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Discrete grey model with the weighted accumulation

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Abstract

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.

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Acknowledgements

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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Authors and Affiliations

  1. College of Economics and Management, Hebei University of Engineering, Handan, 056038, China

    Lifeng Wu & Hongying Zhao

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  1. Lifeng Wu
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  2. Hongying Zhao
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Correspondence to Lifeng Wu.

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Communicated by V. Loia.

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Wu, L., Zhao, H. Discrete grey model with the weighted accumulation. Soft Comput 23, 12873–12881 (2019). https://doi.org/10.1007/s00500-019-03845-3

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  • DOI: https://doi.org/10.1007/s00500-019-03845-3

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