Artificial neural networks to prediction fuel rate in the blast furnace operation

Autor: Carvalho, Leonard de Araújo, Assis, Paulo Santos
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Repositório Institucional da UFOP
Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
Popis: 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.
Databáze: OpenAIRE