元组
可靠性(半导体)
排名(信息检索)
操作员(生物学)
计算机科学
理性
基于规则的机器翻译
模糊逻辑
数据挖掘
表(数据库)
产品(数学)
人工智能
数学
机器学习
功率(物理)
法学
化学
抑制因子
基因
物理
离散数学
转录因子
量子力学
生物化学
政治学
几何学
作者
Yuan Zhong,Guofa Li,Chuanhai Chen,Tongtong Jin,Yan Liu
标识
DOI:10.1109/tr.2022.3177941
摘要
Reliability allocation is a significant link in product design. To solve the problems of poor rationality of data use, considerable difficulty of calculation using existing methods, low accuracy of results, and weak ability of experts to express and process fuzzy information, this article proposes a reliability allocation method for the initial stage of product design based on the 2-tuple linguistic weighted Muirhead mean (2TLWMM) operator and 2-tuple linguistic best-worst method (2TLBWM). The 2TLBWM introduces 2-tuple linguistic to enhance the experts' ability to express fuzzy information. The 2TLWMM operator is used to judge the reliability index ranking of each subsystem, thereby improving the rationality of scoring data, providing a basis for experts to establish the comparison vector table, and reducing the influence of experts' subjective factors. Experts use 2TLBWM, refer to the ranking results of subsystem reliability index, only need to establish a contrast vector table, and can calculate the weight of the subsystem, thereby reducing the number of comparisons between elements and computational complexity. The advantages of the proposed method are illustrated by a specific case.
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