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Avtomatika i Telemekhanika, 2018, Issue 8, Pages 101–110
(Mi at14759)
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This article is cited in 11 scientific papers (total in 11 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
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.
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
Linking options:
https://www.mathnet.ru/eng/at14759 https://www.mathnet.ru/eng/at/y2018/i8/p101
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Statistics & downloads: |
Abstract page: | 310 | Full-text PDF : | 59 | References: | 24 | First page: | 18 |
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