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Features of Data Collection and Software Tool Architecture for Performing Predictive Analysis of Phenomena Leading to Forest Fires
P. 379–395.
In book
Vol. 1228. , Springer Publishing Company, 2025.
Chikake T. M., Goldengorin B. I., Pardalos P. M., Computer Optics 2025 Vol. 49 No. 6 P. 1191–1201
We present a general-purpose, training-free framework for dimensionality reduction and clustering based on per–sample pseudo–Boolean polynomials (PBP). The method constructs compact, interpreTab. features without model fitting and is evaluated under a standardized protocol that compares PBP to PCA, t-SNE, and UMAP using identical inputs and metrics: clustering alignment (V-measure, Adjusted Rand Index), cluster geometry (Silhouette coefficient, ...
Added: January 2, 2026
Khomenko A., Komratova A., Isakov D. et al., В кн.: Экспериментальные исследования языка: материалы конференции 2025.: М.: Наш мир, 2025. С. 17–19.
This study aims to develop a tool for the automated diagnosis of mental disorders based on the analysis of Russian-language speech transcripts. The model uses clustering and stylometric methods to identify differences between the speech of healthy individuals and patients with psychiatric diagnoses. ...
Added: October 19, 2025
Индаков Г. С., Казначеев П. А., Майбук З. Я. et al., Геофизические исследования 2025 Т. 26 № 2 С. 99–124
The paper studies the clusterability of acoustic emission pulses during high-temperature heating of sandstone sample preliminarily subjected to mechanical loading. Mechanical loading was applied in uniaxial mode up to load close to destructive with appearance of signs of large cracks on the surface. After that, samples were subjected to thermal treatment up to 650 °C ...
Added: September 19, 2025
Алкзир Н., Yarykina n., Nikolaev D. et al., Neuroscience and Behavioral Physiology 2024
Added: April 28, 2025
Ullah T., Siraj A. H., Umer Mukhtar Andrabi et al., , in: 2022 VIII International Conference on Information Technology and Nanotechnology (ITNT).: IEEE, 2022. P. 1–7.
Added: March 20, 2025
Yasnitsky L., Plotnikova E. G., Прикладная информатика 2024 Т. 19 № 5 С. 88–100
Outliers in statistical data, which are the result of erroneously collected information, are often an obstacle to the successful application of machine learning methods in many subject areas. The presence of outliers in training data sets reduces the accuracy of machine learning models, and in some cases, makes the application of these methods impossible. Currently ...
Added: November 29, 2024
Gromov V., Zvorykina, E., Beschastnov Y. et al., , in: Recent Trends in Analysis of Images, Social Networks and Texts: 11th International Conference, AIST 2023, Yerevan, Armenia, September 28–30, Revised Selected Papers.: Springer, 2024. P. 250–262.
The paper explores mathematical methods that differentiate regular and chaotic time series, specifically for identifying pathological fistulas. It proposes a noise-resistant method for classifying responding rows of normally and pathologically functioning fistulas. This approach is grounded in the hypothesis that laminar blood flow signifies normal function, while turbulent flow indicates pathology. The study explores two ...
Added: August 12, 2024
Milovidov S., Artnodes 2024 No. 33 P. 1–9
This article employs a case‐study method to investigate the artivism neural network community concentrated on Twitter (since renamed X), which has been ideologically influenced by the content policy and limitations of OpenAI. Today, many young artists using machine learning technologies in their artworks (Midjourney, Stable Diffusion, Kandinsky) note that despite significant progress in the field ...
Added: February 1, 2024
Kosmachev A., Задорожникова А. А., Perov A., В кн.: БОЛЬШИЕ ДАННЫЕ Материалы I Международного форума (Новосибирск, 16–18 ноября 2022 года).: Новосибирск: Новосибирский государственный университет экономики и управления «НИНХ», 2023.
The article discusses the basic concepts and terms used in steganography, substantiates the relevance of the problem of steganalysis, discusses the use of deep neural networks in the tasks of steganalysis on digital images. A comparative analysis and description of the most effective convolutional network architectures for solving the task is performed. ...
