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  • Формирование однородных групп обучающихся методом кластерного анализа с целью повышения эффективности процесса обучения
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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
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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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Формирование однородных групп обучающихся методом кластерного анализа с целью повышения эффективности процесса обучения

Гл. 8. С. 49–77.
Sizykh D., Sizykh N.

The actual issue is formation of fairly even groups of students in order to increase the effectiveness of teaching for the qualitative development of educational material. Currently, there is a large selection of tools for multivariate data analysis, diverse and sufficiently accessible for use by educator users. However, the description of methods for understanding the process of multidimensional classification (grouping), currently available, is relatively difficult for teachers without mathematical training. Therefore, the purpose of this work is to present a description of the process of multivariate classification, which is quite understandable from a methodological point of view, in particular, the methodology of cluster analysis.

Language: Russian
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Keywords: процесс обученияeducational processlectouring methodology эффективность преподаваниягруппа обучающихсяeducational group

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Вопросы образования и психологии
Вопросы образования и психологии
Чебоксары: ИД «Среда», 2022.
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