Research On Pricing and Replenishment of Vegetable Products Based on Time Series Prediction

Abstract

Based on the commodity information, sales data, and recent loss rate of wholesale price commodities of vegetable categories provided by the superstore, this paper focuses on the relationship between vegetable categories and individual products and the prediction of sales volume in the next seven days. Firstly, the distribution pattern and interrelationship of the sales volume of each category and single product of vegetables were analyzed using data analysis and visualization techniques, and the specific size of the correlation of each category and single product was obtained. Secondly, the ARIMA model was used to predict the sales volume of vegetable categories, and the corresponding replenishment volume was obtained. Finally, through the above analysis, a corresponding replenishment strategy can be provided for the superstore to achieve the subsequent optimal revenue, and the superstore revenue planning model is also discussed and outlooked at the end of the paper.