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
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;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580630
