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• W4380740034 abstract "The change from multi-attribute decision-making (MADM) to multi-attribute group decision-making (MAGDM) has led to a doubling of data volume and a trend toward multi-attribute large group decision-making. At this time, operators need to be used to integrate these data, while also reflecting the psychological impact of decision-makers. Linguistic Z-number (LZN) is widely used for evaluating fuzzy information due to its unique flexibility and accuracy. However, in the LZN environment, aggregation operators, as an important component of decision-making, also have some shortcomings. Some aggregation operators currently used in LZN environments have low flexibility, high computational complexity, and are not convenient. This article cleverly utilizes Aczel Alsina t-norm and t-norm to obtain some aggregation operators with good algebraic properties, and proves these properties, which can also reflect the psychological influence of decision-makers. On this basis, we obtained a MAGDM model and successfully applied it in the following example, comparing it with other operators and verifying its superiority." @default.
• W4380740034 created "2023-06-16" @default.
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• W4380740034 date "2023-09-01" @default.
• W4380740034 modified "2023-10-06" @default.
• W4380740034 title "Novel Aczel-Alsina operations-based linguistic Z-number aggregation operators and their applications in multi-attribute group decision-making process" @default.
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• W4380740034 doi "https://doi.org/10.1016/j.engappai.2023.106541" @default.
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