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  • ИНТЕЛЛЕКТУАЛЬНЫЕ МЕТОДЫ ОБРАБОТКИ ДАННЫХ ПРИ ПРОГНОЗИРОВАНИИ ОБОРОТА НАЛИЧНЫХ ДЕНЕЖНЫХ СРЕДСТВ В БАНКОМАТАХ КОММЕРЧЕСКИХ БАНКОВ
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News
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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?

ИНТЕЛЛЕКТУАЛЬНЫЕ МЕТОДЫ ОБРАБОТКИ ДАННЫХ ПРИ ПРОГНОЗИРОВАНИИ ОБОРОТА НАЛИЧНЫХ ДЕНЕЖНЫХ СРЕДСТВ В БАНКОМАТАХ КОММЕРЧЕСКИХ БАНКОВ

Научные труды Вольного экономического общества России. 2019. Т. 218. № 4. С. 481–488.
Астраханцева И. А., Кутузова А. С., Astrakhantsev R.

The Article is focused on a problem of forecasting demand for cash money in ATMs of a commercial Bank. The solution of the forecasting problem let us optimize the processes of liquidity management, cash management and ATM service by the collection service. The method of machine learning - neural network-is used to obtain the forecast of cash turnover. The authors made and trained a model of a multilayer perceptron with one hidden layer in the Python 3 programming language using the Keras library, as well as a model of a recurrent neural network. As a result, the forecast of peaks and declines in demand for cash at the Bank's ATMs was obtained. Based on the forecast load management of ATMs ensures minimal maintenance costs and keep money in the ATM. The algorithm can be replicated to the entire ATM network, as well as applied to another commercial banks.

Research target: Economics and Management Mathematics
Priority areas: economics mathematics
Language: Russian
Keywords: банкиликвидностьмашинное обучениепрогнозированиебанкоматынейросетьперцептронРекуррентная нейронная сетьинкассацияспрос на наличность
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The stability of formal concepts and its generalization as robustness are considered in the paper. We use an approximation of stability in the form of Δ-measure for fast calculations. A computationally efficient method for calculating robustness based on subcontexts is presented. We also present a new method to analytically evaluate the number of preimages for ...
Added: October 14, 2026
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Varieties of regional innovation systems around the world and catch-up by latecomers
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Added: October 10, 2026
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Added: October 9, 2026
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Added: October 8, 2026
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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI 2026)
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Subsidy Effects on Productivity and Technical Efficiency of Corporate Dairy Farms in the Russian Federation
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