• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Articles
  • Application of information technologies and programming methods of embedded systems for complex intellectual analysis
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2028
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.
September 17, 2026
'I Wish That People Would Place Greater Trust in Science'
When Tatiana Eremicheva chose Fundamental and Computational Linguistics as her field of study, she thought it would be about learning languages. Instead, she discovered it was about helping people. In this interview for the HSE Young Scientists project, she discusses science as a way of understanding the world, billiards as a team-building activity, and why learning to read is not always as easy as it seems.
September 15, 2026
Immunity to Chaos: How Personal Resources Help Us Cope with the Challenges of a Turbulent World
International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Application of information technologies and programming methods of embedded systems for complex intellectual analysis

Entropy. 2021. Vol. 23. No. 1. Article 94.
Emelyanov V.
Language: English
Keywords: artifitial neural networks
Similar publications
Prediction of Industrial Cyber Attacks Using Normalizing Flows
V.P. Stepashkina, M.I. Hushchyn, Doklady Mathematics 2024 Vol. 110 No. 1 P. S95–S102
This paper presents the development and evaluation of methods for detecting cyberattacks on industrial systems using neural network approaches. The focus is on the task of detecting anomalies in multivariate time series, where the diversity and complexity of potential attack scenarios require the use of advanced models. To address these challenges, a transformer-based autoencoder architecture ...
Added: March 25, 2025
Comparison of Forecasting Power of Statistical Models for GDP Growth Under Conditions of Permanent Crises for Application in Strategic Risk Controlling
Maria Lashina, Grishunin S., , in: Procedia Computer Science: Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023)Vol. 221.: ScienceDirect, 2023. P. 442–449.
The study evaluates the effectiveness of combining different forecasting models to predict Russia's GDP growth rates for the upcoming quarter. The ensemble model utilized in this study consists of a dynamic factor model (DFM) and a neural network with long- and short-term memory (LSTM). The research compared the root-mean-squared errors (RMSE) of the ensemble model ...
Added: June 18, 2024
Оптимизация физико-информированных нейронных сетей для решения нелинейного уравнения Шредингера
Чупров И. А., Гао Ц., Efremenko D. et al., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2023 Т. 514 № 2 С. 28–38
Физико-информированные нейронные сети (Physics Informed Neural Networks – PINN) являются перспективным методом решения уравнений в частных производных с помощью машинного обучения. В работе рассмотрено применение PINN к нелинейному уравнению Шредингера для описания ...
Added: December 19, 2023
Hybrid acceleration techniques for the physics-informed neural networks: a comparative analysis
Buzaev F., Gao J., Ivan Chuprov et al., Machine Learning 2024 Vol. 113 No. 6 P. 3675 –3692
Physics-informed neural networks (PINN) has emerged as a promising approach for solving partial differential equations (PDEs). However, the training process for PINN can be computationally expensive, limiting its practical applications. To address this issue, we investigate several acceleration techniques for PINN that combine Fourier neural operators, separable PINN, and first-order PINN. We also propose novel ...
Added: December 19, 2023
Synthesis of Datasets for Neural Networks Based on Expert Knowledge
Rabchevskiy A., Ashikhmin E., Yasnitsky L., , in: Cyber-Physical Systems and Control II.: Springer, 2023. P. 535–544.
The problem of creating datasets for training and testing neural networks is described in the example of the task of social network management. A method of expert dataset synthesis based on experts’ knowledge of the subject area is proposed. The essence of the method lies in the fact that sets are generated randomly within the ...
Added: November 20, 2023
Simulation of Residential Real Estate Markets in the Largest Russian Cities
Alekseev A., Economy of Regions 2022 Vol. 18 No. 2 P. 609–622
The existing mass appraisal models and mathematical tools for predicting the market value of residential property have a number of disadvantages, as they are developed for individual regions. Without considering the constantly changing economic environment, these models quickly become outdated and require constant updating. Thus, they are not suitable for construction business optimisation. The study ...
Added: November 19, 2023
EXPERT SYSTEM SOFTWARE FOR ASSESSING THE TECHNICAL CONDITION OF CRITICAL LINED EQUIPMENT
Emelyanov V., Advances in Intelligent Systems and Computing 2020 Vol. 1115 P. 930–937
Added: February 8, 2022
The Mathematical Models of the Operation Process for Critical Production Facilities Using Advanced Technologies
Emelyanov V., Inventions 2022 Vol. 7 No. 1 Article 8
Added: February 8, 2022
Application of artificial intelligence technologies to assess the quality of structures
Emelyanov V., Energies 2021 Vol. 14 No. 23 Article 8040
Added: February 8, 2022
Journal of Physics: Conference Series, Vol. 1828
IOP Publishing, 2021.
Organized by Beijing Jiaotong University, the 2020 International Symposium on Automation, Information and Computing (ISAIC 2020) was held successfully online from December 2nd-4th, 2020. ISAIC 2020 was primarily scheduled to be held in Beijing, China from 2nd to 4th December. However, due to the COVID-19, it had to be changed to virtual model. The technical ...
Added: March 31, 2021
Методика нейросетевого прогнозирования кассовых сборов кинофильмов
Yasnitsky L., Медведева Е. Ю., Белобородова Н. О., Финансовая аналитика: проблемы и решения 2017 Т. 10 № 4 С. 449–463
Theme. Neural network forecasting in the film business. Goal. The article is devoted to application of economic-mathematical modeling in the field of film industry, in particular – to predict revenue and profit from distribution of future films, the identification of factors influencing the commercial success of the film business. Methodology. The basis of economic-mathematical model ...
Added: December 12, 2017
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit