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Enhanced grey relational analysis for structural relationship: an application to economic structure classification
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AI
DOI：10.1080/01605682.2025.2554747.png)
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Abstract
En 中文
Grey relational analysis (GRA) evaluates the relationship between system variables. However, it is challenging to assess the structure relationship between systems represented by compositional data sequences with fixed sum constraints. To address this issue, the structural correlation degree is studied using the construction concept of Deng's grey relational degree. First, the point correlation difference in Deng's correlation is replaced by Aitchison distance to measure the difference between compositional data structures, thereby constructing a novel grey structural relational analysis model based on compositional data with consistent structure. Second, an arithmetic example of the novel model is designed to demonstrate its detailed calculation process. Finally, based on the economic structure data of three major industries from 1998 to 2022, an example analysis of the economic structure correlation between provinces and cities in East China is conducted to show the practicability of the proposed method. This model enriches the analysis of inter-system correlation and broadens the application scope of the GRA model.
Keywords:
Data analytics
grey structural correlation
grey relational analysis
time series
economic structure
classification
Journal
IF:
2.7
Papers:
390
Citations:
9.2K