Abstract
This paper analyzes the historical sales data of vegetable products in a fresh food supermarket, and explores the automatic pricing and replenishment decision-making scheme of vegetable products in this supermarket. Firstly, we integrate and clean the attached data, and then we solve the characteristics and interrelationships of individual products and categories by establishing SARIMA model and Spearman's correlation coefficient model, and then we use nonlinear regression model, nonlinear autoregressive neural network model and optimization model to realize automatic pricing and replenishment decision-making for vegetable products.
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