Data/hora: 10/06/2024 04:57:38

Provedor de dados: | 65
País: | Brazil
Título: | Multivariate analysis and neural networks application to price forecasting in the Brazilian agricultural market
Autores: | Pinheiro,Carlos Alberto Orge; Senna,Valter de.
Data: | 2017-01-01
Ano: | 2017
Palavras-chave: | Neural networks; Multivariate analysis; Agricultural products; Forecasting.
Resumo: | ABSTRACT: The purpose of this study is to apply the methodology proposed by PINHEIRO &amp; SENNA (2015) to a set of agricultural products traded in Brazil. The multivariate and nonlinear character of this methodology has shown to be suitable, as compared to the neural network model, since it allows for a better predictive performance. Results obtained in an out-of-sample period, by using the calculated error and statistical test, confirmed this statement. This study will be useful to farmers as price forecasting based on their tendency is relevant.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000100931
Editor: | Universidade Federal de Santa Maria
Relação: | 10.1590/0103-8478cr20160077
Formato: | text/html
Fonte: | Ciência Rural  v.47 n.1 2017
Fonte: | info:eu-repo/semantics/openAccess