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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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Recent Advances of the Russian Operations Research Society

Cambridge : Cambridge Scholars Publishing, 2020.
Academic editor: Aleskerov F. T., Васин А. А.

This collection of articles highlights the most interesting new results from the IX Moscow International Operations Research Conference, the largest Russian meeting in this field, held every three years for leading experts. These papers will interest researchers and organizations specialized in OR, Game Theory, System Analysis, Macro- and Micro-economic Modelling, and Actuarial Mathematics. The volume may be a source for PhD and Master students in the specified areas. The proposed methods for optimal decision making will be useful for insurance and auditing companies, banks, and others.

The volume consists of three parts; the first includes game-theoretic models, the second part considers innovations and their possible opposite impact to the growth of GDP and social welfare, as well as new methods for improving reliability of banks’ credit risks, monopolistic competition under heterogeneous labor, interregional trade and different ways of developing the Russian banking system. The last part contains articles on a wide range of optimization problems and their applications.

Chapters
Chapter 10. Credit rating patterns: a financial approach for industrial companies
Dyachkova N., Karminsky A. M., , in: Recent Advances of the Russian Operations Research Society.: Cambridge: Cambridge Scholars Publishing, 2020. P. 163–177.
Interpreting and finding patterns in financial data can lead economists to make changes through the process of monitoring and planning. In the context of modern research papers, it often shows results, based on the patterns of financial indicators, which contain some insightful information. In our experience, we obtained results from the distinction of credit rating ...
Added: September 29, 2020
The Comparison of Modifications of the Russian Banking System Model with Identification, Using a Method for Solving Inverse Problems
Sagirova A., Pospelov I. G., Zhukova A., , in: Recent Advances of the Russian Operations Research Society.: Cambridge: Cambridge Scholars Publishing, 2020. P. 196–220.
The work is devoted to solving the problem of identification for two versions of the model of the Russian banking system on the available statistical data. To identify the parameters of models, the method of solving the inverse problem for a system of differential equations is used. For calculations, the Runge-Kutta method of order 4 is used, taking into account ...
Added: June 16, 2021
Increase of Banks’ Credit Risk Forecasting Power Using the Set of Credit Ratings and Probability of Default Models
Khromova E., , in: Recent Advances of the Russian Operations Research Society.: Cambridge: Cambridge Scholars Publishing, 2020. Ch. 11 P. 177–196.
Added: October 31, 2021
Priority areas: economics management state and public administration IT and mathematics business informatics mathematics
Language: English
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Keywords: operations research
Recent Advances of the Russian Operations Research Society
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