Título:	Identification of freight patterns via association rules: the case of agricultural grains.
Autoria:	MOREIRA, C. E. S. OLIVEIRA, A. L. R. de OLIVEIRA, S. R. de M. YAMAKAMI, A.
Afiliação:	CARLOS EDUARDO SOUZA MOREIRA, Unicamp; ANDRÉA LEDA RAMOS DE OLIVEIRA, Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; AKEBO YAMAKAMI, Unicamp.
Ano de publicação:	2017
Referência:	Bulgarian Journal of Agricultural Science, v. 23, n. 6, p. 887-893, 2017.
Conteúdo:	The 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.
Thesagro:	Agronegócio Logística Transporte
NAL Thesaurus:	Agribusiness
Palavras-chave:	Mineração de dados Data mining
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPTIA)