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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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An Algorithm for Optimizing a Nonlinear System, Based on the Behavior of the Hamiltonian on the Optimal Trajectory

P. 359–364.
Anna P. Presnova, Valery N. Afanas’ev, Artem N. Burtsev
Language: English
Full text
DOI
Text on another site
Keywords: suboptimal controlHamiltonianсубоптимальное управлениеSDC-modelГамильтониан

In book

7th IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control LHMNC 2021. Berlin, Germany, 11-13 October 2021
7th IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control LHMNC 2021. Berlin, Germany, 11-13 October 2021
Vol. 54. Issue 19. , Elsevier, 2021.
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