DocumentCode :
1724835
Title :
The optimized GPM(1,1) for forecasting small sample oscillating series
Author :
Wang, Zheng-Xin ; Dang, Yao-Guo ; He, Sha-Wei
Author_Institution :
Sch. of Econ. & Manage., Zhejiang Normal Univ., Jinhua, China
fYear :
2011
Firstpage :
286
Lastpage :
290
Abstract :
This paper puts forward a modeling approach for oscillating series based on an optimized grey power model with first-order one-variable (abbreviated as GPM(1,1). An optimization method is used to determine the initial value in GPM(1,1) model, and furthermore, the parameters in the model are optimized by utilizing a non-linear programming model. The results show that the modeling approach proposed in this paper can reflect the fluctuation of original data and be solved handily using a computer. The range of application of Grey Model is further extended to forecast oscillating series. The effectiveness of the optimized GPM(1,1) model is demonstrated by an actual case study.
Keywords :
forecasting theory; grey systems; nonlinear programming; GPM(1,1) model; grey power model; nonlinear programming model; optimization method; sample oscillating series; Computational modeling; Forecasting; GPM(1,1) model; forecasting; optimization; oscillating series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grey Systems and Intelligent Services (GSIS), 2011 IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-61284-490-9
Type :
conf
DOI :
10.1109/GSIS.2011.6043996
Filename :
6043996
Link To Document :
بازگشت