Demand Analysis of Employment Talents based on Deep Learning

Abstract

This paper forecasts the demand of urban talents in the future years from the perspective of urban talent demand and employment situation of Chinese students. To a certain extent, there is a relationship between the supply of talents in cities and the demand for talents in China. Artificial neural network is a kind of nonlinear system which contains some simple nonlinear connection points or calculation modules. BP neural network is one of the most widely studied and widely used artificial neural networks. BP neural network includes input layer and output layer, which overcomes the shortcomings of traditional evaluation methods and enriches the relevant evaluation methods. The evaluation results can truly map the nonlinear relationship among various analysis indexes. BP neural network model is suitable for nonlinear sample analysis and belongs to quantitative analysis. The grey prediction model belongs to qualitative analysis, which can predict the future development trend of the analysis object, and does not require high data. Therefore, this paper uses the combination of BP neural network model and gray prediction model to predict the talent demand of China’s College Students employment market reasonably and effectively, and finally analyzes the reliability of the prediction results. According to the prediction results, this paper puts forward the development strategy for the city, in order to promote the modernization of the city.