Original scientific paper

https://doi.org/10.17559/TV-20240905001968

Advanced Decision-Making with Interval-Valued Probabilistic Linguistic Fuzzy Sets

Xun Zhang ; School of Economics and Management, Beijing Jiaotong University, 100044, Beijing, China *

* Corresponding author.

Abstract

Decision-making under uncertainty is a fundamental challenge in various fields, requiring methods that effectively capture probabilistic uncertainty and decision-maker hesitancy. This study introduces Interval-Valued Probabilistic Uncertain Linguistic q-Rung Orthopair Fuzzy Sets (IVPULq-ROFSs), a novel framework that extends existing fuzzy set models by incorporating interval-valued probabilities and linguistic hesitancy. Based on this model, we develop two advanced Multi-Attribute Group Decision-Making (MAGDM) methods: (1) an aggregation-based approach, and (2) a TODIM-based decision method. To validate the effectiveness of the proposed methods, we apply them to autonomous vehicle sensor configuration selection, demonstrating enhanced decision robustness and reliability. The results indicate that IVPULq-ROFSs outperform conventional fuzzy models in handling complex and uncertain decision scenarios. Future research will explore algorithmic optimization, real-time applications, and integration with deep learning models for enhanced decision intelligence.

Keywords

autonomous vehicle sensor configurations; hesitancy degrees; interval-valued probabilistic uncertain linguistic q-rung orthopair fuzzy sets; multi-attribute group decision-making

Hrčak ID:

342640

URI

https://hrcak.srce.hr/342640

Publication date:

31.12.2025.

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