Title :
A prediction method for irregular demand processes
Author :
Wang, Qian ; Li, Bo ; Yang, Jun-Li
Author_Institution :
Dept. of Ind. Eng., Tianjin Univ., China
Abstract :
Irregular demand forecasting method based on radial basis function network (RBFN) is presented in this paper. Firstly, some researches in the literatures are discussed, and then a modeling prediction method based on RBFN is proposed for irregular demand time series. According to the irregularity of time series, the method can successively adjust model structure and parameters by error, so that can effectively simulate rules of system; Meanwhile, the orthogonality and forward regression can realize the recursive computation, greatly reduce the amount of computation and more satisfy practical desires. Finally the effectiveness of the method is illustrated by the simulation examples.
Keywords :
demand forecasting; forecasting theory; radial basis function networks; regression analysis; time series; Croston method; forward regression; irregular demand forecasting method; irregular demand time series; prediction method; radial basis function network; Computational modeling; Demand forecasting; Engineering management; Industrial engineering; Inventory management; Prediction methods; Predictive models; Production planning; Radial basis function networks; Smoothing methods; Croston method; Prediction; irregular demand; radial basis function network;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527265
