Paper Info
Title
Multi-variable grey forecast based on TOPSIS method
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.
Year
DOI
Venue
2010
10.1109/ICMLC.2010.5580630
ICMLC
Keywords
Field
DocType
time factor,grey systems,topsis method,grey model,forecast,forecasting theory,mgm(1,affect factor,multivariable grey forecast,differential equation,n) model,generation series,differential equations,machine learning,data models,economic indicators,mathematical model,predictive models,cybernetics
Differential equation,Data modeling,Computer science,Economic indicator,Time factor,Artificial intelligence,TOPSIS,Forecasting theory,Cybernetics,Machine learning,Gray (horse)
Conference
Volume
ISBN
Citations 
2
978-1-4244-6526-2
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Hongqi Hui103.04
Lei Zhou28317.87