Title :
Research on the price prediction in supply chain based on data mining technology
Author :
Yang LanQin ; Xin, Xu
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;
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
DOI :
10.1109/MSNA.2012.6324621
