Title :
A sales forecasting model for manufacturer in hybrid supply chain
Author :
Cao, Jian ; Ye, Feng ; Zhou, Gengui ; Wang, Hui ; Li, Ping
Author_Institution :
Inst. of Inf. Intelligence & Decision-Making Optimization, Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
In view of the characteristics of sales forecasting of manufacturer in hybrid supply chain (HSC), an extended recursive forgetting factor forecasting (ERFFF) model was given in this paper. The coefficient vector in this model is altered dynamically with the actual data, and the optimum structural parameters are adjusted according to the Theil U statistic, thus the best forecasting value is acquired under the optimal state. Through a practical case, it was proven the greater accuracy and applied value of this model.
Keywords :
forecasting theory; sales management; supply chains; Theil U statistic; extended recursive forgetting factor forecasting; forecasting value; hybrid supply chain; sales forecasting model; Decision making; Electronic mail; Manufacturing processes; Marketing and sales; Predictive models; Pulp manufacturing; Statistics; Supply chains; Technology forecasting; Virtual manufacturing;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343112
