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Analysis of Rural Talent Scale in Hebei Province Based on Fractional GM (1,1) and the Grey Relational Analysis Model

Authors :
Kuo Xiao
Wenbin Bi
Yibo Li
Chaoyong Tang
Huan Li
Shi Yin
Source :
Journal of Mathematics, Vol 2021 (2021)
Publication Year :
2021
Publisher :
Hindawi Limited, 2021.

Abstract

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.

Details

ISSN :
23144785 and 23144629
Volume :
2021
Database :
OpenAIRE
Journal :
Journal of Mathematics
Accession number :
edsair.doi.dedup.....6feb8b6fa7b3fa0a4b9d8b0e6a42e3d7