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dc.contributor.author
Rossit, Daniel Alejandro
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Olivera, Alejandro
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Viana Céspedes, Víctor
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Broz, Diego Ricardo
dc.date.available
2021-08-03T15:53:38Z
dc.date.issued
2017
dc.identifier.citation
Application of data mining to forest operations planning; 1st International Conference on Agro Big Data and Decision Support Systems in Agriculture; Montevideo; Uruguay; 2017; 147-150
dc.identifier.isbn
978-9974-0-1514-2
dc.identifier.uri
http://hdl.handle.net/11336/137678
dc.description.abstract
In Uruguay, mechanized forestry harvesting for industrial purposes is carried out using modern equipment. They are capable of record a wealth of information that can be exploited in the decision making process and improve operations. Some approaches from data mining field, as decision trees, are an alternative to analyze large volumes of data and determine incidence factors. In this work, it was proposed to analyze how different variables of the forest harvest (DBH, species, shift and operator) affect the productivity of a forest harvester. Data were collected automatically by a forest harvester working on plantations of Eucalyptus spp. in Uruguay. The results show that DBH is the most influential factor in productivity.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Universidad de la República
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
DATA MINING
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HARVESTING
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EUCALYPTUS SPP
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Estadística y Probabilidad
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Matemáticas
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CIENCIAS NATURALES Y EXACTAS
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Matemática Aplicada
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Matemáticas
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CIENCIAS NATURALES Y EXACTAS
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Ciencias de la Computación
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Ciencias de la Computación e Información
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CIENCIAS NATURALES Y EXACTAS
dc.title
Application of data mining to forest operations planning
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/conferenceObject
dc.type
info:ar-repo/semantics/documento de conferencia
dc.date.updated
2021-06-22T13:48:55Z
dc.journal.pagination
147-150
dc.journal.pais
Uruguay
dc.journal.ciudad
Montevideo
dc.description.fil
Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
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Fil: Olivera, Alejandro. Universidad de la República; Uruguay
dc.description.fil
Fil: Viana Céspedes, Víctor. Universidad de la República; Uruguay
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Fil: Broz, Diego Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.coverage
Internacional
dc.type.subtype
Conferencia
dc.description.nombreEvento
1st International Conference on Agro Big Data and Decision Support Systems in Agriculture
dc.date.evento
2017-09-27
dc.description.ciudadEvento
Montevideo
dc.description.paisEvento
Uruguay
dc.type.publicacion
Book
dc.description.institucionOrganizadora
Universidad de la República
dc.description.institucionOrganizadora
Universitat de Lleida
dc.source.revista
Proceeding of I International Conference on Agro BigData and Decision Support Systems in Agriculture
dc.date.eventoHasta
2017-09-29
dc.type
Conferencia
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