Study on Supply Chain Partner Selection Based on Support Vector Machine

摘要：

　　SVM is a novel machine learning technique developed on empirical risk minimization principle.SVM has many advantages in solving small sample size,nonlinear and high dimensional pattern recognition problem.Based on the study of SVM,this paper discusses its application in the supply chain partner selection that provides a reference for enterprise to select the partner.

关键词： Support Vector Machine Kernel Function Supply Chain Partner Selection

作者: Wenbo Li

作者单位: Economics and Management School, Zhejiang Normal University, Jinhua, Zhejiang, 321004, China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4779-4783

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）