A picture fuzzy multi-attribute decision-making approach based on Hamacher Muirhead mean operators

IF 5.5 0 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Granular Computing Pub Date : 2024-06-08 DOI:10.1007/s41066-024-00486-2
Shumaila Javeed, Mubashar Javed, Atif Jameel, T. Senapati
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基于 Hamacher Muirhead 均值算子的图片模糊多属性决策方法
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来源期刊
Granular Computing
Granular Computing Multiple-
CiteScore
10.70
自引率
23.60%
发文量
49
期刊介绍: Granular Computing constitutes an extensive body of knowledge, which dwells upon individual formalisms of information granules (established within various settings including set theory, interval calculus, fuzzy sets, rough sets, shadowed sets, probabilistic granules) and unifies them to form a coherent methodological and developmental environment. Granular Computing is about formation, processing and communicating information granules.
期刊最新文献
A picture fuzzy multi-attribute decision-making approach based on Hamacher Muirhead mean operators Multi-attribute decision-making using (p, q)-rung orthopair fuzzy Hamacher interactive aggregation operators Multiattribute group decision-making based on weighted correlation coefficient of linguistic q-rung orthopair fuzzy sets and TOPSIS method Partitioned Hamy mean aggregation for multi-criteria group decision-making in the MAIRCA framework with $${\textsf {q}}$$-rung orthopair fuzzy 2-tuple linguistic information Multiple attribute group decision-making based on the ExpTODIM method and linguistic Pythagorean operators
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