DocumentCode
1633194
Title
Research on the price prediction in supply chain based on data mining technology
Author
Yang LanQin ; Xin, Xu
Volume
2
fYear
2012
Firstpage
460
Lastpage
463
Abstract
Through using data mining methods, we can find useful hidden trends and relationships in the mass data. This can help supply chain companies to improve the quality of decision-making on supply chain management with the gained knowledge. Take the supply chain product polyester filament as an example, through the influence factor analysis of polyester filament price; this paper uses data mining methods to predict the prices of polyester filament. The established predictive models and analytical results can be used in the supply chain enterprises and as the basis of macro-control on the chemical fiber industry of and relevant departments.
Keywords
data mining; decision making; forecasting theory; plastics industry; polymer fibres; pricing; production planning; supply chain management; chemical fiber industry; data mining technology; decision making; polyester filament price prediction; predictive models; supply chain product polyester filament; Chemicals; Data mining; Data models; Forecasting; Predictive models; Supply chains; Data Mining; Price Prediction; Supply Chain;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location
Sanya
Print_ISBN
978-1-4673-2465-6
Type
conf
DOI
10.1109/MSNA.2012.6324621
Filename
6324621
Link To Document