Abstract
In recent years, BP (Back Propagation) neural network is widely used in predictive modeling in various fields. But the BP neural network technology which used for university catering service is very few. The article is applied to the data set which is published by the EMC competition of Shanghai Jiao Tong University in 2015. We use BP neural network to analyze and forecast the university restaurant sales, and then through comparing the model with the time series forecasting method. The elements used in the model include the cycle factor, the Baidu index of the network take away, the weather information. The forecasting factors include three aspects of the 11 variables, which is also an innovation of this paper. Finally, we proved that the model we built has a good prediction result and it also has practical availability. This article also explained how the variables impact on university catering service.
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