Research of procedure quality forecast based on the grey theory and BP neural networks

Qiu Ming Wang*, Ke Cheng Liu, Hui Ying Gao

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    Forecasting of procedure quality plays an important role in quality control. The GM(1, 1) model in grey theory and BP artificial neural networks have been applied in the field of forecasting widely. Although each of above two methods has advantages over traditional forecasting methods, they have their disadvantages respectively. The method of forecasting procedure quality based on the combination of grey theory and BP artificial neural networks is proposed in this article. After analyzing and utilizing the superiority of both, the integrated model to forecasting procedure quality is established. The example illustrates that the proposed method for forecast is feasible.

    Original languageEnglish
    Pages (from-to)249-252
    Number of pages4
    JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
    Volume31
    Issue number2
    Publication statusPublished - Feb 2011

    Keywords

    • Grey theory
    • Neural networks
    • Procedure quality
    • