A New Computational Method Based on Probabilistic Linguistic Z-Number With Unbalanced Semantics and Its Application to Multi-Criteria Group Decision Making
نویسندگان
چکیده
Z-number that proposed by Zadeh is an effective tool to describe the information with uncertainty in decision-making problems. However, most of researches on Z-numbers employed linguistic cardinalities uniformly distributed scales. In fact, unbalance situation much common terms psychology experts. this paper, we propose a new computational method based Probabilistic Linguistic Unbalanced semantics(UPLZ), which can represent evaluations experts precisely combined individual risk appetite. A score function UPLZs provided hesitant degree and scale reduce complexity. Afterward, linear programming constructed determine weights criteria considering cross entropy maximization. The robust decision result be obtained applying MULTIMOORA since it specific peculiarities three subordinate models. Finally, case study concerning medicine selection for patients mild symptoms COVID-19 illustrate feasibility effectiveness method. advantages are highlighted sensitivity analysis comparative two outstanding multi-criteria methods.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2020.3047937