Purpose

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is insufficient, or the decision objects vary.

Design/methodology/approach

Considering that the sample dependence of the ideal sequence selection in gray relational decision-making is based on case sampling, which causes the phenomenon of rank reversal, this study designs an ideal point diffusion method based on the development trend and distribution skewness of the sample information. In this method, a gray relational model for sample classification is constructed using a virtual-ideal sequence. Subsequently, an optimization model is established to obtain the criteria weights and classification radius values that minimize the deviation between the comprehensive relational degree of the classification object and the critical value.

Findings

The rank-reversal problem in gray relational models could drive decision-makers away from using this method. The results of this study demonstrate that the proposed gray relational model based on information diffusion and virtual-ideal sequencing can effectively avoid rank reversal. The method is applied to classify 31 brownfield redevelopment projects based on available interval gray information. The case analysis verifies the rationality and feasibility of the model.

Originality/value

This study proposes a robust method for ideal point choice when the decision information is limited or dynamic. This method can reduce the influence of ideal sequence changes in gray relational models on decision-making results considerably better than other approaches.

中文翻译：

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基于信息扩散和区间灰色关联分析的案例分类模型

目的

本研究的目的是构建基于信息扩散的灰色关联模型，以避免在可用决策信息不足或决策对象变化时出现秩反转。

设计/方法/方法

考虑到灰色关联决策中理想序列选择的样本依赖性是基于案例抽样的，会导致秩反转现象，本研究根据样本信息的发展趋势和分布偏度设计了一种理想点扩散方法。 . 该方法利用虚理想序列构建样本分类的灰色关联模型。随后，建立优化模型，得到使分类对象的综合关联度与临界值的偏差最小的准则权重和分类半径值。

发现

灰色关系模型中的秩反转问题可能会驱使决策者远离使用这种方法。本研究结果表明，所提出的基于信息扩散和虚拟理想排序的灰色关联模型可以有效避免秩反转。应用该方法基于可用区间灰色信息对31个棕地重建项目进行分类。案例分析验证了模型的合理性和可行性。

原创性/价值

当决策信息有限或动态时，本研究提出了一种用于理想点选择的稳健方法。与其他方法相比，该方法可以更好地降低灰色关联模型中理想序列变化对决策结果的影响。