The method of optimal resource management of a distributed dynamic system based on the algorithm of zeroing neural networks : доклад, тезисы доклада | Научно-инновационный портал СФУ

The method of optimal resource management of a distributed dynamic system based on the algorithm of zeroing neural networks : доклад, тезисы доклада

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

Конференция: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-II-2023); Krasnoyarsk; Krasnoyarsk

Год издания: 2024

Идентификатор DOI: 10.1051/itmconf/20245901003

Аннотация: The method of optimal resource management of a distributed dynamic system based on the algorithm of zeroing neural networks offers a new approach to effective resource management in distributed dynamic systems using advanced machine learning technologies. Research questions concern determining optimal resource management strategies in a distributed dynamic system, as well as evaluating the effectiveness of the proposed method in various scenarios. The research methods include mathematical formalization of the problem, development of an algorithm for zeroing neural networks and conducting numerical experiments based on computer modeling. The results of the study demonstrate the high efficiency of the proposed method of optimal resource management in a distributed dynamic system. The conclusions emphasize the importance of using the algorithm of zeroing neural networks in the context of optimal resource management in distributed systems and the possibility of its application to solve practical problems in various fields, such as energy, production, transport and others.

Ссылки на полный текст

Издание

Журнал: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-II-2023)

Номера страниц: 1003

Место издания: Krasnoyarsk

Персоны

  • Bryukhanova Evgenia (Siberian Federal University)

Вхождение в базы данных

Информация о публикациях загружается с сайта службы поддержки публикационной активности СФУ. Сообщите, если заметили неточности.

Вы можете отметить интересные фрагменты текста, которые будут доступны по уникальной ссылке в адресной строке браузера.