Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: Siberian Scientific Workshop on Data Analysis Technologies with Applications, SibDATA 2021

Год издания: 2021

Ключевые слова: aluminum production, anode effects, detection of disruptions, ensemble algorithms

Аннотация: The article considers the approaches for automatically detecting process disruptions known as anode effects in aluminum electrolysis. The suggested method of their identification is based on using ensemble algorithms which are applied to data from immediate and daily average monitoring of reduction cells. The method includes the stПоказать полностьюage of preprocessing of daily-average inputs, aggregation of immediate and daily average parameters, and construction of a math model. The study determines the most informative parameters, while analyzing how algorithms and approaches featuring ensembles of decision trees stack up against each other. The quality metrics reveal the most effective algorithm for the set task. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Журнал: CEUR Workshop Proceedings

Выпуск журнала: Vol. 3047

Номера страниц: 79-85

ISSN журнала: 16130073

Издатель: CEUR-WS

• Mikhalev A. (Siberian Federal University, 26, Kirenskogo st., Krasnoyarsk, 660074, Russian Federation)
• Lugovaya N. (Siberian Federal University, 26, Kirenskogo st., Krasnoyarsk, 660074, Russian Federation)
• Penkova T. (Institute of Computational Modelling, The Siberian Branch, The Russian Academy of Sciences, 50/44 Akademgorodok, Krasnoyarsk, 660036, Russian Federation)
• Puzanov I. (RUSAL Engineering and Technology Center, 37/1 Pogranichnikov st., Krasnoyarsk, 660111, Russian Federation)
• Zavadyak A. (RUSAL Engineering and Technology Center, 37/1 Pogranichnikov st., Krasnoyarsk, 660111, Russian Federation)

• Scopus
• Ядро РИНЦ (eLIBRARY.RU)