Product sales forecasting model based on robust wavelet v-support vector machine

被引：0

作者：

Wu, Qi ^{[1
,2
]}

Yan, Hong-Sen ^{[1
]}

Wang, Bin ^{[1
]}

机构：

[1] Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University

[2] School of Mechanical Engineering, Southeast University

来源：

Zidonghua Xuebao/ Acta Automatica Sinica | 2009年 / 35卷 / 07期

关键词：

Forecasting; Robust loss function; Support vector machine (SVM); Wavelet kernel function;

D O I：

10.3724/SP.J.1004.2009.01027

中图分类号：

学科分类号：

摘要：

Aiming at the normal Gaussian distributional noise, greater breadth noise and oddity point noise of product sales series and combing a designed robust loss function with wavelet kernel function, we propose a new wavelet v-support vector machine, named as robust wavelet v-support vector machine (RWv-SVM). The RWv-SVM, which has a stronger robustness and simpler dual optimization problem than standard wavelet-support vector machine (Wv-SVM), can inhibit some types of noise and disturbing oddity point noise of product sales series effectively. Finally, the RWv-SVM is applied to the forecasts of car sales, and the results show that the forecasting model based on the proposed RWv-SVM is effective and feasible. © 2009 Acta Automatica Sinica. All rights reserved.

引用

页码：1027 / 1032

页数：5

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