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Predictive models for metrological data of engineering systems
Journal of Physics: Conference Series. 2021. Vol. 1740. P. 1–6.
Lukankin Alexander, Slastnikov Sergey
Paper is devoted to the predictive models for metrological indicators on the real estate engineering infrastructure. The solution is in demand among many enterprises both in terms of security and economic considerations. The key task is to build a mathematical model performing predictions on the real data samples. We study both classical predictive models (ARIMA, SARIMA) and modern machine learning based approaches (RBF, LSTM), and compare them.
Nazarova V., Lodiagin B., Круглов Ф. А. et al., AlterEconomics (ранее - Журнал экономической теории) 2025 № 22(3) С. 482–502
This paper examines methods for forecasting oil prices, comparing traditional autoregressive mo dels (ARIMA, SARIMAX) with machine learning approaches (LSTM). The target variable is the price of WTI crude oil. The dataset covers 2015–2019 and includes both WTI price data and a set of exogenous varia bles: the Wilshire 5000, Dow Jones, and DXY indices; ...
Added: October 5, 2025
Surkov A., Zakharov V., Sergei Koltcov et al., , in: Smart Technologies, Systems and Applications: 4th International Conference, SmartTech-IC 2024, Quito, Ecuador, December 2–4, 2024, Revised Selected Papers, Part IIVol. 2: Revised Selected Papers, Part II.: Springer, 2025. P. 239–252.
Currently, large language models are actively developing and beginning to be used to solve some mathematical problems. With the emergence of xLSTM model, which demonstrates the results comparable with transformer-based models, there has been a surge of interest in recurrent neural networks. This paper considers the application of baseline recurrent models such as LSTM and ...
Added: September 11, 2025
Kruchinskaia E., Политическая наука 2025 № 1 С. 156–180
The article examines the phenomenon of affective political polarization, which is operationalized through the fact of detected hate speech. In this study we have made two assumptions. Firstly, it is believed that during political mobilization, affective polarization (hate speech) will be significantly stronger than during the non-protest period, although hate speech will be detected for ...
Added: March 12, 2025
Sizykh D., Tregub K., Belyakov B. et al., , in: 2024 17th International Conference on Management of Large-Scale System Development (MLSD).: IEEE, 2024. P. 1–5.
Currently, a large number of studies are being conducted to improve the accuracy of the developed forecasting methods for the stock market. At the same time, multivariate models based on machine learning methods are increasingly used. Since liquidity indicators have a significant impact on asset pricing, taking them into account can improve the accuracy of ...
Added: January 15, 2025
Bronitsky G., Population and Economics 2024 Vol. 8 No. 2 P. 133–154
Analysis of migration flows is crucial for understanding and forecasting social and economic trends. This paper presents an algorithm for obtaining migration estimates with minimal time delay (nowcasting) using Google Trends Index (GTI) search queries. The predictive power of the models is assessed across different periods, including one marked by the restrictions imposed due to ...
Added: March 21, 2024
Orlando G., Bufalo M., Technological and Economic Development of Economy 2023 Vol. 29 No. 4 P. 1216–1238
This research aims to propose the so-called CIR#, which takes its cue from the well- known Cox-Ingersoll-Ross (CIR) model originally devised for pricing, as a general econometric model. To this end, we present the results on two very different time series such as Polish interest rates (subject to market sentiments) and seasonal tourism (subject to ...
Added: February 22, 2024
Natalia Sizykh, Said Dandamaev, Dmitry Sizykh, , in: 16th International Conference Management of large-scale system development (MLSD).: IEEE, 2023. P. 1–5.
Forecasting data and research on cryptocurrency price forecasting methods are increasing in importance. So far, methods based on LSTM deep learning architecture have shown the best results in forecasting cryptocurrency prices. In order to improve the accuracy of forecasting data, this paper investigates the application of a multivariate multistep forecasting method based on the LSTM ...
Added: December 22, 2023
I. K. Kusakin, Fedorets O. V., A. Y. Romanov, Scientific and Technical Information Processing 2023 Vol. 50 No. 3 P. 176–183
This paper discusses modern approaches to natural language processing and the application of machine learning models to the task of classifying short scientific texts in Russian. This study is devoted to the analysis of methods for vectorization of textual information, selection of a model for scientific paper clas- sification, and training of linguistic model BERT ...
Added: November 4, 2023
Кусакин И. К., Федорец О. В., Romanov A., Научно-техническая информация. Серия 2: Информационные процессы и системы 2022 Т. 12 С. 6–9
This paper discusses modern approaches to natural language processing and appliance of artificial intelligence technologies in the task of classifying scientific texts in Russian. The report contains an analysis of implementations of text vectorization methods, a description of experiments with training various classifier models: from classical machine learning algorithms to neural network transformer architectures. ...
