Research Article
Commodity Sales Forecast Based on Cluster Analysis and Time Series
@INPROCEEDINGS{10.4108/eai.27-10-2023.2341974, author={Wanying Lu and Dongyao Ren}, title={Commodity Sales Forecast Based on Cluster Analysis and Time Series}, proceedings={Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27--29, 2023, Tianjin, China}, publisher={EAI}, proceedings_a={ICEMBDA}, year={2024}, month={1}, keywords={pearson correlation analysis time series model prediction accuracy}, doi={10.4108/eai.27-10-2023.2341974} }- Wanying Lu
Dongyao Ren
Year: 2024
Commodity Sales Forecast Based on Cluster Analysis and Time Series
ICEMBDA
EAI
DOI: 10.4108/eai.27-10-2023.2341974
Abstract
The price of vegetables in fresh supermarkets is affected by many factors such as time and sales. Reliable market demand analysis is especially important for replenishment and pricing decisions. This article delves into related issues in vegetable pricing. We select the sales data of the latest 2023 Mathematical Modeling Competition Question C as the data in this paper, first preprocess the data, summarize the data according to vegetable categories and single products every day, and observe the sales trend of categories and single products over time by drawing a line chart. Second, the distribution of the data is tested, and the P-P plot of each variable is drawn to determine whether it follows a normal distribution; Pearson correlation analysis and Spearman correlation analysis were used to calculate the correlation coefficient between categories and items, respectively.
