The empirical study of executive compensation in China port and shipping listed companies based on the grey relational analysis

Chen, Jiajia; Rong, Zhang; Liu, Bin

doi:10.1108/gs-09-2015-0069

Cited by 11 publications

(12 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Grey relational analysis is one of the grey system methods [17,18], which has been widely applied in various fields, such as economics [19], sociology [20], and environics [21]. Its basic idea is to determine the relational degree between two data sequences depending on the similarity of their geometric shapes.…”

Section: Grey Relational Analysismentioning

confidence: 99%

Risk Assessments of Water Inrush from Coal Seam Floor during Deep Mining Using a Data Fusion Approach Based on Grey System Theory

et al. 2020

View full text Add to dashboard Cite

With the increase in depth of coal mining, the hydrogeological complexity largely increases and water inrush accidents happen more frequently. For the safety of coal mining, horizontal directional drilling and grouting techniques have been implemented to detect and plug the fractures and conduits that deliver high-pressure groundwater to coal mine. Taking the grouting engineering performed at Xingdong coal mine at 980 m below sea level as an example, we collected the data of grouting quantity, the loss of drilling fluid, gamma value, water temperature, average water absorption, distance between grouting loss points, water pressure on coal seam floor, and aquifuge thickness at 90 boreholes in the mine to conduct grey relational analysis, first. The analysis showed that the grouting quantity was highly correlated with all other factors. Subsequently, grey system evaluation was used to evaluate the risk of water inrush from the coal seam floor. The results of risk analysis illustrated that three water inrushes from Ordovician limestone occurred in mining face 2127, 2125, and 2222 in the study area were all located in the area with a risk score higher than 65. Through grouting, the identified cracks were effectively blocked and waterproof layers beneath the coal seam floors were constructed to reduce the threat of water inrush. By comparing the risk assessment results with three water inrush cases before grouting operation, we found that water inrush areas were consistent with the area of higher risk.

show abstract

Section: Grey Relational Analysismentioning

confidence: 99%

Risk Assessments of Water Inrush from Coal Seam Floor during Deep Mining Using a Data Fusion Approach Based on Grey System Theory

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Grey relational analysis is a grey system method that has been widely applied in various fields, such as economics [26], sociology [27] and environics [28]. Its basic idea is to determine the relational degree between two data sequences, depending on the similarity of their geometric shapes [29].…”

Section: Grey Relational Analysis With Time Lagmentioning

confidence: 99%

Investigation of Karst Spring Flow Cessation Using Grey System Models

Guo

Yeh

Hao

2019

Water

View full text Add to dashboard Cite

Karst aquifers are prominent sources of water worldwide; they store large amounts of water and are known for their beautiful springs. However, extensive groundwater development and climate variation has resulted in a decline in the flow of most karst springs; some have even dried up. In order to obtain a better understanding of the factors contributing to this development, this study introduced grey system models, which quantified spring flow, taking Jinci Springs (China), which dried up in May 1994, as an example. Based on the characteristics of Jinci Springs, spring flow was divided into two stages: first (1954–1960), when the spring flow was affected only by climate variation; and second (1961–1994), when the flow was impacted by both climate variation and anthropogenic activities. The results showed that Jinci Springs flow had a strong relationship with precipitation occurring one year and three years earlier in the first stage. Subsequently, a grey system GM (1,3) model with one-year and three-year lags was set up for the first stage. By using the GM (1,3) model, we simulated the spring flow in the second stage under effects of climate variation only. By subtracting the observed spring flow from the simulated flow, we obtained the contribution of anthropogenic activities to Jinci Springs’ cessation. The contribution of anthropogenic activities and climate variation to the decline was 1.46 m3/s and 0.62 m3/s, respectively. Finally, each human activity that caused the decline was estimated. The methods devised herein can be used to describe karst hydrological processes that are under the effects of anthropogenic activities and climate variation.

show abstract

“…Grey relational analysis is one of grey system method, which has been widely applied in various fields, such as economics [26], sociology [27] and environics [28]. Its basic idea is to determine the relational degree between two data sequences, depending on the similarity of their geometric shapes [29].…”

Section: Grey Relational Analysis With Time Lagmentioning

confidence: 99%

Investigation of Karst Spring Flow Cessation Using Grey System Model

Guo¹,

Yeh²,

Hao³

2019

Preprint

View full text Add to dashboard Cite

Globally karst aquifers store large amount of precious water and create beautiful karst springs in many places. However, most of the karst springs flow declined, and some of the karst springs dried up with the effects of extensive groundwater development and climate variation. For example, Jinci Springs (China) is known for the beautiful landscape it created and large area of paddy fields it irrigated. Unfortunately, it dried up in May 1994. For better understanding of the hydrological processes of karst springs, this study introduced grey system models to quantify spring flow taking Jinci Springs as an example. Based on the characteristics of Jinci Springs flow, the spring flow was divided into two stages: the first stage (1954-1960), when the spring flow was affected only by climate variation; and the second stage (1961-1994), when the flow was impacted by both climate variation and anthropogenic activities. Results showed that the Jinci Springs flow had strong relations with precipitation occurring one year and three years earlier in the first stage. Subsequently, a grey system GM (1, 3) model with one-year and three-year lags was set up for the first stage. By using the GM (1, 3) model, we simulated the spring flow in the second stage under effects of climate variation only. Subtracting the observed spring flow from the simulated flow, we obtained the contribution of anthropogenic activities to Jinci Springs cessation. The contribution of anthropogenic activities and climate variation to Jinci Springs cessation was 1.46m3/s and 0.62m3/s, respectively. Finally, each human activity causing spring flow decline was estimated.

show abstract

The empirical study of executive compensation in China port and shipping listed companies based on the grey relational analysis

Cited by 11 publications

References 4 publications

Risk Assessments of Water Inrush from Coal Seam Floor during Deep Mining Using a Data Fusion Approach Based on Grey System Theory

Risk Assessments of Water Inrush from Coal Seam Floor during Deep Mining Using a Data Fusion Approach Based on Grey System Theory

Investigation of Karst Spring Flow Cessation Using Grey System Models

Investigation of Karst Spring Flow Cessation Using Grey System Model

Contact Info

Product

Resources

About