基于BP神经网络的食堂点单系统备菜量预测

The Prediction of the Quantity of Food Prepared by the Canteen Ordering System Based on BP Neural Network

在点单系统中为方便食堂人员明确备菜的量,设计一款基于BP神经网络的备菜预测算法。根据设计App中的前期统计值作为训练数据,采用有导师学习方式,得到该系统的预测算法。根据该算法,得到某菜品30天中午的预测销售情况,并与实际情况进行对比。实验表明该点单预测算法能在一定程度上预测某菜品的销售量,起到防止浪费菜品的作用。

In order to get the quantity of prepared food accuracy for canteen staff system,a prepared food prediction algorithm based on BP neural net⁃work was designed.According to the preliminary statistical values in the designed App as the training data,the predictive algorithm of the system was obtained by using the tutor learning method.According to this algorithm,the sales forecast of a dish at noon for 30 days is ob⁃tained and compared with the actual situation.To a certain extent,the experiment shows that the algorithm can predict the sales of the dishes and prevent the waste of dishes.