Tecnologia em Metalurgia, Materiais e Mineração
Tecnologia em Metalurgia, Materiais e Mineração
ABM Week 2018



Gabriela Araújo Gois, Leonard Carvalho, Moacir Andretti, Paulo dos Santos Assis

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Este artigo propõe o uso de redes neurais artificiais para a previsão do consumo total de combustível no alto-forno. Para tanto, foi considerado um conjunto de dados contendo 270 registros, com 19 variáveis de entrada, com base nos dados históricos médios de operação de um alto-forno no período de janeiro/2016 a junho/2017, e verificou-se que o modelo apresentou bons resultados com coeficiente de correlação de 0,837, rmse de 11,8 (treino) e 12.7 (teste). O modelo final apresenta uma camada de entrada com 19 neurônios, camada intermediária com 19 neurônios e camada de saída com 1 neurônio.


Redes neurais artificiais; Consumo de combustível; Alto-forno.


This paper proposes the use of artificial neural networks for the prediction of fuel rate in the blast furnace. For this purpose, a dataset of 270 records, with 19 input variables were considered, based on the historical mean data of operation from the jan/2016 to jun/2017 of a blast furnace, and it was verified that model presented good results with correlation coefficient of 0.837 and rmse of 11.8 (train) and 12.7 (test). The model consisting of an input layer with 19 neurons, intermediate layer with 19 neurons and output layer with 1 neuron.


Artificial neural networks; Fuel rate; Blast furnace.


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