The research into crisis early warning of supply chain quality based on rough set&feature weighted support vector machine - Details

author：

Qiang, Rui (Qiang, Rui.) ^[1] (Scholars：强瑞) | Hu, Xiu-Lian (Hu, Xiu-Lian.) ^[2] | Lu, Li-Xia (Lu, Li-Xia.) ^[3]

Indexed by：

EI Scopus

Abstract：

A　RS-FWSVM　model　is　presented　by　means　of　combining　RS　(Rough　Set)　with　FWSVM　(Feature　Weighted　Support　Vector　Machine)　theory.　Application　process　of　this　model　to　the　crisis　early　warning　of　SCQ　is　researched,　which　can　help　enable　chain　enterprises　to　identify　crises　in　the　process　of　operations　and　to　predict　possible　crises.　©　2011　IEEE.

Keyword：

Rough set theory Supply chains Support vector machines

Community：

[ 1 ] [Qiang, Rui]Management Science and Engineering, Fuzhou University, Fujian, China
[ 2 ] [Qiang, Rui]Fuzhou University, No. 523, Industry Road, Gulou District, Fuzhou, China
[ 3 ] [Hu, Xiu-Lian]Management Science and Engineering, Fuzhou University, Fujian, China
[ 4 ] [Lu, Li-Xia]Management Science and Engineering, Fuzhou University, Fujian, China