In recent years, interest in artificial intelligence and the integration of Industry 4.0 technologies to improve and monitor steel production conditions has increased. Every day, several models are proposed to simulate industrial processes. In this sense, committee machines are presented as competitive alternatives to solve this task. A committee machine uses a multiple classification system in which the responses from multiple ANNs are combined into a single response. In this context, the purpose of this work was to develop committee machines using 108 independent artificial neural networks to predict the amount of impurities (silicon, phosphorus, and sulfur) in the production of cast iron in a blast furnace. It is concluded that neural networks operating in committee mode may be used in practice as a prediction and control tool due to the low RMSE values and high mathematical correlation between the database values and the values calculated by the committee machine.

A novel committee machine to predict the quantity of impurities in hot metal produced in blast furnace

Di Felice R.
2022

Abstract

In recent years, interest in artificial intelligence and the integration of Industry 4.0 technologies to improve and monitor steel production conditions has increased. Every day, several models are proposed to simulate industrial processes. In this sense, committee machines are presented as competitive alternatives to solve this task. A committee machine uses a multiple classification system in which the responses from multiple ANNs are combined into a single response. In this context, the purpose of this work was to develop committee machines using 108 independent artificial neural networks to predict the amount of impurities (silicon, phosphorus, and sulfur) in the production of cast iron in a blast furnace. It is concluded that neural networks operating in committee mode may be used in practice as a prediction and control tool due to the low RMSE values and high mathematical correlation between the database values and the values calculated by the committee machine.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1083808
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact