SVR mathematical model and methods for sale prediction
作者： Yi Yangl , Rong Fulil , Chang Huiyou , Xiao Zhijiaol
DOI: 10.1016/S1004-4132(08)60018-3
关键词:
摘要: Abstract Sale prediction plays a significant role in business management. By using support vector machine Regression (ɛ-SVR), method to predict sale is illustrated. It takes historical data and current context as inputs presents results, i.e. tendency the future forecasting sales, according user's specification of accuracy time cycles. Some practical experiments comparative tests with other algorithms show advantages proposed approach computation correctness.
sci-hub.se 参考文章(4)
Celia Frank, Ashish Garg, Les Sztandera, Amar Raheja, Forecasting women's apparel sales using mathematical modeling International Journal of Clothing Science and Technology. ,vol. 15, pp. 107- 125 ,(2003) , 10.1108/09556220310470097
A. J. Smola, B. Schölkopf, On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion Algorithmica. ,vol. 22, pp. 211- 231 ,(1998) , 10.1007/PL00013831
Yuh-Jye Lee, Wen-Feng Hsieh, Chien-Ming Huang, /spl epsi/-SSVR: a smooth support vector machine for /spl epsi/-insensitive regression IEEE Transactions on Knowledge and Data Engineering. ,vol. 17, pp. 678- 685 ,(2005) , 10.1109/TKDE.2005.77
Chin‐Tsai Lin, Pi‐Fang Hsu, Forecast of non‐alcoholic beverage sales in Taiwan using the Grey theory Asia Pacific Journal of Marketing and Logistics. ,vol. 14, pp. 3- 12 ,(2002) , 10.1108/13555850210764927