Development of Elements of an Intelligent High-Performance Platform of a Distributed Decision Support System for Monitoring and Diagnostics of Technological Objects | Научно-инновационный портал СФУ

Development of Elements of an Intelligent High-Performance Platform of a Distributed Decision Support System for Monitoring and Diagnostics of Technological Objects

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

Конференция: 9th Computer Science On-line Conference, CSOC 2020

Год издания: 2020

Идентификатор DOI: 10.1007/978-3-030-51971-1_50

Ключевые слова: decision support system, diagnostics, intelligent platform, monitoring, technological objects

Аннотация: In the article the architecture of the intelligent high-performance platform of a distributed decision support system for monitoring and diagnostics of technological objects is developed. The proposed architecture will ensure the implementation of the concept of an integrated cyber-physical system to ensure the safety and sustainability of production in terms of operation of technological equipment. In general version, building a system using such an architecture, on the one hand, ensures openness in the formation of the analytical core of the decision support system, which will ensure a high level of system adequacy in the conditions of production transformation, increasing the intensity of information exchange and the volume of data being analyzed. The approaches based on the methods of automatic construction of artificial neural networks ensemble-distributed solvers (classifiers) are examined. It can be used to create analytical support for decision support systems and their automated initialization in a specific production environment. #CSOC1120. © 2020, Springer Nature Switzerland AG.

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Издание

Журнал: Advances in Intelligent Systems and Computing

Выпуск журнала: Vol. 1225 AISC

Номера страниц: 614-626

ISSN журнала: 21945357

Издатель: Springer

Авторы

  • Bukhtoyarov V. (Siberian Federal University, Krasnoyarsk, Russian Federation, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation)
  • Tynchenko V. (Siberian Federal University, Krasnoyarsk, Russian Federation, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation)
  • Petrovsky E. (Siberian Federal University, Krasnoyarsk, Russian Federation)
  • Bashmur K. (Siberian Federal University, Krasnoyarsk, Russian Federation)
  • Sergienko R. (Ulm University, Ulm, Germany)

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