Analysis of GDP based on polynomial regression and BP neural network

Abstract

GDP(Gross Domestic Product) is the important index for measuring economic development. Quantitative analysis and prediction for GDP can regulate the economic development trend and promote steady economic development. In this article, we used Jiangsu province as an example. Firstly, we determined to 19 indexes which could explain GDP potentially by national economic accounting theory, and a quadratic polynomial regression model was used between the GDP and the principal factor. Secondly, in order to efficiently predict the GDP, we established a BP neural network model with excellent parameter taking 19 indexes as independent variable and GDP as dependent variable. Finally, we came to the conclusion about the GDP of Jiangsu province, and some suggestions for development were given.