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Article
Publication date: 10 September 2024

Yanli Zhai, Gege Luo and Dang Luo

The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.

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Abstract

Purpose

The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.

Design/methodology/approach

Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.

Findings

The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.

Practical implications

The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM2.5, PM10 and O3 are the main pollutants affecting air quality in northern Henan.

Originality/value

This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.

Details

Grey Systems: Theory and Application, vol. 14 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 6 September 2018

Dang Luo, Lili Ye, Yanli Zhai, Hanyu Zhu and Qicun Qian

Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index…

148

Abstract

Purpose

Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index values have some grey multi-source heterogeneous characteristics. The purpose of this paper is to construct a grey projection incidence model (GPIM) to evaluate the hazard of the drought disaster characterised by the grey heterogeneity information.

Design/methodology/approach

First, the index system of the drought hazard risk is established based on the formation mechanism of the drought disaster. Then, the GPIM for the heterogeneous panel data is constructed to assess drought hazard of five cities in Henan Province. Subsequently, based on the assessment results, the grey clustering model is employed for the regional division.

Findings

The findings demonstrate that five cities in central Henan Province are divided into three categories, which correspond to three different risk grades, respectively. With respect to different drought risk areas, corresponding countermeasures and suggestions are proposed.

Practical implications

This paper provides a practical and effective new method for the hazard assessment on drought disaster. Meanwhile, these countermeasures and suggestions can help policy makers to improve the efficiency of drought resistance work and reduce the losses caused by drought disasters in Henan Province.

Originality/value

This paper proposes a new GPIM which resolves the assessment problems of the uncertain systems with grey heterogeneous information, such as real numbers, interval grey numbers and three-parameter interval grey numbers. It not only expands the application scope of the grey incidence model, but also enriches the research of panel data.

Details

Grey Systems: Theory and Application, vol. 8 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

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