DocumentCode
2246568
Title
Multi-variable grey forecast based on TOPSIS method
Author
Hui, Hong-qi ; Zhou, Lei
Author_Institution
Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhang, China
Volume
2
fYear
2010
fDate
11-14 July 2010
Firstpage
1054
Lastpage
1058
Abstract
Grey forecast has been widely used in many areas for the characteristics of few data and poor information by differential equation of accumulated generation series. In the forecast process of grey model, different number of variables can produce forecast results with different precision. This paper selects variables to forecast with TOPSIS method, which takes different affect factors as plans and converts time factors to attributes. Case studies show that TOPSIS method can be used to variables choice to produce good forecast results.
Keywords
differential equations; forecasting theory; grey systems; TOPSIS method; affect factor; differential equation; generation series; grey model; multivariable grey forecast; time factor; Biological system modeling; Cybernetics; Data models; Economic indicators; Machine learning; Mathematical model; Predictive models; Forecast; Grey model; MGM(1, n) model; TOPSIS method;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5580630
Filename
5580630
Link To Document