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A novel hesitant fuzzy tensor-based group decision-making approach with application to heterogeneous wireless network
Muhammad Bilal1, Ioan Lucian-Popa2,3
1School of Mathematics and Statistics, Yunnan University, Kunming, 650106, China. bilalmaths28@gmail.com.
Scientific Reports
|August 21, 2025
Summary
This study introduces the Hesitant Fuzzy Tensor (HFT), a new method for handling uncertainty in expert decisions. HFT effectively analyzes complex data for better group decision-making in uncertain environments.
Area of Science:
- Decision Sciences
- Information Theory
- Computer Science
Background:
- Traditional decision models struggle with vagueness and expert hesitation.
- Representing multiple, uncertain expert opinions requires advanced frameworks.
Purpose of the Study:
- Introduce the Hesitant Fuzzy Tensor (HFT) as a novel multidimensional tool.
- Develop theoretical foundations and a decision-making algorithm for HFT.
- Apply HFT to optimize heterogeneous wireless communication network selection.
Main Methods:
- Formal definition and development of Hesitant Fuzzy Tensor (HFT) operations.
- Formulation of a group decision-making algorithm using HFT aggregation operators.
- Empirical evaluation of HFT in selecting wireless communication networks.
Main Results:
- HFT effectively captures and represents hesitation in expert judgments.
- The HFT-based algorithm demonstrates robustness and interpretability.
- Successful application in selecting optimal wireless networks under uncertainty.
Conclusions:
- HFT provides a scalable and realistic tool for uncertainty-based decision analysis.
- This research advances hesitant fuzzy modeling for complex technological domains.
- The proposed framework enhances group decision-making in uncertain environments.
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