A comprehensive inventory forecasting model based on data mining of demand system
被引:1
作者:
De, Xia
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R ChinaWuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China
De, Xia
[1
]
Zheng, Zhaoxia
论文数: 0引用数: 0
h-index: 0
机构:
Hubei Univ Technol, Sch Comp Sci, Wuhan 430068, Peoples R ChinaWuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China
Zheng, Zhaoxia
[2
]
机构:
[1] Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China
[2] Hubei Univ Technol, Sch Comp Sci, Wuhan 430068, Peoples R China
来源:
2009 ISECS INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT, VOL I
|
2009年
关键词:
Grey system;
Data mining;
Correlation;
Inventory forecast;
D O I:
10.1109/CCCM.2009.5268099
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
There are complex grey correlations among different demands of products as well as ones between demands and inventories. In terms of the nature of huge data reflecting this tough grey system in market, we manage to design a comprehensive inventory forecasting model, which is based on the data mining of market demand and inventory serial data. Grey theory is applied to reserve the essence of system while a data mining method is designed to screen the serial data to target critic ones as basis to inventory forecast. The model can produce valuable information about the tendency of inventory in near future.