Abstract
According to the theory that the degree of education of workers in educational economics has a certain positive relationship with social labor productivity, the fuzzy system and neural network modeling mechanism are used to establish the fuzziness of laborers’ education level to social productivity (per capita national income). This article combines fuzzy theory and neural network theory to construct an empirical model for the analysis of the contribution of education economy and conduct an empirical analysis of statistical data from 2010 to 2020. Analysis shows that there is a great correlation between per capita years of education and per capita GDP, especially the number of college students per million people has a greater correlation with per capita GDP. This fully confirms that economic growth is increasingly dependent on education, especially higher education. The main body of this article is the improvement of the measurement model and the calculation of the contribution of our country’s education to economic growth using the fuzzy neural network measurement model. The final empirical conclusion shows that education has a significant role in promoting the development of our country’s economy.
Highlights
Based on the basic theories of Marxism, drawing on the useful experience of Western economics and combining the reality of our country’s education and economic development, they proposed the statistical measurement method of “education-labor productivity-economic development” [1].ese methods have promoted the development of educational economics and added new content to the development of economics itself
As the cornerstones of educational economics, these theories and methods have a strong guiding significance for guiding us to understand the economic meaning of education, regardless of the past, present, or future. e basic theory of educational economics points out that “Educational economic value’ is understood as the effect created by educational labor, which can promote social and economic growth and development and meet people’s material and spiritual needs, which is condensed in the product of educational labor [2].”
In addition to its rapid local education development, it has used the economic value condensed by foreign laborers for free; the economic development of Western countries is even more important
Summary
Based on the basic theories of Marxism, drawing on the useful experience of Western economics and combining the reality of our country’s education and economic development, they proposed the statistical measurement method of “education-labor productivity-economic development” [1]. In addition to its rapid local education development, it has used the economic value condensed by foreign laborers for free; the economic development of Western countries is even more important In this way, there have been ups and downs, the economic role of education-sustainable development of productivity has been stable. E impact of education on economic growth is a typical social and economic problem Its complexity makes it difficult to apply certain deterministic mathematical methods, and in many cases, we cannot construct a deterministic structural model of the relationship between the two. Based on the basic theories of educational economics, this paper uses fuzzy neural network methods to study the mapping relationship between laborers’ education level and social productivity (per capita national income) and soft-calculates the increase in national income caused by the increase in laborers’ education level. Is paper uses statistical data from 2010 to 2019, and the analysis shows that there is a great correlation between per capita years of education and per capita GDP, especially the number of college students per million people has a greater correlation with per capita GDP. is fully confirms that economic growth is increasingly dependent on education, especially higher education. e improvement of various measurement models and the use of fuzzy neural network measurement models to calculate the contribution of the education to economic growth constitute the main content of this thesis. rough three-stage indicator selection and neural network training, the final empirical conclusions show that education has a significant role in promoting the development of my country’s economy
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