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A three-factor stochastic model for forecasting production of energy materials
Finance Research Letters. 2023. Vol. 51. Article 103356.
Bufalo M., Orlando G.
In this paper, we present a generalized stochastic three-factor model to forecast changes in the industrial production of energy materials. This approach is new as, by deriving a stochastic process correlated with its mean and volatility, we convert it into an uncorrelated auxiliary process through Lamperti transformations. We show that the proposed model can be used for forecasting the change in the equilibrium between demand and supply of energy materials and could be further developed for setting up a reference pricing model for the market. © 2022 Elsevier Inc.
Warong M. M., Prostranstvennaya ekonomika 2026 Vol. 22 No. 2 P. 86–105
Achieving a global energy transition requires multidimensional policy designs, but the universal approach to international benchmarking often fails in emerging nations with diverse institutional trajectories and a heavy reliance on fossil fuels. This study systematically assesses the long-run macroeconomic performance of integrated energy policy portfolios – market-based, non-market-based, and technology support – in the expanded ...
Added: September 20, 2026
Medvedev V., Annals of Global Analysis and Geometry 2026 Vol. 70 No. 2 P. 8–23
This paper studies three-dimensional compact static manifolds with boundary and positive scalar curvature. We prove that, under a suitable bound on the Ricci curvature, the orientable quotient of the Nariai static manifold with boundary is the only such manifold with connected boundary, provided that the zero-level set of the potential is connected and does not intersect ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2026 Vol. 36 No. 2 P. 323–334
In this paper, an improved approach for automatic wildlife detection in natural environments based on the integration of a neural network architecture with a two-stream attention mechanism and a novel preclassification step based on infrared data has been presented. The proposed method addresses one of the key challenges in environmental monitoring: the need for scalable ...
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Proceedings of the ACM on Management of Data, USA 2026 Vol. 4 No. 1 P. 1–28
Modern knowledge and large volumes of data are increasingly encoded within neural networks, making the task of simplifying their structures and reducing the number of parameters especially relevant, both to improve efficiency and to facilitate deployment in resource-constrained environments. This paper presents a novel approach to neural network compression that addresses redundancy at both the ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 148–158
This paper describes our research on creating classifiers for microbial images (micrococci microscopy images) obtained from pictures of unfixed microscopic scenes. In our work, we propose an AutoML approach based on the automatic generation and analysis of the feature space for constructing the most optimal descriptors of microorganism images for subsequent classification. This makes it ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2026 Vol. 36 No. 2 P. 302–312
The lack of annotated microscopic datasets remains a major obstacle to training robust deep learning models for microbial classification. In this paper, a novel data augmentation pipeline that uses visual–linguistic large-scale models to generate synthetic microscopic images of six different bacterial and nonbacterial classes has been proposed. Synthetic samples have gradually been added to the ...
Added: September 19, 2026
Springer, Cham, 2026.
computer vision ...
Added: September 19, 2026
Springer, Cham, 2026.
Added: September 19, 2026
FRUCT Oy, 2024.
Added: September 19, 2026
FRUCT Oy, 2024.
Added: September 19, 2026
FRUCT Oy, 2025.
Added: September 19, 2026
FRUCT Oy, 2026.
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 8 P. 1–26
This paper presents a novel method for pruning deep neural networks based on the concept of flow, derived from the continuous modeling of signal propagation across layers. We derive flow functions for fully connected, convolutional, and self-attention architectures, and we propose a new iterative pruning algorithm, Iterative Flow-Aware Pruning (IFAP), that leverages these measures to ...
Added: September 19, 2026
Kuzyutin D., Smirnova N., Veselkov A., Bulletin of the South Ural State University, Series: Mathematical Modelling, Programming and Computer Software 2026 Vol. 19 No. 3 P. 40–49
We consider spatial dynamic fishery management problem taking into account the resource migration process between an open-access fishing area and no-take marine protected area. The introduced extension of a standard single-criterion fish war game implies that each player aims to maximize simultaneously two performance criteria which present an economic benefit and an environmental conservation goal ...
Added: September 18, 2026
Lola I. S., Asoskov D., Усов Н. А., ИСИЭЗ НИУ ВШЭ, 2026.
В обзоре представлены композитные индикаторы раннего реагирования, рассчитанные на основе обобщенных результатов обследований деловой активности, проводимых Росстатом в мониторинговом режиме в базовых видах экономической деятельности. Индексы рассчитываются в соответствии с общими рекомендациями ОЭСР и руководством Европейской комиссии по построению композитных индикаторов опережающего характера.
В основу обзора положены ежеквартальные и ежемесячные конъюнктурные опросы руководителей организаций базовых ...
Added: September 18, 2026
Lola I. S., Asoskov D., ИСИЭЗ НИУ ВШЭ, 2026.
В обзоре Центра конъюнктурных исследований ИСИЭЗ НИУ ВШЭ представлены текущие и прогнозные тенденции на важнейших отраслевых рынках труда, которые отражают простые и композитные индикаторы занятости (Индекс кадровой обеспеченности, Индекс совокупной занятости и т. д.), рассчитанные на основе обобщенных результатов обследований деловой активности, проводимых Росстатом в мониторинговом режиме в базовых видах экономической деятельности. Исследование охватывает шесть ...
Added: September 18, 2026
Lola I. S., Ostapkovich G. V., Усов Н. А., ИСИЭЗ НИУ ВШЭ, 2026.
Центр конъюнктурных исследований Института статистических исследований и экономики знаний Национального исследовательского университета «Высшая школа экономики» представляет аналитический обзор о состоянии делового климата в сфере услуг в II кв. 2026 г., а также ожиданиях на III кв.
В обзоре использованы результаты ежеквартальных опросов, проводимых Федеральной службой государственной статистики среди руководителей 3 тыс. организаций, оказывающих различные виды ...
Added: September 18, 2026
Lola I. S., Ostapkovich G. V., Семенова М. Т., ИСИЭЗ НИУ ВШЭ, 2026.
Центр конъюнктурных исследований Института статистических исследований и экономики знаний НИУ ВШЭ представляет информационно-аналитический материал «Потребительские настроения населения во II квартале 2026 г.», подготовленный в рамках Программы фундаментальных исследований НИУ ВШЭ.
В основу обзора положены ежеквартальные опросы более 5 тыс. человек в возрасте от 16 лет и старше. Такие опросы Федеральная служба государственной статистики (Росстат) проводит во всех субъектах ...
Added: September 18, 2026
Lola I. S., ИСИЭЗ НИУ ВШЭ, 2026.
Центр конъюнктурных исследований ИСИЭЗ НИУ ВШЭ представляет специальный выпуск обзора потребительских настроений россиян в II кв. 2026 г., основанный на данных ежеквартального опроса Росстата. Внимание уделено представителям младшей возрастной группы (16–29 лет). В фокусе исследования — динамика частного Индекса потребительской уверенности (ИПУ), потребительские оценки ожидания изменений личного материального положения в ближайшую годовую перспективу, текущей экономической ...
Added: September 18, 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
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
Lisenkova A. D., Современная Европа 2025 № 6 С. 74–84
The energy supplies is a traditional problem for the EU due to the lack of its own resources. This issue has become most relevant after the deterioration of relations with Russia, formerly a leading energy partner. The Union began to explore options for diversification because it is not ready to implement a green transition at ...
Added: November 22, 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