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Аналитика данных для формирования управленческих решений в образовании
Гл. 4. С. 186–210.
Keywords: forecastingcomparative analysispredictive analyticsсопоставительный анализдинамический анализуправление, ориентированное на результатконтекстуальный анализcausal analysisdynamic analysisпрогнозная аналитикаresult-oriented managementrisk analyticscontextual analysisанализ причинно-следственных связейриск-аналитика
In book
Издательский дом «Дело» РАНХиГС, 2021.
Trubochkina N. K., М.: Юрайт, 2026.
This textbook is designed to develop students' holistic understanding of modern production processes and methods for their analysis and management using machine learning technologies. In the context of the fourth industrial revolution, where traditional engineering disciplines are inextricably intertwined with intelligent data processing methods, there is a growing need for specialists capable of integrating knowledge ...
Added: August 8, 2026
Karacharovskiy V., Ларина У. С., Резмерица А. А., Социологические исследования 2026 № 7 С. 60–75
Based on the neural network approach, the decomposition of the index of social mood in Russia for the period 2004-2024 was carried out and their dynamics for this period was modeled. The following issues are discussed: (a) the nature of the social mood' shocks in Russia, based on their connection with the concepts of politics ...
Added: May 14, 2026
Belov A. V., Irina V. Arutyunova, , in: Proceedings of the 2025 INTERNATIONAL CONFERENCE "QUALITY MANAGEMENT, DIGITAL SECURITY, INFORMATION TECHNOLOGIES" (2025 QM&DS&IT).: IEEE, 2025. P. 169–173.
The equipment condition assessment system of the Caspian Pipeline Consortium is purposed to enhance the efficiency of monitoring and to manage the operation of pipeline systems. The primary objective of this initiative is to develop an information system that enables continuous monitoring of pipeline conditions, thereby minimizing maintenance costs and reducing risks associated with potential ...
Added: April 21, 2026
Trofimov S., Ymer 2025 Vol. 24 No. 11 P. 1–18
This paper presents the development of a multi-agent system for managing the technical condition of bus fleets in public transport enterprises. The proposed solution aims to enhance management decision-making processes in vehicle maintenance through the implementation of intelligent agents and data analytics. The system is based on the interaction of two types of agents: "Bus," which collects ...
Added: January 24, 2026
Kopnova E., Журавлева К. А., Коряков И. В. et al., Журнал Белорусского государственного университета. Экономика 2025 № 1 С. 36–46
he article examines the prospects for economic cooperation between Russia and Belarus within the framework of the EAEU, SCO and BRICS integration associations, with an emphasis on the impact of sanctions and their consequences for the economic growth of the countries. The study includes the use of econometric modeling methods to evaluate the forecast of ...
Added: December 11, 2025
Kychkin A., Chernitsin I., Vikentyeva O., , in: 2025 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM).: IEEE, 2025. P. 987–991.
Industry 4.0 concept focuses on sustainability problem that requires to control air emissions, especially for harmful substances like H2S, and reduction their impact on nature by using environmental monitoring and sources identification systems. This task requires solving inverse problem of dispersion models, which should establish complex mathematical dependences between the sensor data, the location and ...
Added: November 4, 2025
Smirnov S. V., Вопросы экономики 2025 № 10 С. 131–154
The paper summarizes machine-learning (ML) methods most relevant to macroeconomics and assesses their performance in forecasting and nowcasting key macro indicators. Despite rapid methodological progress and a surge of publications over the past 25 years, gains in forecast accuracy with traditional statistical (economic, financial, and survey) data remain modest. ML models often outperform naïve and ...
Added: October 12, 2025
Kychkin A., Chernitsin I., Vikentyeva O., , in: 2025 International Russian Automation Conference (RusAutoCon).: IEEE, 2025. P. 1046–1050.
This paper presents system architecture of the automated AI-driven predictive assessment of the ecological state of the air in sanitary protection zones around industrial facilities. The developed solution implements automated pre-processing of data presented in the form of time series using machine learning methods and the construction of short-term forecasts of pollutant concentrations for the ...
