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Avtomatika i Telemekhanika, 2018, Issue 8, Pages 101–110 (Mi at14759)  
This article is cited in 12 scientific papers (total in 12 papers)

Intellectual Control Systems, Data Analysis

Statistical control of defects in a continuously cast billet based on machine learning and data analysis methods

I. A. Varfolomeev, E. V. Ershov, L. N. Vinogradova

Cherepovets State University, Cherepovets, Russia
Full-text PDF (2863 kB) Citations (12)
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Abstract: We consider the problems of defects arising in the production of continuously cast billets at continuous casting plants. We propose a model for predicting slab cracks based on the random forest machine learning algorithm. We determine the main technological parameters that influence the appearance of cracks and present the results of the model.
Keywords: statistical control, continuous casting defect, continuous steel casting, cracks on the slab, hot charging, random forests, influencing parameters.
Presented by the member of Editorial Board: N. N. Bakhtadze

Received: 26.04.2017
English version:
Automation and Remote Control, 2018, Volume 79, Issue 8, Pages 1450–1457
DOI: https://doi.org/10.1134/S0005117918080076
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: I. A. Varfolomeev, E. V. Ershov, L. N. Vinogradova, “Statistical control of defects in a continuously cast billet based on machine learning and data analysis methods”, Avtomat. i Telemekh., 2018, no. 8, 101–110; Autom. Remote Control, 79:8 (2018), 1450–1457
Citation in format AMSBIB
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\pages 101--110
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  • https://www.mathnet.ru/eng/at14759
  • https://www.mathnet.ru/eng/at/y2018/i8/p101
    • This publication is cited in the following 12 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Avtomatika i Telemekhanika
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    Full-text PDF :66
    References:29
    First page:18
     
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