Сибирский федеральный университет

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

Конференция: Siberian Scientific Workshop on Data Analysis Technologies with Applications, SibDATA 2020; Krasnoyarsk; Krasnoyarsk

Год издания: 2020

Ключевые слова: aluminum production, cluster analysis, multidimensional data analysis, Prevention of Technological Disorders, Principal Component analysis

Аннотация: This paper presents a comprehensive analysis of the technological parameters of aluminum production for three test sites by applying data mining techniques. Based on the principal component analysis and cluster analysis, structural features of the multidimensional monitoring data space were investigated, regularities in the aluminum production complex operation in its basic operating modes were detected, and typical conditions leading to technological disorders were determined. New knowledge and "analytical portraits"of the operation of an aluminum production complex can be used to develop algorithms for the prevention of technological disorders.

Журнал: CEUR Workshop Proceedings

Выпуск журнала: 2727

Номера страниц: 128-136

• Penkova T. (Institute of Computational Modeling of the Siberian Branch,Russian Academy of Sciences)
• Senashova M. (Institute of Computational Modeling of the Siberian Branch,Russian Academy of Sciences)
• Korobko A. (Institute of Computational Modeling of the Siberian Branch,Russian Academy of Sciences)

• Ядро РИНЦ (eLIBRARY.RU)