Research on Neural Network Fusion Algorithm of Pension Participation Rate Based on Word Frequency Analysis

Population aging is a significant trend in human societal development, emphasizing the urgent need to build a pension service system that aligns with this aging process. Therefore, predicting the participation rate of young people in pension insurance is of significant importance for the construction of the social security system. This paper, based on word frequency analysis, investigates specific content related to pension insurance with young people as the survey object. It proposes an Artificial Neural Network (ANN) model based on time series analysis. Using the participation rate in Shaanxi as an example, predictions are made using the time series ARIMA analysis method, the multiple linear regression model, and the neural network fusion model constructed in this paper. The results indicate that while all three prediction models show high goodness of fit, the ANN fusion algorithm fits better. The prediction model results show that most young people are willing to participate in pension insurance, and the number of people participating in pension insurance in Shaanxi will increase year by year over the next five years.