Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/10852
Title: Artificial neural networks to prediction fuel rate in the blast furnace operation.
Authors: Carvalho, Leonard de Araújo
Assis, Paulo Santos
Keywords: Modelling
Issue Date: 2018
Citation: CARVALHO, L. de A.; ASSIS, P. S. Artificial neural networks to prediction fuel rate in the blast furnace operation. Indian Journal of Applied Research, v. 8, p. 431-432, 2018. Disponível em: <https://wwjournals.com/index.php/ijar/article/view/5680>. Acesso em: 15 fev. 2019.
Abstract: This paper proposes the use of artificial neural networks for the prediction of fuel consumption in the blast furnace. For this purpose, a dataset of 270 records, with 19 input variables were considered, based on the historical data of operation from the years 2014 to 2017 of a blast furnace of a Brazilian steel mill, and it was verified that model presented good results with correlation coefficient of 0.837, consisting of an input layer with 19 neurons, intermediate layer with 19 neurons and output layer with 1 neuron.
URI: http://www.repositorio.ufop.br/handle/123456789/10852
ISSN: 2249555X
metadata.dc.rights.license: This work is licensed under a Creative Commons Attribution 4.0 International License. Fonte: Indian Journal of Applied Research <https://www.worldwidejournals.com/indian-journal-of-applied-research-(IJAR)/> acesso em: 18 fev. 2019.
Appears in Collections:DEMET - Artigos publicados em periódicos

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