casa 24(1):

Editorial

Toward Modeling Linguistic Fuzzy Spanning Trees Based on Hedge Algebra

Download22 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetcasa.7337,
    author={Nguyen Van Han},
    title={Toward Modeling Linguistic Fuzzy Spanning Trees Based on Hedge Algebra},
    journal={EAI Endorsed Transactions on Contex-aware Systems and Applications},
    volume={10},
    number={1},
    publisher={EAI},
    journal_a={CASA},
    year={2024},
    month={9},
    keywords={Linguistic Fuzzy Maximum Spanning Tree, Hedge Algebra, Fuzzy graph, Linguistic Variables},
    doi={10.4108/eetcasa.7337}
}
  • Nguyen Van Han
    Year: 2024
    Toward Modeling Linguistic Fuzzy Spanning Trees Based on Hedge Algebra
    CASA
    EAI
    DOI: 10.4108/eetcasa.7337
Nguyen Van Han1,*
  • 1: Trường ĐH Nguyễn Tất Thành
*Contact email: nvhan@ntt.edu.vn

Abstract

This paper presents an innovative approach to modeling Linguistic Fuzzy Maximum Spanning Trees (L-FMSTs) using Hedge Algebra (HA). HA provides a robust framework for quantifying linguistic terms, which is essential for handling the vagueness inherent in natural language. By integrating HA with L-FMSTs, we aim to enhance the interpretability and performance of fuzzy systems in applications requiring complex decision-making and optimization.

Keywords
Linguistic Fuzzy Maximum Spanning Tree, Hedge Algebra, Fuzzy graph, Linguistic Variables
Received
2024-08-16
Accepted
2024-09-11
Published
2024-09-27
Publisher
EAI
http://dx.doi.org/10.4108/eetcasa.7337

Copyright © 2024 Nguyen Van Han, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.