摘要
Sale prediction plays a significant role in business management. By using support vector machine Regression (ε-SVR), a method using to predict sale is illustrated. It takes historical data and current context data as inputs and presents results, i.e. sale tendency in the future and the forecasting sales, according to the user's specification of accuracy and time cycles. Some practical data experiments and the comparative tests with other algorithms show the advantages of the proposed approach in computation time and correctness.
Sale prediction plays a significant role in business management. By using support vector machine Regression (ε-SVR), a method using to predict sale is illustrated. It takes historical data and current context data as inputs and presents results, i.e. sale tendency in the future and the forecasting sales, according to the user's specification of accuracy and time cycles. Some practical data experiments and the comparative tests with other algorithms show the advantages of the proposed approach in computation time and correctness.
基金
This project was supported by the National Natural Science Foundation of China (60573159)
the Natural Science Foundation of Guangdong Province (05200302).