Application of the Improved Optimal Non-Negative Variable Weight Combination Model
Abstract According to the characteristics of GM (1,1), BP neural network and Kalman filter, we propose an optimal non-negative variable weight combination forecasting model based on grey correlation. This new model can control the effects of the errors. The calculation results are compared with the variable weight combination model based on the error square of minimum and the optimal weighted combination model or the three single method. The results show that the new model has the highest accuracy.
Key words :
dam deformation
optimal combination
grey correlation
non-negative variable weight
Cite this article:
WU Shaohua,CHENG Penggen,FU Bo. Application of the Improved Optimal Non-Negative Variable Weight Combination Model[J]. jgg, 2016, 36(11): 968-971.
WU Shaohua,CHENG Penggen,FU Bo. Application of the Improved Optimal Non-Negative Variable Weight Combination Model[J]. jgg, 2016, 36(11): 968-971.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2016/V36/I11/968
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