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Новые методы сжатия временных рядов экологических показателей
С. 192–195.
Чуприн В. И., Rodriges Zalipynis R. A.
The paper analyzes storage peculiarities of satellite Earth remote sensing data time
series. We propose methods for their compression based on the discovered peculiarities exploiting
different schemes of Huffman coding. One of the proposed methods reaches 6% increase in the
compression ratio (93%) in contrast to the deflate method used in Java SE6 (87%), for a time
series of aerosol optical thickness derived from MODIS radiometer of TERRA satellite. Further
improvement can be achieved by using the entropy coding of floating point numbers.
Language:
Russian
In book
Issue 1(2)–2(3). , Donetsk: Донецкий национальный технический университет, 2012.
Ankudinov I., Социология: методология, методы, математическое моделирование 2025 № 61 С. 165–203
The changing political mood of Russians is a constant subject of interest for sociological agencies. With the development of the Internet, conventional questionnaire research began to be supplemented by online surveys and, despite some skepticism, by social media mining. This article attempts to adjust an accidental web-sample so as to bring its estimates closer to ...
Added: April 22, 2026
Hushchyn M., Arzymatov K., Derkach D., Machine Learning 2026 Vol. 115 Article 56
Moments when a time series changes its behavior are called change points. Occurrence of change point implies that the state of the system is altered and its timely detection might help to prevent unwanted consequences. In this paper, we present two change-point detection approaches based on neural networks and online learning. These algorithms demonstrate linear ...
Added: March 6, 2026
Ivanov S., Borisov V., Ali S. et al., , in: 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE).: IEEE, 2025. Ch. 127 P. 1–7.
This paper investigates the problem of detecting slow refrigerant leaks in a data center cooling system using a graph neural network. The study addresses the challenge of early fault identification, proposing a method for constructing a topological graph based on the engineering diagram, the physical layout, and the cause-and-effect relationships in the cooling system. This ...
Added: December 19, 2025
Алескеров Ф. Т., Lola I. S., Asoskov D. et al., Вопросы экономики 2025 № 11 С. 143–157
The LC-curve method, a new approach to time series analysis, was applied to the composite Business Uncertainty Index (BUI), based on the results of regular Rosstat business surveys, which made it possible to analyze uncertainty trajectories across Russia's enlarged industries and sub-sectors using two index specifications: ex-ante (forecast) and ex-post (actual). The results of the ...
Added: October 13, 2025
Семаков С. Л., Семаков А. С., М.: Физматлит, 2012.
Рассматриваются методы прогнозирования и оперативного управления процессом продаж товара в торговых сетях. Работа будет интересна аналитикам и менеджерам торговых сетей, а также студентам вузов, предполагающим свою дальнейшую деятельность в качестве сотрудников торговых сетей. ...
Added: August 5, 2025
Чертоганов К. А., Journal of Finance and Data Science 2025
This research aims to enhance the forecasting accuracy of extreme events, which pose significant challenges across various domains such as meteorology, finance, and public health. The study investigates the integration of cross-correlation and partial autocorrelation functions (PACF) with machine learning techniques to address the limitations of traditional forecasting methods and improve predictive reliability and interpretability. ...
Added: April 29, 2025
Ivanov P., Shtark M., Kozhevnikov A. et al., IEEE Access 2025 Vol. 13 P. 25186–25197
Fault detection and diagnosis (FDD) is a critical challenge in industrial processes aimed at minimizing risks such as safety hazards, costly downtime, and suboptimal production. Traditional supervised FDD methods offer great performance while heavily relying on large volumes of labeled data, whereas unsupervised methods do not depend on labeled data, though are inferior in performance ...
Added: April 29, 2025
Makeeva N., Прикладная эконометрика 2025 Т. 79 С. 27–49
The paper presents the results of an accuracy analysis of nowcasting models for Russia’s GDP and its components based on usage data for the period from the first quarter of 2014 to the third quarter of 2023. The novelty of the study lies in comparing the accuracy of various models — MIDAS, MFBVAR, DFM models, ...
Added: April 19, 2025
Shvedov A. S., Sviyazov V., В кн.: Системное моделирование социально-экономических процессов: труды 46-ой международной научной школы-семинара, г. Уфа, 9 - 15 октября 2023 г.: Воронеж: Истоки, 2024. С. 526–531.
The generalized autoregressive conditional heteroscedasticity model is widely applied to financial time series. There are further generalizations of this model. One of such generalizations is a combination of Takagi–Sugeno type fuzzy systems and autoregressive conditional heteroscedasticity models. The Takagi–Sugeno fuzzy systems advantage is that there is a standalone generalized autoregressive conditional heteroscedasticity model constructed for ...
