Open AccessCorrelation Analysis of Influencing Factors of Labor Education Level Based on Neural Network Model
Author(s) -
Yuliang Lu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/4/042096
Subject(s) - affect (linguistics) , correlation , positive correlation , economics , value (mathematics) , negative correlation , labour economics , work (physics) , demographic economics , psychology , medicine , engineering , mechanical engineering , geometry , mathematics , communication , machine learning , computer science
Based on the neural network model, this paper analyzes the correlation of influencing factors of labor education level. This paper compares the income changes of 23-30-year-old workers before and after receiving labor education and the changes of income influencing factors. The results show that the new labor market and the whole labor market show a trend of differentiation before and after education. In the background of the increasing role of the whole labor market education into income, the “value” of the education of the new labor force has declined. Among the various factors that affect the income of the new labor force, some of the education types with the same education level are greatly affected by the negative impact. Gender and work area play a more prominent role, while work experience and other factors have no significant correlation with income. The results have a certain reference value for the correlation study of influencing factors of labor education level.