Neural Network Algorithm in Regional Macroeconomic Forecast

Accurate and scientific understanding of the operation law of economic development and transformation of a region can provide a deeper understanding of the law of local economic development and the relationship between its influencing factors. The purpose of this paper is to study regional macroeconomic forecast based on neural network algorithm. The production process of the feedforward neural network, as well as the structure and learning law of the neural network are introduced in detail. Taking the prediction of the added value of the primary, secondary and tertiary industries in M province as the goal, the main economic indicators of the region are applied to the BP neural network, and finally a more practical, perfect and efficient artificial neural network system is obtained. The artificial neural network algorithm is applied to the surrounding macro forecasting, and a set of calculation software is designed by using Matlab to forecast some major economic indicators of M province and compare it with other algorithms. The error between the predicted value and the actual value of BP neural network is within 3%, which is conducive to the economic development of the province.