Yemelyanov, V., Chernyi, S., Yemelyanova, N., Varadarajan, V. Application of neural networks to forecast changes in the technical condition of critical production facilities. Computers and Electrical Engineering. 2021, 93, 107225
Computers and Electrical Engineering. 2021. Vol. 93. Article 107225.
, , Приборы и системы. Управление, контроль, диагностика 2018 № 1 С. 25-33
In this paper author suggests a new hybrid decision support system for operation with a class of semistructured tasks with underdetermined variables. Author defined the general tasks of prediction and estimation for a class of semistructured tasks. Use of interval neural networks and genetic algorithms for such tasks is justified. Author developed the algorithm to ...
Added: February 9, 2018
, , , Бизнес-информатика 2014 № 3 С. 49-56
Object of this research is the Russian banking system. The work purpose – creation of the comput-er program of an assessment of probability of bankruptcies of banks because of revocation of li-cense of banks and use of this system as mathematical model for detection of some regularities of the Russian bank sphere. The instrument of ...
Added: March 2, 2015
, , et al., Пермский медицинский журнал 2015 Т. 32 № 4 С. 63-67
Goal. To develop a system for differential diagnosis of rhinitis allergic and infectious etiologies. Materials and methods. Data 217 pediatric patients with infectious and allergic rhinitis were used to construct a diagnostic system based on neural network technology. Results. Created the system of the differential diagnosis, allowing using a minimal number of input parameters with ...
Added: February 23, 2016
Адаптация нейронных машин Тьюринга для задачи агрегации лингвистических оценок в нейросимволических системах поддержки принятия решений
, , Информационно-управляющие системы 2021 № 5 С. 40-50
Introduction: The construction of integrated neurosymbolic systems is an urgent and challenging task. Building neurosymbolic decision support systems requires new approaches to represent knowledge about a problem situation and to express symbolic reasoning at the subsymbolic level. Purpose: Development of neural network architectures and methods for effective distributed knowledge representation and subsymbolic reasoning in decision support systems in ...
Added: November 3, 2021
, , et al., FME Transactions 2019 Vol. 47 No. 4 P. 765-774
Detection and classification of surface defects of the rolled metal is one of the main tasks for correctly assessing product quality. Historically, these tasks were performed by human. But due to a multitude of production factors, such as high rolling rate and temperature of the metal, the results of such human work are rather low. ...
Added: November 22, 2019
, , , in : 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). Vol. 1.: IEEE, 2019. P. 783-787.
A task of maximizing deep learning neural networks performance is a challenging and actual goal of modern hardware and software development. Regardless the huge variety of optimization techniques and emerging dedicated hardware platforms, the process of tuning the performance of the neural network is hard. It requires configuring dozens of hyper parameters of optimization algorithms, ...
Added: March 30, 2020
Capabilities of neural network technologies for extracting new medical knowledge and enhancing precise decision making for patients
, , et al., Expert Review of Precision Medicine and Drug Development 2021 Vol. November 2021 P. 1-9
Objectives: Currently, there is an active use of neural networks in various areas of human activity. Problems of recognition, diagnostics, optimization, forecasting, control, as well as obtaining new scientific knowledge are successfully solved. However, in medicine, due to the particular complexity of the human body, neural networks are mainly used only for solving the simplest ...
Added: January 23, 2022
, Журнал формирующихся направлений науки 2015 Т. 3 № 7
The article presents selected excerpts of the debate, which the doctor of philosophical Sciences, Professor of Moscow state University Yu. Yu. Petrunin. ...
Added: February 23, 2016
Artificial Intelligence in Music, Sound, Art and Design: 12th International Conference, EvoMUSART 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings
Cham : Springer, 2023
This book constitutes the refereed proceedings of the 12th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2023, held as part of Evo* 2023, in April 2023, co-located with the Evo* 2023 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 7 short papers presented in this book were carefully reviewed ...
Added: April 4, 2023
Разработка и применение комплексных нейросетевых моделей массовой оценки и прогнозирования стоимости жилых объектов на примере рынков недвижимости Екатеринбурга и Перми
, , Имущественные отношения в Российской Федерации 2017 Т. 186 № 3 С. 68-84
Developed complex economic and mathematical models of mass valuation of residential real estate of cities of Yekaterinburg and Perm, which take into account both construction and operating parameters of the apartments, and the changing economic situation in the country and the world. Study models showed that the increase in new housing in Yekaterinburg, 4% in ...
Added: December 12, 2017
, , in : Advances in Intelligent Systems and Computing. Vol. 1037: Proceedings of the 2019 Intelligent Systems Conference (IntelliSys).: Switzerland : Springer, 2019.
Tensor Product Variable Binding is an important aspect of building the bridge between the connectionist approach and the symbolic paradigm. It can be used to represent recursive structures in the tensor form that is an acceptable form for neural networks that are highly distributed in nature and, therefore, promise computational benefits from using it. However, ...
