基于时间序列分析的餐饮市场需求预测模型

Forecasting Model Based on Time Series Analysis

随着互联网应用的快速发展,外卖作为一种新型就餐方式出现在大众视野,但由于病人的“禁忌”饮食和“康复”饮食,病患的膳食在外卖服务中仍然是个盲区。通过Python爬虫技术对2020年至2021年前24个月美团外卖中20家店铺的外卖信息进行定向抓取,并将得到的数据进行可视化处理,建立时间序列分析的ARIMA模型,预测未来12个月病患点餐数据,采用Eviews软件绘制时间序列图。结果表明,所建立模型的分析预测结果是合理的。

With the rapid development of Internet applications,takeaway as a new way of eating appears in the public eye,but due to the patient's"contraindicated"diet and"rehabilitation"diet,the patient's diet is still a blind spot in the takeaway service.Through Python crawler technology,the takeaway information of 20 stores in the first 24 months of Meituan's takeaway from 2020 to 2021 is targeted,and the obtained data is visualized,and an ARIMA model of time series analysis is established to predict the patient ordering data in the next 12 months,and the time series map is drawn by Eviews software.The results show that the analysis and prediction results of the established model are reasonable.