A Short-term Forecasting Method for Regional Logistics Demand Based on Support Vector Regression

摘要：

A short-term forecasting method for regional logistics demand based on support vector regression(SVR)is proposed to solve the problems caused by nonlinearity and fluctuation in forecasting regional logisties demand.Because the proposed method is based on the research of statistical learning theory and kernel mapping,it has good processing ability for nonlinear data.Consequently,it has good generalization ability.At last,an experiment is conducted to validate the rationality and validity of the proposed method.

关键词： Support Vector Regression(SVR) Regional Logistics Forecasting Kernel Method

作者: Xiao Jianhua Tang Jun

作者单位: School of Management,Wuyi University,Jiangmen,Guangdong 529020,China;School of Economic Management,B School of Management,Wuyi University,Jiangmen,Guangdong 529020,China

会议类型: 国际会议

会议名称: 2006 Interntional Conferecne on Management of Logistics and Supply Chain(2006物流与供应链管理国际研讨会)

会议地点: 长沙

会议语种:英文

页码: 710-714

在线出版日期: 2006-09-20（万方平台首次上网日期，不代表论文的发表时间）