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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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?

Self-adaptive Intelligent System for Mass Evaluation of Real Estate Market in Cities

P. 81–87.
Alexeev A., Alexeeva I., Yasnitsky L.

This article is devoted to the method of creating an intelligent neural
network system. Unlike existing similar systems, the proposed system does not
require frequent updates, because it is able to adapt itself to the constantly
changing state of the economy and to the peculiarities of a particular region.
Besides, the proposed system allows performing scenario forecasting of regional
real estate markets depending on virtually changing economic parameters such
as the dollar rate, the market price of oil, gross domestic product and gross
regional product, the volume of housing construction in the region, the
parameters of the state’s credit policy, etc.

Language: English
Full text
DOI
Text on another site
Keywords: оценка недвижимостиreal estate marketискусственная нейронная сеть scenario forecastingсценарное прогнозирование экономикиartificial neural network

In book

Advances in Intelligent Systems and Computing
Vol. 850: Digital Science. , Switzerland: Springer, 2019.
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