Added: January 26, 2024
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
Искандеров Ю. М., Катарушкин Б. Е., Ершов А. А., Информатизация и связь 2020 № 2 С. 46–51
Aim. Currently, when creating intelligent information systems in various fields of practical activity, machine learning methods are used. The article shows the possibilities of using these methods in automating the detection of obstacles in the interest of improving safety and reducing the number of emergencies at level crossings. Materials and methods. The article discusses advanced ...
Added: September 15, 2023
Fabrykant M., Социодиггер 2023 Т. 4 № 5-6
Обсуждаются возможные причины доверия к ChatGPT. Делается вывод, что основная приична в том, что ChatGPT представляют собой наиболее точный из доступных эквивалентов коммуникации с обществом в целом. ...
Added: August 23, 2023
[б.и.], 2023.
Addressing problems in different science and engineering disciplines often requires solving optimization problems, including via machine learning from large training data. One class of methods has recently gained significant attention for problems in computer vision and visual computing: coordinate-based neural networks parameterizing a field, such as a neural network that maps a 3D spatial coordinate ...
Added: July 18, 2023
Pantiukhin D., Информатика и образование 2023 Т. 38 № 1 С. 55–63
The problem of neural network vulnerability has been the subject of scientific research and experiments for several years. Adversarial attacks are one of the ways to “trick” a neural network, to force it to make incorrect classification decisions. The very possibility of adversarial attack lies in the peculiarities of machine learning of neural networks. The ...
Added: April 14, 2023
Vladimir V. Klinshov, Kirillov S., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2022 Vol. 106 No. 6 Article L062302
Neural mass models is a general name for various models describing the collective dynamics of large neural
populations in terms of averaged macroscopic variables. Recently, the so-called next-generation neural mass
models have attracted a lot of attention due to their ability to account for the degree of synchrony. Being exact
in the limit of infinitely large number of ...
Added: January 24, 2023
Vladimir V. Klinshov, Kovalchuk A., Franović I. et al., Chaos, Solitons and Fractals 2022 Vol. 158 Article 112011
Rate chaos is a collective state of a neural network characterized by slow irregular fluctuations of firing rates of
individual neurons.We study a sparsely connected network of spiking neuronswhich demonstrates three different
scenarios for the emergence of rate chaos, based either on increasing the synaptic strength, increasing the
synaptic integration time, or clustering of the excitatory synaptic connections. ...
Added: January 24, 2023
Muratova A., Ignatov D. I., Mitrofanova E., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 297–299.
This is the extended abstract of a case study on demographic sequences analysis by machine learning and data mining methods. ...
Added: November 1, 2022
Pantiukhin D., Речевые технологии 2021 № 3-4 С. 3–16
Added: June 17, 2022
Identification of hydrogen permeability and thermal desorption parameters of vanadium-based membrane
Zaika Y. V., Sidorov N. I., Fomkina Olga V, International Journal of Hydrogen Energy 2021 Vol. 46 No. 18 P. 10789–10800
The paper implements a two-stage “penetration + thermal desorption” experiment for the complex estimation of hydrogen permeability and thermal desorption parameters (sorption, dissolution, diffusion and desorption) of vanadium-based membrane. A gradual growth of the thermal desorption flux at high temperature is interpreted as a lowering of the potential surface barrier (primarily due to the loss of oxides). Indirect evidence ...
Added: January 30, 2022
Belov A. V., Sapozhnikov A., Semichasnov I., , in: Proceedings of the 2021 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS).: IEEE, 2021. P. 485–490.
The purpose of this work is to develop algorithms and game mechanics for controlling the car driving along a track using a genetic algorithm for training a neural network with the ability to save and load the obtained weights during training. A genetic algorithm and a neural network were developed using the C ++ programming ...
Added: January 14, 2022
Markvirer V., Sakhipova M., В кн.: Математика и междисциплинарные исследования – 2021.: Пермь: Пермский государственный национальный исследовательский университет, 2021. С. 152–157.
Added: December 19, 2021