Search

How to analyze and predict the consumption behavior of Chinese residents is of great significance based on the existing consumption theory research and the actual situation in China. This study studies the factors influencing the consumption of urban and rural residents in China through factor analysis and builds a model of urban and rural residents' consumption expenditure based on BP neural network. At the same time, through the data collection, the consumption data of urban and rural residents in China from 1986 to 2017 were collected. The BP neural network prediction model was used to predict the consumption expenditure of urban and rural residents, and the absolute error and relative error were obtained. In addition, this study establishes a combined forecasting model based on Lasso regression analysis and BP neural network to predict the consumption expenditure of urban and rural residents and compares its prediction results with BP neural network prediction model. The research shows that the combined prediction model based on Lasso regression analysis and BP neural network comprehensively surpasses BP neural network prediction model in prediction accuracy, and it has certain effectiveness and puts forward practical suggestions, which provides theoretical reference for subsequent related research. [ABSTRACT FROM AUTHOR]