Added: October 6, 2025
Чан Ф. Т., Староверова О. В., Kosov M., Аудиторские ведомости 2025 № 2 С. 129–134
This article is devoted to the study of factors affecting enterprise cash flow management. Methods of analysis and synthesis of peer-reviewed scientific sources on this issue are applied. As a result of the research, two groups of factors have been identified and systematized: objective factors (state economic policy, customer influence) and subjective factors (competence of ...
Added: September 22, 2025
Karacharovskiy V., Социологические исследования 2025 № 6 С. 3–14
The article evaluates the possibility of forecasting mass social attitudes based on the interest of the population for the eras in the development of the country. Historical eras and their symbols are considered as comparison standards, temporal analogues of reference groups that provide the mass consciousness with samples of “reserve” standards of living and standards ...
Added: August 12, 2025
К прогнозированию вероятности невооруженной революционной дестабилизации методами машинного обучения
Медведев И. А., Korotayev A., Социология власти 2025 Т. 37 № 2 С. 108–141
The authors provide a broad overview of the main applications for machine learning methods in political sociology. They describe history of the transition from simple regression models to complex machine learning models. The reasons for and benefits of this transition are discussed. The authors identify the main uses of machine learning models in related disciplines and ...
Added: August 1, 2025
Tatyana A. Alexeeva, Kuznetsov N., Mokaev T. et al., Chaos, Solitons and Fractals 2025 Vol. 196 Article 116371
Irregular dynamics (especially chaotic) is often undesirable in economics because it presents challenges for predicting and controlling the behavior of economic agents. In this paper, we used an overlapping generations (OLG) model with a control function in the form of government spending as an example, to demonstrate an effective approach to forecasting and regulating chaotic ...
Added: April 20, 2025
Smirnov N., Высшее образование в России 2025 Т. 34 № 3 С. 77–99
The study examines the effects of the Russian Foundation for Basic Research grant programme for doctoral students. It analyses the impact of the programme, implemented in 2019–2020, designed to support dissertation research among doctoral candidates. The study investigates the effects of receiving a grant on doctoral students’ outcomes and scientific productivity, specifically their successful thesis ...
Added: April 10, 2025
Lee H., Sergey U. Chernikov, Nagy S. et al., Social Sciences 2022 Vol. 11 No. 11 Article 522
This empirical study investigates the impact of the Hofstede cultural dimensions (HCD) on the Global Innovation Index (GII) scores in four different years (2007, 2009, 2019 and 2021) to compare the impacts during the pre- and post-crisis (financial and COVID-19) period by employing ordinary least square (OLS) and robust least square (Robust) analyses. The purpose ...
Added: March 11, 2025
Pshichenko D., Znanstvena misel 2024 No. 96 P. 38–42
The article analyzes the application of artificial intelligence (AI) models for forecasting market volatility (MV). Examples of algorithms such as recurrent neural networks (RNN), long short-term memory (LSTM) networks, and regression methods are studied, demonstrating their effectiveness in processing time series and identifying complex data patterns. The importance of integrating machine learning (ML), as a ...
Added: March 10, 2025
D. Pshychenko, Вестник Воронежского института высоких технологий 2024 Vol. 18 No. 3 Article 14
The article discusses the optimization of business processes using automated control systems based on
artificial intelligence (AI). Modern methods such as machine learning, robotic process automation,
natural language processing, and predictive analytics are examined, which enhance operational
efficiency, improve forecasting accuracy, and minimize errors. The advantages of implementing AI in
various business sectors are analyzed, including the automation of ...
Added: March 10, 2025
Pshichenko D., Инновационная наука 2024 No. 7-2 P. 40–45
This paper evaluates the effectiveness of AI-based Customer Relationship Management (CRM) systems
compared to traditional CRM systems. It examines the impact of AI integration on business operations, focusing
on automation and personalization. A comparative analysis highlights significant advantages of AI-CRM systems
in terms of customer satisfaction and operational efficiency. The study also addresses challenges, including high
implementation costs and ...
Added: March 10, 2025
Габов М. А., Bukina T. V., Kashin D., Журнал Новой экономической ассоциации 2025 № 4(69) С. 87–117
The study aims to compare approaches to forecasting the monthly level of consumer price index (CPI y/y) in the regions of the Volga Federal District using time series models and machine learning methods. This study attempts to select the most appropriate and efficient models for predicting the regional general price level index. The paper also ...
Added: February 22, 2025