSN2166-4633
2166-465X
Citation KeyRuivoCampOlivRamo:2015:AnExPr
TitleAnalysis of Extreme Precipitation Events Using a Novel Data Mining Approach
Year2015
Access Date2024, May 16
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size810 KiB
2. Context
Author1 Ruivo, Heloisa Musetti
2 Campos Velho, Haroldo Fraga de
3 Oliveira, Gilvan Sampaio de
4 Ramos, Fernando Manuel
Resume Identifier1
2 8JMKD3MGP5W/3C9JHC3
3 8JMKD3MGP5W/3C9JHBE
4 8JMKD3MGP5W/3C9JH4A
Group1 LAC-CTE-INPE-MCTI-GOV-BR
2 LAC-CTE-INPE-MCTI-GOV-BR
3 CST-CST-INPE-MCTI-GOV-BR
4 LAC-CTE-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 heloisa.ruivo@lac.inpe.br
2 haroldo@lac.inpe.br
3 gilvan.sampaio@cptec.inpe.br
4 fernando@lac.inpe.br
JournalAmerican Journal of Environmental Engineering
Volume5
Number1A
Pages96-105
Secondary MarkB3_GEOCIÊNCIAS B3_ENGENHARIAS_II B4_ENGENHARIAS_III
History (UTC)2015-04-06 16:40:56 :: simone -> administrator ::
2018-06-04 02:55:19 :: administrator -> simone :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsExtreme event
Drought
Intense rainfall
KDD (Knowledge Discovery in Databases)
Data mining
Classification
Decision tree
AbstractAn innovative data mining approach is presented and applied to investigate the climatic causes of extreme climatic events. Our approach comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity of the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the extreme events. The first step applies a class comparison technique. The second step consists of a decision tree learning algorithm used as a predictive model to map the set of statistically most significant climate variables identified in the previous step to classes of precipitation intensity. The methodology is employed to the study the climatic causes of two extreme events occurred in Brazil the last decade: the Santa Catarina 2008 extreme rainfall tragedy and the Amazon droughts of 2005 and 2010. In both cases, our results are in good agreement with analyses published in the literature.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Analysis of Extreme...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > COCST > Analysis of Extreme...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 06/04/2015 13:40 1.0 KiB 
4. Conditions of access and use
data URLhttp://mtc-m21b.sid.inpe.br/ibi/8JMKD3MGP3W34P/3J9MAD8
zipped data URLhttp://mtc-m21b.sid.inpe.br/zip/8JMKD3MGP3W34P/3J9MAD8
Languageen
Target Fileruivo_analysis.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Linking8JMKD3MGP7W/3DHME8E
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3F3T29H
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.40 3
sid.inpe.br/mtc-m21/2012/07.13.14.49.24 2
sid.inpe.br/bibdigital/2013/09.22.23.14 2
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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