Research on Consumption Prediction of Daily Necessities Based on Combination Model and Its Influence on Upgrading of Industrial Structure

The development of big data and artificial intelligence ensures the industrial innovation traditional commodities. Economic transformation upgrading has become general trend social development. Based on public Rossmann store, a well-known German chain consumption prediction model daily necessities based random forest GBRT is proposed in this paper. By combining to initialize residuals, not only training speed effectively improved but also more accurate obtained. analysis data, paper puts forward influence forecast structure constructs value creation transmission system for necessities, so as promote rationalization level consumer provide reference same type commodity structure.