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Forecasting seeing and parameters of long-exposure images by means of ARIMA
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 the forecasting. A new procedure for forecasting the image characteristics of direct astronomical observations (central image intensity, full width at half maximum, radius encircling 80% of the energy) has been proposed. Probability density functions of the forecast of these quantities are 1.5–2 times thinner than the respective unconditional probability density functions. Overall, this study found that the described technique could adequately describe temporal stochastic variations of the OT power.
Piontkovski D., / Series arXiv "math". 2026.
A noncommutative projective variety is defined, following Artin and Zhang, by a graded coherent algebra 𝐴. The category of coherent sheaves is then the quotient qgr(𝐴) of the category of finitely presented graded modules by the subcategory of torsion modules. We consider the categorical and polynomial entropies of the Serre twist, that is, of the ...
Added: June 23, 2026
Piontkovski D., / Series arXiv "math". 2025.
If a symmetric multilinear algebra is weakly nil, then it is Engel. This result may be regarded as an infinite-dimensional analogue of the well-known Jacobian theorem, which states that if a polynomial mapping has a polynomial inverse, then its Jacobian matrix is invertible. This refines a theorem of Gerstenhaber and partially answers a question posed ...
Added: June 23, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Daria Gribkova, Milshina Y., , in: Artificial Intelligence Enabled Real Time Environmental Monitoring.: Springer, 2026. P. 231–252.
The environment, as a dynamic system influenced by anthropogenic factors, requires evidence-based decision-making to ensure sustainable resource management and mitigate adverse effects. This chapter explores the transformative role of artificial intelligence (AI) in environmental decision support systems (EDSS), focusing on its potential to address complex environmental challenges. EDSS, characterized by their interactivity and ability to ...
Added: January 12, 2026
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer: original packets are encoded into coded packets, and the message is reconstructed after the first successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025
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
Musaev A., Makshanov A., Dmitry Grigoriev, Computational Economics 2024 Vol. 64 P. 137–160
This paper addresses the challenge of short-term forecasting for processes modeled as output signals of nonlinear dynamic systems in unstable environments with non-stationary, non-Gaussian interference. Traditional computational forecasting methods are often ineffective for such chaotic processes, which exhibit exponential divergence of trajectories. We propose a solution based on multidimensional correlations with other processes in the ...
Added: July 11, 2025
Kolokolov I., Lebedev V., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2025 Vol. 111 No. 6 Article 064104
We examine the probability of the appearance of high values of the intensity I of a light beam at its propagation
in the turbulent atmosphere. Starting from the functional integral representation of averages over turbulent
fluctuations, we find the saddle-point configuration in the functional space corresponding to the high values of
I. The saddle-point configuration determines the tail ...
Added: June 5, 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
Liseo B., Bufalo M., Orlando G., Applied Stochastic Models in Business and Industry 2022 Vol. 38 No. 4 P. 620–650
The gist of this work is to propose a minimum tracking error portfolio that could be adopted not only as an automated alternative to ETFs but, it could also be potentially used to anticipate market changes in the target index. This goal has been achieved by adopting skew Brownian motion as a general framework. The ...
Added: February 23, 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
Leonid N. Yasnitsky, Gruzman V., Martynenko S. et al., , in: 2023 5th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA)Vol. 5.: IEEE, 2023. P. 813–816.
Abstract—The paper deals with the creation and application of a mathematical model designed for operational control of strength characteristics of items produced under conditions of open-hearth steelmaking. Variations in the chemical composition of the raw material as well as in the parameters and modes of smelting are used as controlling influences. The mathematical model is ...
Added: February 4, 2024
Barskov K., Chechin D., Drozd I. et al., Boundary-Layer Meteorology 2023 Vol. 187 P. 311–338
We present results from the multi-level mast eddy-covariance measurements conducted over flat grassland and over complex urban terrain composed of trees and small buildings. Relationships between the stability parameter and turbulent statistical properties were analysed. Over flat grassland, non-dimensional turbulent moments up to the third-order obey Monin–Obukhov similarity theory. Third-order moments increase for increasing instability, ...
Added: October 5, 2023
Dean Fantazzini, Julia Pushchelenko, Mironenkov A. et al., Forecasting 2021 Vol. 3 No. 4 P. 774–803
This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to study the migration data of the two Russian cities with the largest migration inflows: Moscow and ...
Added: July 28, 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
Korotayev A., Ilya Medvedev, Zinkina J., Comparative Sociology 2022 No. 21 P. 64–104
This article offers a comparison of sociopolitical instability forecasting systems. It compares systematically their efficiency by correlating their predictions for particular years with actual levels of destabilization in the respective years. It is demonstrated that the predictive capacity of those systems dropped dramatically after 2011. This is shown to be connected with the fact that ...
Added: March 15, 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
Kornilov V., Safonov B., Kornilov Matwey, Journal of the Optical Society of America A: Optics and Image Science, and Vision 2021 Vol. 38 No. 9 P. 1284–1292
The development of new techniques for characterizing atmospheric optical turbulence (OT) has become an active topic of research again in recent years. In order to facilitate these studies, we reconsidered known theoretical results and obtained some new practically useful conclusions. We introduce a dimensionless Fresnel filter, which allows us to approximate a polychromatic weighting function ...
Added: September 27, 2021