Paper Title:
Study on Supply Chain Partner Selection Based on Support Vector Machine
  Abstract

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.

  Info
Periodical
Chapter
Chapter 8: System Modeling and Simulation
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
4779-4783
DOI
10.4028/www.scientific.net/AMM.121-126.4779
Citation
W. B. Li, "Study on Supply Chain Partner Selection Based on Support Vector Machine", Applied Mechanics and Materials, Vols. 121-126, pp. 4779-4783, 2012
Online since
October 2011
Authors
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Wei Jian Huang, Hua Zhao, Liang Huang, Wei Du
Abstract:The enterprise of port logistics has its own traits such as very high specialty of assets, high uncertainty of internal and external...
746
Authors: Xiang Tian Nie, Jing Hai Lan
Chapter 3: Innovation in Architecture and Building Construction
Abstract:Selecting excellent partnering partners is crucial for project implementation.In view of the drawbacks of traditional methods which only...
565
Authors: Ai Ling Chen
Chapter 16: Industrial Engineering, Production Management, Operations, Quality and Control
Abstract:Partner selection decisions are an important component of production and supply chain management. However, partner selection is a typical...
1633
Authors: Jian Ping Yang, Li Jun Hou
Chapter 7: Innovative Technologies in Production Management, Economics and Finances
Abstract:Strategic alliance of real estate enterprise is the strategic choice responds to the current market environment and pursue sustainable...
731