Data/hora: 01/06/2024 09:27:49

Provedor de dados: | 70
País: | Brazil
Título: | ESTIMATION OF FUEL CONSUMPTION IN AGRICULTURAL MECHANIZED OPERATIONS USING ARTIFICIAL NEURAL NETWORKS
Autores: | Borges,Pedro H. M.; Mendoza,Zaíra M. S. H.; Maia,João C. S.; Bianchini,Aloísio; Fernándes,Haroldo C.
Data: | 2017-02-01
Ano: | 2017
Palavras-chave: | Machine performance; Artificial intelligence; Agricultural planning.
Resumo: | ABSTRACT This study aimed to develop artificial neural networks for the estimation of tractor fuel consumption during soil preparation, according to the adopted system. The multilayer perceptron network was chosen. As input data: the soil mechanical penetration resistance, the mobilized area by implements, the working gear and the tractor engine speed. The number of layers and neurons varied to form different architectures. The adjustment was verified based on various statistical criteria. The values estimated by the networks did not differ significantly from those obtained experimentally. The conclusion was that the networks showed adequate reliability and accuracy to predicting the fuel consumption in each tillage system, in function of the input data and this can be a useful tool for planning and management of agricultural operations.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000100136
Editor: | Associação Brasileira de Engenharia Agrícola
Relação: | 10.1590/1809-4430-eng.agric.v37n1p136-147/2017
Formato: | text/html
Fonte: | Engenharia Agrícola  v.37 n.1 2017
Fonte: | info:eu-repo/semantics/openAccess