Analysis and Prediction of Economic Industrial Structure by BP Neural Network Based on Genetic Algorithm

Analyzing and predicting the economic and industrial structure can grasp the future development characteristics and trends of the industrial structure, thereby helping to optimize and upgrade the industrial structure. Analyzed the basic principles of BP neural network and genetic algorithm, and further analyzed the prediction of economic and industrial structure using BP neural network based on genetic algorithm. This article introduces the application of BP neural network based on genetic algorithm in the analysis and prediction of economic industrial structure. One of the important indicators of economic development is the change in industrial structure. In order to predict economic development trends more accurately, an improved BP neural network model is proposed based on the traditional BP neural network model and combined with genetic algorithm. This model utilizes genetic algorithm to optimize the structure of the BP neural network, and enhances the generalization ability of the neural network by learning similar patterns from the training set. Experiments have shown that the improved BP neural network has higher prediction accuracy and lower error rate. This model will be widely applied in industries such as finance and economy, and is expected to provide more accurate predictions and effective decision support for economic development.