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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 прогнозирования платежеспособности предприятий

С. 227–230.
Bogdanova T., Мамедова С. В.

One of the most important criteria for selection of partners for the enterprise is the solvency of the entity. Insolvent Corporation does not attract any contractors or investors, as the interaction with them risk to lose their own money and resources. Although the insolvency does not always lead to bankruptcy or liquidation of the enterprise, but always serves as a signal about the adverse financial position for the company's partners. The insolvency of the enterprise can develop according to different scenarios that can be traced to the nature of the changes of financial indicators in dynamics. However, most existing prediction models solvency ignore this feature and do not take into account the retrospective dynamics data, which significantly reduces their accuracy. Therefore, the problem of forecasting of solvency taking into account dynamics of change of financial indicators is relevant.

Language: Russian
Full text
Keywords: неплатежеспособностьforecastingпрогнозированиевероятностьprobabilityфинансовое состояниеfinancial positiondynamics of changesдинамика измененияinsolvency

In book

Системное моделирование социально-экономических процессов: труды 37-ой Международной научной школы-семинара, г. Сочи, 30 сентября - 5 октября 2014 г.
Воронеж: Воронежский государственный педагогический университет, 2014.
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