Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1086281
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dc.contributor.authorMOREIRA, C. E. S.
dc.contributor.authorOLIVEIRA, A. L. R. de
dc.contributor.authorOLIVEIRA, S. R. de M.
dc.contributor.authorYAMAKAMI, A.
dc.date.accessioned2018-01-25T23:35:46Z-
dc.date.available2018-01-25T23:35:46Z-
dc.date.created2018-01-25
dc.date.issued2017
dc.identifier.citationBulgarian Journal of Agricultural Science, v. 23, n. 6, p. 887-893, 2017.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1086281-
dc.descriptionThe road system is the main form of transport in the biggest production regions between the domestic market and exporting. ports, as well as the transport used on intermodal routes connecting production areas with rail and/or water terminals. The goal of the current study is to recognize non-obvious patterns in a mass of data for road freights of selected grain: soy and corn. As such, the data mining technique, known as the Apriori algorithm, is used to generate association rules that describe such patterns. Among the varied rules identified by this technique, we highlight those that enable us to conclude that: i. Soy and corn production in the state of Mato Grosso is carried via the port of Santos; ii. The grain storage silos located in the state of Mato Grosso mainly receive shipments from the same state; iii. The port of São Francisco do Sul, mainly receives corn; iv. In the state of Minas Gerais there is an intermodal route that receives the grain originating mostly from Mato Grosso and transfers it to the rail system, which then carries the load to its next destination.
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectMineração de dados
dc.subjectData mining
dc.titleIdentification of freight patterns via association rules: the case of agricultural grains.
dc.typeArtigo de periódico
dc.date.updated2018-01-25T23:35:46Zpt_BR
dc.subject.thesagroAgronegócio
dc.subject.thesagroLogística
dc.subject.thesagroTransportept_BR
dc.subject.nalthesaurusAgribusiness
riaa.ainfo.id1086281
riaa.ainfo.lastupdate2018-01-25
dc.contributor.institutionCARLOS EDUARDO SOUZA MOREIRA, Unicamp; ANDRÉA LEDA RAMOS DE OLIVEIRA, Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; AKEBO YAMAKAMI, Unicamp.
Aparece nas coleções:Artigo em periódico indexado (CNPTIA)

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