Development of Software to Test Transitivity of Fuzzy Relations

 
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Abstract

The problem of fuzzy relation transitivity checking and transitive closure finding is considered in the paper. Solution algorithms are formulated and corresponding software is described. A logical scheme is given.

General Information

Keywords: fuzzy relations, transitivity, transitive closure

Journal rubric: Optimization Methods

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OpenAlex trends: Mathematical Control Systems and Analysis, Advanced Computational Techniques in Science and Engineering, Advanced Data Processing Techniques

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Number of citations: 0

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Mathematical Control Systems and Analysis

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Advanced Computational Techniques in Science and Engineering

This cluster of papers focuses on the intersection of Internet of Things (IoT) and healthcare systems, including topics such as remote monitoring, algorithmic modeling, wireless sensor networks, telemedicine, biomedical signal processing, and digital information management. The papers also touch upon the application of IoT in smart city healthcare systems and the use of corpus analysis in technical writing classrooms.

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Advanced Data Processing Techniques

This cluster of papers focuses on the modeling and control of multidimensional systems, with an emphasis on redundant transmission, fuzzy controller adaptation, fault tolerance, real-time systems, and energy efficiency in various domains such as cyber-physical systems, network traffic analysis, and industrial automation.

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Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2023130104

Received 18.01.2023

Accepted

Published

For citation: Smerchinskaya, S.O., Kiselev, D.M. (2023). Development of Software to Test Transitivity of Fuzzy Relations. Modelling and Data Analysis, 13(1), 36–43. (In Russ.). https://doi.org/10.17759/mda.2023130104

© Smerchinskaya S.O., Kiselev D.M., 2023

License: CC BY-NC 4.0

References

  1. Smerchinskaya S.O., Yashina N.P. Agregirovanie nechetkih otnosheniy strogogo poryadka [Aggregation of strict order fuzzy relations]. Izvestiya vysshih uchebnyh zavedenij. Matematika. [News of Higher Education Institutions. Mathematics.], 2022, no. 7, pp. 30-43.
  2. Guseva A.I., Tikhomirova A.N. Diskretnaya matematika dlya informatikov i economistov: Uchebnoe posobie. [Discrete mathematics for Computer Scientists and Economists: Textbook]. ‒Moscow: Publ. NRNU MEPhI, 2010, pp. 260-264. (In Russ.).
  3. Gubko M.V. Lekcii po prinyatiyu resheniy v usloviyah nechetkoy informacii. Versiya 1. [ Lectures on decision-making in a fuzzy information environment. Version 1.]. ‒Moscow.: ICS RAS, 2004. Available at: http://www.aup.ru/files/m539/m539.pdf (Accessed 19.01.2023). (In Russ.).

Information About the Authors

Svetlana O. Smerchinskaya, Candidate of Science (Physics and Matematics), Associate Professor, Department of Mathematical Cybernetics, Institute of Computer Science and Applied Mathematics, Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0003-0614-1835, e-mail: svetlana_os@mail.ru

Daniil M. Kiselev, Graduate Student of the Institute of Computer Sciences and Applied Mathematics, Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-4509-3533, e-mail: kiselevdaniilm@gmail.com

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