Purpose

This paper aims to deal with the grey relational problem of panel data with an attribute value of interval numbers. The grey relational model of interval number for panel data is constructed in this paper.

Design/methodology/approach

First, three kinds of interval grey relational operators for the behavior sequence of a dimensionless system are proposed. At the same time, the positive treatment method of interval numbers for cost-type and moderate-type indicators is put forward. On this basis, the correlation between the three-dimensional interval numbers of panel data is converted into the correlation between the two-dimensional interval numbers in time series and cross-sectional dimensions. The grey correlation coefficients of each scheme and the ideal scheme matrix are calculated in the two dimensions, respectively. Finally, the correlation degree of panel interval number and scheme ordering are obtained by arithmetic mean.

Findings

This paper proves that the grey relational model of the panel interval number still has the properties of normalization, uniqueness and proximity. It also avoids the problem that the results are not unique due to the different orders of objects in the panel data.

Practical implications

The effectiveness and practicability of the model is verified by taking supplier selection as an example. In fact, this model can also be widely used in agriculture, industry, society and other fields.

Originality/value

The accuracy of the relational results is higher and more accurate compared with the previous studies.

中文翻译：

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面板数据区间数的灰色关联模型研究

目的

本文旨在处理具有间隔号属性值的面板数据的灰色关联问题。建立了面板数据区间数的灰色关联模型。

设计/方法/方法

首先，针对无量纲系统的行为序列，提出了三种区间灰色关联算子。同时提出了成本型和中型型指标区间数的积极处理方法。在此基础上，将面板数据的三维间隔号之间的相关性转换为时间序列中的二维间隔号与横截面尺寸之间的相关性。分别在二维中计算每个方案的灰度相关系数和理想方案矩阵。最后，通过算术平均值获得面板区间数与方案排序的相关度。

发现

本文证明了面板区间数的灰色关联模型仍然具有归一化，唯一性和邻近性的性质。还避免了由于面板数据中对象顺序不同而导致结果不唯一的问题。

实际影响

以供应商选择为例，验证了模型的有效性和实用性。实际上，该模型也可以广泛用于农业，工业，社会等领域。

创意/价值

与以前的研究相比，关系结果的准确性更高，更准确。