基于不完全三角模糊数判断矩阵的单方案评价新方法

Qianfang Xiang, Wei Li, Lei Wang
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引用次数: 2

摘要

在仿真可信度评价问题中,专家的偏好信息以不完全三角模糊数判断矩阵(ITFNJM)的形式存在,本文研究了一种针对单一方案评价的指标聚合新方法。首先定义三角模糊数(TFN)的不确定度和Hausdorff距离。然后,将基于不完全三角模糊数判断矩阵计算的专家客观权重与基于凸组合的专家主观权重聚合为专家综合权重(ESW)。其次,利用专家综合权值(ESW)建立最小二乘决策模型(LSDM)确定指标权重,并进一步提出了不完全三角模糊数判断矩阵的指标聚合方法。最后通过数值算例验证了所提方法的合理性和有效性。
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A New Evaluation Method for Single Scheme Based on Incomplete Triangular Fuzzy Numbers Judgment Matrix
Expert's preference information is in the form of incomplete triangular fuzzy numbers judgment matrix (ITFNJM) in the problem of simulation credibility evaluation, a new method of index aggregation focused on the evaluation for single scheme is investigated in this paper. First, the uncertainty degree and Hausdorff distance of triangular fuzzy number (TFN) are defined. Then, the expert's objective weight which is calculated based on the incomplete triangular fuzzy number judgment matrix and the subjective weight are aggregated into an expert's synthesis weight (ESW) based on convex combination. Next, a least square decision model (LSDM) is established with the expert's synthesis weight (ESW) to determine the index weight, and a method for index aggregation with incomplete triangular fuzzy number judgment matrix is further proposed. Finally a numerical example is illustrated to validate the reasonableness and effectiveness of the proposed method.
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