DocumentCode :
442036
Title :
Collaborative identification of coordination questions in supply chain based on support vector machines
Author :
Li, Xiang-Yang ; Li, Hui ; Zhou, Yan-Chun
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., China
Volume :
6
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
3662
Abstract :
Aiming at guarantee the coordination of supply chain, the working flow of coordination questions identification of supply chain based on support vector machine (SVM) is analyzed. Identification model of coordination questions based on SVM is established by formalization, which mainly includes three parts: resources of coordination questions identification in supply chain, collaborative identification of coordination questions and results of collaborative identification. Degree of similarity of supply chain partners (SCP) feature sets is proposed to be a rule in the process of SVM feature selection. And identification accuracy of SCP is proposed to determined weighs of SCP. Finally the approach is simulated in distributor´s marking ability identification.
Keywords :
groupware; identification; logistics; supply chain management; support vector machines; collaborative identification of coordination question; distributor marking ability identification; feature selection; identification model; supply chain management; supply chain partner; support vector machine; Collaboration; Collaborative work; Learning systems; Logistics; Machine learning; Machine learning algorithms; Supply chain management; Supply chains; Support vector machine classification; Support vector machines; Logistics management; SVM; collaborative identification of coordination questions; supply chain management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527577
Filename :
1527577
Link To Document :
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