Added: January 31, 2023
Bronitsky G., Vakulenko E., Демографическое обозрение 2022 Т. 9 № 3 С. 75–92
International migration statistics are published with a delay of up to several years. This prevents researchers from making timely analyses of migration flows. The article reviews a method for forecasting international migration flows based on search queries on the Internet using the example of flows from Russia to Germany during 2011-2020. Rosstat, German and OECD ...
Added: October 13, 2022
Zvezdina N., Сараев А. В., Вопросы статистики 2023 Т. 30 № 1 С. 27–41
On the part of the population, residential real estate is considered from the point of view of improving the standard of living, as well as an object of profitable investment. The Russian residential real estate market attracts the attention of not only the population, but also researchers. Its structure and the multifactorial nature of development ...
Added: October 10, 2022
Aleksandr Belov, Monina M., Rakhmetullina Z., , in: 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS 2022).: IEEE, 2022. P. 1–6.
Added: July 20, 2022
Vukovic D., Romanyuk K., Ivashchenko S. et al., Expert Systems with Applications 2022 Vol. 194 No. May 2022 Article 116553
This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector
Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov
switching autoregression (MSA) for daily CDS spreads of the 513 leading US companies, in the period
2009–2020. The goal of this study is to test the forecasting performance of ...
Added: February 4, 2022
Moiseev N., Sorokin A., Zvezdina N. et al., Mathematics 2021 No. 9(19) Article 2423
The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period. In this paper, a new method of dealing with ...
Added: October 1, 2021
Giachanou A., Россо П., Crestani F., , in: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’19).: NY: Association for Computing Machinery (ACM), 2019. P. 877–880.
The spread of false information on the Web is one of the main problems of our society. Automatic detection of fake news posts is a hard task since they are intentionally written to mislead the readers and to trigger intense emotions to them in an attempt to be disseminated in the social networks. Even though ...
Added: October 29, 2020
Rodionova L., Kopnova E., Демографическое обозрение 2019 Т. 6 № 2 С. 104–141
According to the May Presidential Decree (2018), one of the national goals and strategic objectives of the development of the Russian Federation for the period up to 2024 is “ensuring sustainable natural growth in the population of the Russian Federation and increasing life expectancy to 78 years”. Thus, the increased need to monitor the current demographic situation, the study ...
Added: September 2, 2019
Kornilov Matwey V., Experimental Astronomy 2016 Vol. 41 No. 1 P. 223–242
Atmospheric turbulence is the one of the major limiting factors for ground-based astronomical observations. In this paper, the problem of short-term forecasting seeing is discussed. The real data that were obtained by atmospheric optical turbulence (OT) measurements above Mount Shatdzhatmaz in 2007–2013 have been analysed. Linear auto-regressive integrated moving average (ARIMA) models are used for ...
Added: February 7, 2019
Попова А. С., Рассадин А. Г., Пономаренко А. А., В кн.: Материалы XXIV международной научно-технической конференции «Информационные системы и технологии-2018.: [б.и.], 2018. С. 1083–1089.
Рассматривается задача автоматической классификации эмоций в цифровом аудио сигнале. В работе рассматривается и верифицируется подход, в котором классификация звукового фрагмента производится с помощью рекуррентной нейронной сети c долговременно-кратковременной памятью. В качестве признаков использовались мел-кепстральные коэффициенты. Произведен численный эксперимент на открытом наборе данных Ravdess, включающий 8 различных эмоций: “нейтральный”, “спокойный”, “счастливый”, “грустный”, “злой”, “испуганный”, “отвращение”, “удивление” ...
Added: October 21, 2018
Slastnikov S., Лупанов В. Э., Journal of Physics: Conference Series 2019 Vol. 1163 No. 12048 P. 1–6
A lot of files and data, in general, are transferred throughout the networks. But the data may be corrupted by intrusions or package loss so, the executable files may be marked as non-executable and violate the local network policy. Thus, it’s necessary to detect such files. In this paper, we present a novel method for ...
Added: October 19, 2018
Grachev A., Ignatov D. I., Savchenko A., , in: Pattern Recognition and Machine Intelligence. 7th International Conference, PReMI 2017, Kolkata, India, December 5-8, 2017, Proceedings. Lecture Notes in Computer Science book series (LNCS, volume 10597).: Springer, 2017. P. 351–357.
In this paper, we consider several compression techniques for the language modeling problem based on recurrent neural networks (RNNs). It is known that conventional RNNs, e.g., LSTM-based networks in language modeling, are characterized with either high space complexity or substantial inference time. This problem is especially crucial
for mobile applications, in which the constant interaction with ...
Added: October 14, 2018
Kondratyev M., Компьютерные исследования и моделирование 2013 Т. 5 № 5 С. 863–882
The number of papers addressing the forecasting of the infectious disease morbidity is rapidly growing due to accumulation of available statistical data. This article surveys the major approaches for the short-term and the long-term morbidity forecasting. Their limitations and the practical application possibilities are pointed out. The paper presents the conventional time series analysis methods ...
Added: January 13, 2014