Title :
Adaptive Hierarchical Forecasting
Author :
Engels, C. ; Konen, W.
Author_Institution :
Fachhochschule Dortmund, Dortmund
Abstract :
This paper describes the extension of classical forecasting methods for an application to hierarchical data structures. We show that various methods of hierarchical coupling can improve forecasting results using hierarchical relationships considerably. In a concrete application we are able to reduce the relative error of a retail forecasting model by 10%.
Keywords :
data structures; forecasting theory; retailing; adaptive hierarchical forecasting; hierarchical coupling; hierarchical data structures; retail forecasting model; Business; Conferences; Construction industry; Data analysis; Data mining; Data structures; Demand forecasting; Intelligent structures; Predictive models; Technology forecasting;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on
Conference_Location :
Dortmund
Print_ISBN :
978-1-4244-1347-8
Electronic_ISBN :
978-1-4244-1348-5
DOI :
10.1109/IDAACS.2007.4488400
