Demand Analysis of Science and Technology Talents Based on Time Series - BP Neural Network Model
Jing Luo, Jingwen Qu · Advances in computer science research · 2023
Using Eviews7 and SPSS25, Granger causality test and stepwise regression analysis were carried out on the statistical data of China Statistical Yearbook, Shaanxi Statistical Yearbook and Xi'an Statistical Yearbook from 2010 to 2020.On this basis, a time series-BP neural network combined prediction model was constructed, and MATLAB software was used to train BP neural network for relevant data.Accordingly, the demand for scientific and technological talents in Shaanxi Province from 2021 to 2025 was predicted.The following conclusions were drawn: the total output value of industrial enterprises in Shaanxi Province can effectively predict the demand for scientific and technological talents; compared with the GM(1,1) model, the time series model has higher prediction accuracy for the gross industrial output value of industrial enterprises on the specification; the demand for science and technology talents in Shaanxi Province is estimated to increase exponentially.