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Combined model based on optimized multi-variable grey model and multiple linear regression

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4 Author(s)
Pingping Xiong ; College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China; College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China ; Yaoguo Dang ; Xianghua Wu ; Xuemei Li

The construction method of background value is improved in the original multi-variable grey model (MGM(1, m)) from its source of construction errors. The MGM(1, m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Published in:

Journal of Systems Engineering and Electronics  (Volume:22 ,  Issue: 4 )