由多功能元件组成的可重构系统的逻辑概率建模与结构分析

IF 0.7 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-04-10 DOI:10.1134/s1054661824010218

Sergo Tsiramua, Hamlet Meladze, Tinatin Davitashvili

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引用次数: 0

摘要

摘要多功能元件是一类特殊的元件，其可靠性模型不同于经典的两极 "开-关 "模型。多功能元件除了非错误状态和错误状态外，还可以有部分错误状态。元件的多功能性导致形成具有可重新配置结构的灵活、适应性强的系统，在这种系统中，当元件出现部分故障时，可以通过重新分配元件之间的功能，使系统继续成功运行。本文讨论了多功能元件（MFE）和在其基础上组装的系统的特性、结构分析方法、逻辑-概率可靠性模型以及基于多功能元件的系统优化重组问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Logical-Probabilistic Modeling and Structural Analysis of Reconfigurable Systems Composed of Multifunctional Elements

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Logical-Probabilistic Modeling and Structural Analysis of Reconfigurable Systems Composed of Multifunctional Elements

Abstract

Multifunctional elements are a special class of elements, the reliability model of which differs from the classical two-pole “on-off” model. A multifunctional element can have partly false states in addition to nonfalse and false states. The multifunctionality of the elements leads to the formation of flexible, adaptable systems with reconfigurable structure, in which, in case of partial failure of the element, it is possible to continue the successful functioning of the system by redistributing the functions between the elements. In this paper, the properties of multifunctional elements (MFE) and systems, assembled on their basis, methods of structural analysis, logical-probabilistic reliability models and issues of optimal reconfiguration of systems based on MFE are discussed.

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来源期刊

PATTERN RECOGNITION AND IMAGE ANALYSIS Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

1.80

自引率

20.00%

发文量

期刊介绍： The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.