To add greater weight to new information, discrete grey model with the weighted accumulation (WDGM(1,1)) is put forward. This paper proved the stability of WDGM(1,1) disturbance boundary and the influence of the analysis parameter λ on the reduction error. The prediction ability of the WDGM(1,1) is verified by five cases. The results show that WDGM(1,1) not only satisfies the new information priority to a certain extent, but also has better stability. Moreover, the parameter λ in WDGM(1,1) can effectively reduce the reduction error, so that it has better prediction accuracy in practical applications. Therefore, the proposal of WDGM(1,1) is not only very theoretical, but also has good practical significance.
Grey model Weighted accumulation Disturbance boundary Reduction error
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The relevant researches carried out in this paper are supported by the National Natural Science Foundation of China (Nos. 71871084, 71401051).
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Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals.
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