SVR mathematical model and methods for sale prediction

查看全文 作　　者：Yi [1]Yang;Rong [1]Fuli;Chang [2]Huiyou;Xiao [1]Zhijiao

机构地区：[1]Computer Science Dept., Sun Yat-Sen Univ., Guangzhou 510275, P. R. China;[2]Software School, Sun Yat-Sen Univ., Guangzhou 510275, P. R. China

出　　处：《Journal of Systems Engineering and Electronics》索引2007年第18卷第4期,共5页

基　　金：This project was supported by the National Natural Science Foundation of China (60573159);the Natural Science Foundation of Guangdong Province (05200302). 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. 关键词：支持向量机人工智能数学模型价格预测

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SVR mathematical model and methods for sale prediction

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