Prediction and analysis of industrial growth rate based on intelligent methods

Industrial growth rate plays a decisive role in the economic growth of enterprises. When formulating industrial development policies, government departments and enterprises usually take it as an important standard. Therefore, accurate prediction of changes in industrial growth rate is of great significance to the development of government departments and enterprises. Based on the existing statistical data of Shaanxi Province, through correlation analysis, this paper first judges that the growth rate of industrial added value in Shaanxi Province is highly correlated with the cumulative growth rate of the above-scale energy and non-energy. Finally, in view of the nonlinear, time-varying and other uncertainties brought about by the large-scale and globalization of modern industrial economy, the research idea of intelligent modeling and prediction is proposed, and the prediction model of industrial growth rate is constructed by combining Sparrow Search Algorithm (SSA) with BPNN.