Optimization approach of background value and initial item for improving prediction precision of GM(1,1) model

Abstract

A combination method of optimization of the background value and optimization of the initial item is proposed. The sequences of the unbiased exponential distribution are simulated and predicted through the optimization of the background value in grey differential equations. The principle of the new information priority in the grey system theory and the rationality of the initial item in the original GM(1,1) model are fully expressed through the improvement of the initial item in the proposed time response function. A numerical example is employed to illustrate that the proposed method is able to simulate and predict sequences of raw data with the unbiased exponential distribution and has better simulation performance and prediction precision than the original GM(1,1) model relatively. © 1990-2011 Beijing Institute of Aerospace Information.