Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/12762
Title: Application of machine learning in the control of metal melting production process
Authors: Duc̈ić N.
Jovicic A.
Manasijevic, Srecko
Radiša R.
Ćojbašić, Žarko
Savković B.
Journal: Applied Sciences (Switzerland)
Issue Date: 1-Sep-2020
Abstract: © 2020 by the authors. This paper presents the application of machine learning in the control of the metal melting process. Metal melting is a dynamic production process characterized by nonlinear relations between process parameters. In this particular case, the subject of research is the production of white cast iron. Two supervised machine learning algorithms have been applied: the neural network and the support vector regression. The goal of their application is the prediction of the amount of alloying additives in order to obtain the desired chemical composition of white cast iron. The neural network model provided better results than the support vector regression model in the training and testing phases, which qualifies it to be used in the control of the white cast iron production.
URI: https://scidar.kg.ac.rs/handle/123456789/12762
Type: Article
DOI: 10.3390/app10176048
SCOPUS: 85090199641
Appears in Collections:University Library, Kragujevac
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