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Fuzzy Information Evolution with Three-Way Decision in Social Network Group Decision-Making

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022695" target="_blank" >RIV/62690094:18450/25:50022695 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/11177555" target="_blank" >https://ieeexplore.ieee.org/document/11177555</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TFUZZ.2025.3614003" target="_blank" >10.1109/TFUZZ.2025.3614003</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fuzzy Information Evolution with Three-Way Decision in Social Network Group Decision-Making

  • Original language description

    In group decision-making (GDM) scenarios, uncertainty, dynamic social structures, and vague information present challenges for traditional opinion dynamics models. To address these issues, this study proposes a novel social network group decision-making (SNGDM) framework that integrates three-way decision (3WD) theory, dynamic network reconstruction, and linguistic opinion representation. First, the 3WD mechanism is introduced to explicitly model hesitation and ambiguity in agent judgments, thereby preventing irrational decisions. Second, a connection adjustment rule based on opinion similarity is developed, enabling agents to adaptively update their communication links and better reflect the evolving nature of social relationships. Third, linguistic terms are used to describe agent opinions, allowing the model to handle vague and incomplete information more effectively. Finally, an integrated multi-agent decision-making framework is constructed, which simultaneously considers individual uncertainty, opinion evolution, and network dynamics. The proposed model is applied to a multi-UAV cooperative decision-making scenario, where simulation results and consensus analysis demonstrate its effectiveness. Experimental comparisons further verify the algorithm&apos;s advantages in enhancing system stability and representing realistic decision-making behaviors. © 1993-2012 IEEE.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Transactions on Fuzzy Systems

  • ISSN

    1063-6706

  • e-ISSN

    1941-0034

  • Volume of the periodical

    33

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    14

  • Pages from-to

    4331-4344

  • UT code for WoS article

    001630903600010

  • EID of the result in the Scopus database

    2-s2.0-105017258314