基于梯形模糊语言变量的小企业信用评级

Liang Xue-chun, Dai Lan
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引用次数: 1

摘要

针对小企业信用信息多为定性信息的特点,提出了梯形模糊语言变量(tflv)对其进行描述。定义了TFLVs期望值的计算公式,研究了TFLVs的一些特性。基于期望值,提出了一种基于tflv的多属性决策方案排序方法。利用梯形模糊语言加权平均算子对决策信息进行聚合,通过比较tflv的期望值对所有备选方案进行排序,然后将期望值映射为信用评级。最后,以某商业银行小企业信用评级为例进行了实证分析,结果表明,该方法可以在不丢失语言信息的情况下轻松进行语言计算过程,从而使决策结果合理有效。本文构建了小企业信用评级的新框架和新视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Credit Rating of Small Business with Trapezoid Fuzzy Linguistic Variables
For the credit information of small business is mostly qualitative, trapezoid fuzzy linguistic variables (TFLVs) are brought forward to describe them. The formula of the expected value of TFLVs is defined, and some of its properties are studied. Based on the expected value, an approach to ranking the decision alternatives in multiple attribute decision making(MADM) with TFLVs is developed. A trapezoid fuzzy linguistic weighted averaging operator is utilized to aggregate the decision information, and all alternatives are ranked by comparison the expected value of TFLVs, then the expected value is mapped to credit rating. Finally, an empirical example about credit rating of small business from some commercial bank is illustrated, the results indicate that the method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision result reasonable and effective. This paper builds a new frame and view on credit rating of small business.
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