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May 25, 2026
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Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
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?

Метод спектральной трикластеризации для систем совместного пользования ресурсами

С. 246–254.
Секинаева З. Р., Ignatov D. I.
Language: Russian
Full text
Keywords: data miningspectral clusteringтрикластеризацияtriclusteringАнализ сетевых (графовых) данныхсистемы совместного пользования ресурсамиразработка данныхспектральная трикластеризация

In book

Анализ изображений, сетей и текстов. Доклады всероссийской научной конференции АИСТ'12. Модели, алгоритмы и инструменты анализа данных; результаты и возможности для анализа изображений, сетей и текстов. Екатеринбург, 16 – 18 марта 2012 года
Анализ изображений, сетей и текстов. Доклады всероссийской научной конференции АИСТ'12. Модели, алгоритмы и инструменты анализа данных; результаты и возможности для анализа изображений, сетей и текстов. Екатеринбург, 16 – 18 марта 2012 года
Вып. 1. , М.: Национальный открытый университет «ИНТУИТ», 2012.
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