Research on the Predicting Model of Convenience Store Model Based on Digital Twins

With the rapid development of information economy, how to make full use of the existing store information for decision—making and analysis of goods has significant importance in the store’s sales forecast. As a potential way to realize the interaction and integration between physical world and information space, the concept of digital twins had been proposed recently which attracted high attentions of academics practitioners in related fields. Based on the previous research on the concept of digital twins, the reference system architecture of digital twins convenience stores is designed. A digital twins model based on BP neural network is proposed as the example of convenience store prediction, compared with the traditional grey prediction, the results show that the model has smaller prediction error and higher accuracy.