Grey Relational Analysis on the Relationship between Economic Development and Carbon Emissions in Hubei Province

2014 ◽  
Vol 1073-1076 ◽  
pp. 2641-2647
Author(s):  
Yan Wen Liu ◽  
Zhi Chen ◽  
Xia Zhou
Keyword(s):  
Economic Development ◽  
Carbon Emissions ◽  
Grey Relational Analysis ◽  
Hubei Province ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Relational Analysis ◽  
Correlation Degree ◽  
Grey Relational ◽  
The Relationship

The problem about promoting the rapid economic growth while effectively reducing CO2 emission has aroused great attention of scholars both at home and abroad. Researches show that there are differences in the relationship between economic development and carbon emissions in the different historical stages of the different regions. This paper took Hubei Province as the survey region, by means of the decomposition model of CO2 emissions, accurately calculated CO2 emissions from 2001 to 2010 in Hubei Province, selected Hubei Province’s GDP and the three industries’ GDP as indicators of economic development, used the method of grey relational analysis to calculate grey correlation degree of Hubei Province’s GDP, three major industries’ GDP and CO2 emissions, carried on the comparative analysis of the relationship between economic development and CO2 emissions of Hubei Province in combination with China’s corresponding results, specifically put forward policy suggestions on energy conservation and emissions reduction in Hubei Province, so as to provide the theoretical reference for the development of low carbon economy in Hubei Province.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Grey relational analysis between Turkey’s macroeconomic indicators and domestic savings

2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran
Keyword(s):  
Grey Relational Analysis ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Domestic Savings ◽  
Macroeconomic Indicators ◽  
Private Savings ◽  
Grey Relational ◽  
High Degree ◽  
The Relationship

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

scholarly journals Research on the Comprehensive Evaluation of Low Carbon Economic Development in Shandong Province Based on the Weighted Gra-topsis Method

2020 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
Xingle Teng ◽  
Jian Rong
Keyword(s):  
Economic Development ◽  
Comprehensive Evaluation ◽  
High Energy ◽  
Shandong Province ◽  
Low Carbon ◽  
Topsis Method ◽  
Low Carbon Economy ◽  
Development Level ◽  
Correlation Degree ◽  
Carbon Economy

This paper starts from the analysis of the connotation of low-carbon economy, and establishes the evaluation index system of regional low-carbon economic development level. The main research content is to determine the index weight, judge the correlation degree and sort the decision-making units by entropy method, grey correlation analysis and TOPSIS method, and finally make a comprehensive evaluation of the low-carbon economic development level of Shandong Province. The conclusion shows that the development level of low-carbon economy in Shandong Province shows a good trend year by year, but the consumption dependence on high energy consumption resources and backward ecological benefits are increasingly becoming the bottleneck of the development of low-carbon economy in Shandong Province.

Research of the Relationship between Hemp Fiber Disintegration Degree and its Chemical Composition

2012 ◽  
Vol 482-484 ◽  
pp. 2531-2534
Author(s):  
Ying Chao Ji ◽  
Fei Wang ◽  
Yu Jia Liang ◽  
Dan Yue Li
Keyword(s):  
Chemical Composition ◽  
Mathematical Models ◽  
Grey Relational Analysis ◽  
Theoretical Basis ◽  
Hemp Fiber ◽  
Relational Analysis ◽  
Degumming Process ◽  
Grey Relational ◽  
The Relationship ◽  
Selection Of

In order to solve the problem of degumming and short yarn of the hemp fiber, this paper mainly research the relationship between hemp fiber disintegration degree and its chemical composition. Then discuss how the contents of pectin, hemicellulose, cellulose and lignin in hemp fiber could affect the hemp fiber disintegration degree. Calculate and analysis the four factors’ affection degree by Grey Relational Analysis, and build four mathematical models between hemp fiber disintegration degree and each of its content at last. This paper makes a contribution to provide the theoretical basis to the degumming process of hemp fiber and the selection of spinning material.

The Influencing Factor Analysis of "Three Wastes" Emissions in Inner Mongolia

2013 ◽  
Vol 864-867 ◽  
pp. 1369-1378
Author(s):  
Yu Chen Song ◽  
Qian Wang ◽  
Xiao Bing Li ◽  
Zhen Hua Yang
Keyword(s):  
Waste Water ◽  
Economic Development ◽  
Grey Relational Analysis ◽  
Inner Mongolia ◽  
Industrial Waste ◽  
Coal Consumption ◽  
Waste Gas ◽  
Relational Analysis ◽  
Waste Solid ◽  
Grey Relational

As the economy grows rapidly, Inner Mongolia is faced with more and more serious environmental problems, which cast a large shadow on the ecological system, health and economic development. Environmental problems have become the biggest restricting factor for economic growth and the sustainable development of society in Inner Mongolia. This paper uses three wastes emissions as a research object and adopts the method of grey relational analysis, and selects the indexes of economic development level, science and technology input and policy level, energy consumption level, then performs grey relational analysis for waste water, waste gas and waste solid. The research results show that economic development has the greatest influence on the emissions of industrial waste water and waste solid; coal consumption has the biggest effect on the emissions of industrial waste gas, meanwhile coal consumption also has a big impact on the emissions of waste water and waste solid.

An Empirical Study on China's Energy Consumption, Carbon Emissions and Economic Growth

2013 ◽  
Vol 869-870 ◽  
pp. 377-380
Author(s):  
Meng Hui Liu ◽  
Kun Kun Xue
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Empirical Investigation ◽  
Var Model ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Negative Effect ◽  
The Relationship ◽  
Carbon Economy

With the development of low-carbon economy, it is necessary to explore the relationship between energy consumption, carbon emissions and the economic growth correctly. In this paper, the VAR model was proposed with analyzing the relationship between the three factories through pulse response graph. Through the empirical investigation, the result shows: increasing energy consumption can promote economic growth, while the increasing consumption will also raise emissions of carbon. However, the emissions of carbon have negative effect on economic growth. Therefore, we must correctly handle the relationship between the three factories. Thus, it offers the best way to develop the economic in this paper is to develop the low carbon economy.

Sign in / Sign up

Export Citation Format

Share Document