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News
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.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Моделирование и стабилизация нерегулярного механизма ценообразования на сети локальных рынков

Дифференциальные уравнения и процессы управления. 2023. № 4. С. 53–66.
Alexeeva T., Кузнецов Н. В., Мокаев Т. Н., Посудин К. М.

The accuracy of forecasting the expected values of economic indicators under conditions of irregular dynamics has a key role in taking optimal management decision-making. This current and complex task can be effectively solved using modern methods based on artificial intelligence, the wide introduction of which into the economy is aimed at by the Federal project "Artificial Intelligence". We show the effectiveness of combining artificial intelligence and classical methods of mathematical control to detect irregular dynamics in the pricing mechanism and stabilize the revealed irregular mode through a small control action using a pricing model in the market of short-term goods as an example.

Research target: Mathematics Economics and Management
Language: Russian
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Keywords: искусственный интеллектхаосchaosнелинейная динамикаnonlinear dynamicspricing modelмодель ценообразованияunstable periodic orbitHenon mapОтображение Энонестабильная периодическая орбита deep machine learning artificial intelligenceглубокое машинное обучение
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