Purpose

With the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (ε_ij), relative degree of grey incidence (r_ij) or synthetic degree of grey incidence (ρ_ij) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.

Design/methodology/approach

To achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).

Findings

It turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.

Research limitations/implications

Limitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.

Originality/value

In this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.

中文翻译：

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灰色相对发生率评价

目的

利用灰色关联度分析（GIA），计算绝对灰色关联度（ ε _ij）、相对灰色关联度（r _ij）或综合灰色关联度（ρ _{ij ）等指标。}然而，计算它们时所做的一些假设似乎是有争议的，这也可能对测试结果的可靠性产生重大影响。在本文中，作者分析了GIA的指标之一，即灰色发生率的相对程度。文章的目的是验证假设：在确定灰色关联度的相对程度时，系列元素标准化的方法显着影响检验结果。

设计/方法论/途径

为了达到本文的目的，作者使用了数值模拟方法和逻辑分析方法（以便从我们的测试中得出结论）。

发现

结果表明，计算灰色关联度相对度时所采用的元素串联标准化方法对检验结果有显着影响。此外，原始方法中使用的标准化方式（涉及将所有元素除以第一个元素）并不是最好的。通过将所有元素除以其算术平均值的标准化可以获得更可靠的结果。

研究局限性/影响

所进行的评估的局限性尤其涉及推理范围的有限。这是因为获得的结果仅涉及归入 GIA 的指标之一。

原创性/价值

在本文中，作者评估了确定灰色关联度相对程度的 GIA 模型。作为研究的结果，作者提出了关于改变变量标准化方法的建议，这将有助于利用灰色系统理论在关系检验中获得更可靠的结果。