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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3A7MC6H
Repositorysid.inpe.br/mtc-m19/2011/08.04.19.19   (restricted access)
Last Update2011:12.23.16.19.50 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m19/2011/08.04.19.19.45
Metadata Last Update2021:02.12.13.48.14 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1016/j.eswa.2010.10.031
ISSN0957-4174
Citation KeyLorenaJaSiGiLoCaYa:2011:CoMaLe
TitleComparing machine learning classifiers in potential distribution modelling
Year2011
Monthmay
Access Date2024, May 04
Secondary TypePRE PI
Number of Files1
Size595 KiB
2. Context
Author1 Lorena, Ana C
2 Jacintho, Luis F. O
3 Siqueira, Marinez F.
4 De Giovanni, Renato
5 Lohmann, Lucia G.
6 Carvalho, Andre C. P. L. F. de
7 Yamamoto, Missae
Group1
2
3
4
5
6
7 DAE-CEA-INPE-MCT-BR
Affiliation1 CMCC Univ Fed ABC, Santo Andre, SP, Brazil
2 CMCC Univ Fed ABC, Santo Andre, SP, Brazil
3 CRIA, Campinas, SP, Brazil
4 CRIA, Campinas, SP, Brazil
5 Univ Sao Paulo, Inst Biociencias, Sao Paulo, Brazil
6 Univ Sao Paulo, ICMC, Sao Carlos, SP, Brazil
7 Instituto Nacional de Pesquisas Espaciais (INPE)
e-Mail Addresssecretaria.cpa@dir.inpe.br
JournalExpert Systems with Applications
Volume38
Number5
Pages5268-5275
Secondary MarkA1_ADMINISTRAÇÃO,_CIÊNCIAS_CONTÁBEIS_E_TURISMO B1_CIÊNCIA_DA_COMPUTAÇÃO A1_ENGENHARIAS_I A1_ENGENHARIAS_III A2_GEOCIÊNCIAS A1_INTERDISCIPLINAR
History (UTC)2011-08-04 19:27:59 :: secretaria.cpa@dir.inpe.br -> administrator :: 2011
2011-08-15 04:45:40 :: administrator -> secretaria.cpa@dir.inpe.br :: 2011
2011-11-01 11:45:46 :: secretaria.cpa@dir.inpe.br -> tereza@sid.inpe.br :: 2011
2011-12-23 16:20:26 :: tereza@sid.inpe.br -> administrator :: 2011
2012-10-15 02:14:45 :: administrator -> tereza@sid.inpe.br :: 2011
2013-03-08 17:14:50 :: tereza@sid.inpe.br -> administrator :: 2011
2021-02-12 13:48:14 :: administrator -> tereza@sid.inpe.br :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsEcological niche modelling
Potential distribution modelling
Machine learning. SPECIES DISTRIBUTIONS
CLIMATE-CHANGE
HABITAT SUITABILITY
PREDICTION
BIODIVERSITY
AREAS
INVASIONS
ENVELOPE
NICHES
SCALE
AbstractSpecies' potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species' potential distribution.
AreaCEA
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDAE > Comparing machine learning...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
Languageen
User Groupadministrator
secretaria.cpa@dir.inpe.br
tereza@sid.inpe.br
Visibilityshown
Archiving Policydenypublisher denyfinaldraft24
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
Next Higher Units8JMKD3MGPCW/3ETL868
DisseminationWEBSCI; PORTALCAPES; COMPENDEX.
Host Collectionsid.inpe.br/mtc-m19@80/2009/08.21.17.02
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel electronicmailaddress format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate session shorttitle sponsor subject targetfile tertiarymark tertiarytype typeofwork url
7. Description control
e-Mail (login)tereza@sid.inpe.br
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