Added: June 26, 2024
Баранников А. В., Левицкий И. А., Loginov V. et al., Информационные процессы 2023 Т. 23 № 4 С. 555–567
The Multi-User Multiple Input Multiple Output (MU-MIMO) technology allows increasing the channel throughput. However, MU-MIMO efficiency is reduced by overhead induced by frequent channel sounding and transmission of channel feedback frames. This paper examines the problems of channel state information (CSI) compression in Wi-Fi networks using MU-MIMO with channel aging. The research aims to experimentally ...
Added: January 17, 2024
Sizykh D., Sizykh N., Чебоксары: ИД «Среда», 2023.
The monograph presents research materials based on the results of assessment and analysis of the dynamic characteristics of time series of stock quotes. Optimal estimates were selected and justified, the applying of which makes possible to improve the quality and efficiency of the forecasting stock quotes, building and rebalancing of investment portfolios, risk management, etc. ...
Added: December 22, 2023
Sviyazov V., Control Sciences 2022 No. 6 P. 21–28
Volatility modeling and forecasting is a topical problem both in scientific circles and in the practice. This paper develops an approach combining the GARCH model and fuzzy logic. The Takagi–Sugeno fuzzy inference scheme is adopted to fuzzify an original autoregression model (the conditional heteroskedasticity model). As a result, several different local GARCH models can be ...
Added: December 6, 2023
Sviyazov V., Экономический журнал Высшей школы экономики 2023 Т. 27 № 3 С. 412–434
The problem of volatility forecasting with and without consideration of weekly seasonality effect (the weekend effect) is examined in this research. The question of the seasonality existence is understood in the following sense: do models, which incorporate seasonality, feature better forecasts? The fuzzy GARCH model, which accounts for a weekly seasonality effect is presented in ...
Added: October 28, 2023
Bessonov V. A., Вопросы статистики 2023 Т. 30 № 4 С. 84–95
The paper discusses the author's proposals for addressing the problem of achieving the comparability of Russian socio-economic indicators related to the change in the borders of the state as a result of the special military operation. The experience of ensuring indicators comparability when changing state borders, namely during the unification of Germany in 1990 and ...
Added: August 25, 2023
Beznosikov A., Richtarik P., Diskin M. et al., , in: Thirty-Sixth Conference on Neural Information Processing Systems : NeurIPS 2022.: Curran Associates, Inc., 2022. P. 14013–14029.
Added: January 27, 2023
Riabykh A., Surzhko D., Konovalikhin M. et al., PeerJ Computer Science 2022 Vol. 8 Article e1156
Open text data, such as financial news, are thought to be able to affect or to describe stock market behavior, however, there are no widely accepted algorithms for extracting the relationship between stock quotes time series and fast-growing textual representation of economic information. The field remains challenging and understudied. In particular, topic modeling as a ...
Added: December 18, 2022
Makeeva N., Stankevich I., Экономический журнал Высшей школы экономики 2022 Т. 26 № 4 С. 598–622
The paper discusses the problem of nowcasting the current growth rates of Russian GDP and its components using quarterly data. The quality of restricted and unrestricted MIDAS models (models with mixed data), MIDAS model with L1 regularisation and MFBVAR model (Bayesian vector autoregression of mixed frequency) are compared. The results are compared with classical autoregression ...
Added: December 9, 2022
Pashkov S., Социология: методология, методы, математическое моделирование 2021 № 53 С. 39–82
The Consumer Sentiments Index (CSI) reflects views of the population of Russia on the economic and financial policy of the country and contributes to the understanding of recessive changes in the economy. Current methodological approach singles out inflation, exchange rate, unemployment, intensity of economic events coverage in mass media as the primary factors that guide consumers in their assessments when ...
Added: December 5, 2022
Mylnikov L., СПб.: БХВ Петербург, 2021.
Книга посвящена активно развивающейся на сегодняшний день области, связанной с построением и использованием эмпирических моделей в задачах управления и планирования производственными системами находящейся на стыке статистики, информационных технологий, методов машинного обучения и предметной области в которой эти знания применяются. Целью книги является знакомство читателя с используемыми для этого методами и примерами их применения. Книга позволяет ...
Added: October 6, 2022
Kramkov V., Maksimov A. G., В кн.: Системное моделирование социально-экономических процессов: труды 43-ей международной научной школы-семинара.: Воронеж: Истоки, 2020. С. 433–438.
Added: September 27, 2022