Title :
An effective supply chain performance prediction method and its application
Author_Institution :
Economic Manage. Coll., Sichuan Agric. Univ., Yaan, China
Abstract :
This article sets up a supply chain performance prediction model based on rough sets and support vector regression machine (SVR) from knowledge discovery and data mining perspectives. According to a supply chain performance prediction example, the index can be reduced based on balanced scorecard system, and input the reduction index to SVR for training. Then, the forecast sample are put in the model and get supply chain performance predictive value. The forecast result is fitted with the actual result.
Keywords :
data mining; regression analysis; rough set theory; supply chain management; support vector machines; balanced scorecard system; data mining; knowledge discovery; reduction index; rough sets; supply chain performance prediction; support vector regression machine; Data analysis; Data mining; Linear regression; Neural networks; Prediction methods; Predictive models; Risk management; Rough sets; Supply chains; Support vector machines;
Conference_Titel :
Grey Systems and Intelligent Services, 2009. GSIS 2009. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4914-9
Electronic_ISBN :
978-1-4244-4916-3
DOI :
10.1109/GSIS.2009.5408233
