The grey relational analysis on industrial structure and employment structure in Hebei Province

Author(s):  
Fan Yin ◽  
Hui Tian ◽  
Yan Cui ◽  
Fan Jin
2013 ◽  
Vol 726-731 ◽  
pp. 3521-3525 ◽  
Author(s):  
Zhi Wei Xu

Jing-Jin-Ji region of China is facing a contradiction between economic development and water resource shortage. The basic work to strengthen water resource management is finding out what the relation between industrial structure and water resource consumption is. The article measures the correlation by the grey relational analysis. The result is that Hebei province has a lowest grey relational grade in primary industry. Tianjin and Beijing has a relatively weak correlation in secondary industry and tertiary industry separately. The conclusion provides a direction for water resource optimization and cooperation within the region.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yibo Li ◽  
Wenbin Bi ◽  
Kuo Xiao ◽  
Huan Li ◽  
Shi Yin ◽  
...  

Talents are the key of rural revitalization. Under the background of Beijing-Tianjin-Hebei Coordinated Development, Hebei Province has always put talent revitalization at the core of rural revitalization. In order to promote the process of rural revitalization in Hebei Province, it is very important to understand the scale of rural talents. Firstly, the GM (1,1) model was used to predict the scale of rural talents in Hebei Province from 2020 to 2025. The prediction results showed that, in the rural development of Hebei Province in the next few years, the scale of production-oriented talents would gradually decline, while the scale of service-oriented, business-oriented, management-oriented, and skilled talents would show varying degrees of growth. Secondly, the grey relational analysis was used to analyze the importance of different factors for rural talents. Through the grey relational analysis, it was found that the infrastructure had the greatest impact on production-oriented talents, the agricultural industrialization operating rate had the strongest impact on service-oriented talents, and the urban-rural income level had the greatest impact on business-oriented talents, management-oriented talents, and skilled talents. Finally, according to the results of the GM (1,1) model and grey relational analysis, aiming at different types of rural talents, this paper puts forward countermeasures and suggestions from the aspects of strengthening rural infrastructure construction, improving rural medical and health conditions and improving income distribution pattern.


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