Added: October 1, 2020
Method of calculating Lyapunov exponents for time series using artificial neural networks committees
, , et al., Days on Diffraction (DD) 2016 P. 127-132
The aim of this work is to develop a method for calculating all Lyapunov exponents from time series with high accuracy. To achieve this goal we propose a new method for determining the local and global Lyapunov exponents for a given time series. A special feature of the proposed method is the use of neural ...
Added: August 23, 2017
Методика создания комплексной экономико-математической модели массовой оценки стоимости объектов недвижимости на примере квартирного рынка города Перми
, , Вестник Пермского университета. Серия: Экономика 2016 № 2(29) С. 54-69
Currently, there are a number of economic and mathematical models designed for mass appraisal of real estate, tailored to their construction and performance properties, but taking no account of the evolving macroeconomic situation in the country and the world. The disadvantage of such static models is their rapid obsolescence, the need for constant updating, and ...
Added: February 15, 2017
Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish
, , in : Proceedings of Third Workshop "Computational linguistics and language science". Issue 4.: Manchester : EasyChair, 2019. P. 113-124.
Lemmatisation, which is one of the most important stages of text preprocessing, consists in grouping the inflected forms of a word together so they can be analysed as a single item. This task is often considered solved for most modern languages irregardless of their morphological type, but the situation is dramatically different for ancient languages. Rich inflectional system and ...
Added: December 12, 2018
, , et al., Всероссийский криминологический журнал 2015 Т. 9 № 3 С. 423-430
Modern criminalists do not share a common opinion regarding the choice of parameters which could be used to work out a system of characteristics to differentiate a maniac killer from an ordinary person. This hinders the development of efficient software for investigation purposes. The paper describes the experience of developing a neural network that can ...
Added: October 1, 2015
Классификация событий в системах обеспечения информационной безопасности на основе нейросетевых технологий
, , , Открытое образование 2019 № 23(1) С. 57-63
При решении сложных задач классификации зачастую ни один из используемых алгоритмов классификации не обеспечивает требуемой точности.В таких случаях строят композиции алгоритмов, в которых ошибки отдельных алгоритмов взаимно компенсируются. Рассматривается применение нейросетевого ансамбля для решения задач классификации событий безопасности в корпоративной информационной системе. Представлен краткий обзор существующих подходов к построению нейросетевых ансамблей и методов формирования решений задач, в которых используются нейросетевые классификаторы. ...
Added: February 22, 2020
, , in : Труды 6-й Международной научно-практической конференции студентов и аспирантов «Статистические методы анализа экономики и общества» (12-15 мая 2015 г.). : М. : Издательский дом НИУ ВШЭ, 2015. P. 18-19.
Using artificial neural network approach, the electricity price forecast model is created to predict the short-term dynamic of day-ahead electricity market (spot) prices in the European zone of Russian wholesale electricity market. Such model make a big contribution to reduce the uncertainty caused by recent liberalization of Russian power industry, which typically lead to high ...
Added: October 21, 2015
, , , , in : the 2014 Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA). : [б.и.], 2014.
This article presents the results of neural network technologies that are used and can be used in the information systems security. It focuses on two paradigms of neural networks: multilayer neural network and the Cerebellar Model Articulation Controller (the CMAC neural network). ...
Added: September 13, 2016
Новые возможности применения методов искусственного интеллекта для моделирования появления и развития заболеваний и оптимизации их профилактики и лечения
, , Терапия 2018 № 1(19) С. 109-118
This article is devoted to the methodological issues of the application of artificial intelligence techniques in preventive medicine. We showed a specific example of the neural network application allows not only to diagnose cardiovascular diseases, but also on a quantitative basis to predict their emergence and development in future periods of life. This allows you ...
Added: January 9, 2019
Towards Automatic Manipulation of Arbitrary Structures in Connectivist Paradigm with Tensor Product Variable Binding
, , in : Advances in Neural Computation, Machine Learning, and Cognitive Research III. : Springer, 2020. P. 375-383.
Building a bridge between symbolic and connectionist level of computations requires constructing a full pipeline that accepts symbolic structures as an input, translates them to distributed representation, performs manipulations with this representation equivalent to symbolic manipulations and translates it back to the symbolic structure. This work proposes neural architecture that is capable of joining two ...
Added: October 27, 2019
IEEE Computer Society, 2020
ICTAI 2020: The annual IEEE International Conference on Tools with Artificial Intelligence (ICTAI) provides a major international forum where the creation and exchange of ideas related to artificial intelligence are fostered among academia, industry, and government agencies. The conference facilitates the cross-fertilization of these ideas and promotes their transfer into practical tools, for developing intelligent systems ...
Added: January 30, 2021
, , et al., , in : 2022 International Siberian Conference on Control and Communications (SIBCON). : IEEE, 2022. Ch. 9438857. P. 1-6.
Added: October 11, 2021
The Parallel Approach to the Conjugate Gradient Learning Algorithm for the Feedforward Neural Networks
, , , Lecture Notes in Computer Science 2014 Vol. 8467 P. 12-21
This paper presents the parallel architecture of the conjugate gradient learning algorithm for the feedforward neural networks. The proposed solution is based on the high parallel structures to speed up learning performance. Detailed parallel neural network structures are explicitly shown. ...
Added: September 13, 2016