Research Article
A Method for Sales Prediction Based on Time Series
@INPROCEEDINGS{10.4108/eai.2-6-2023.2334677, author={Chen Chen}, title={A Method for Sales Prediction Based on Time Series}, proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2023}, month={8}, keywords={sales prediction; arima; time series}, doi={10.4108/eai.2-6-2023.2334677} }- Chen Chen
Year: 2023
A Method for Sales Prediction Based on Time Series
ICIDC
EAI
DOI: 10.4108/eai.2-6-2023.2334677
Abstract
This article explores the application of MA, ARMA, and ARIMA models in sales forecasting based on the method of time series analysis. By crawling and cleaning data, the training results of the data model can be better ensured. In sales forecasting, time series analysis can be used to study the patterns and trends of historical sales data, and make predictions for future sales based on this. Time se-ries analysis is a widely used statistical method for data analysis and prediction. By training and testing object data groups, algorithm prediction of sales data is achieved. Experiments have shown that ARIMA has better prediction perfor-mance than MA and ARMA.
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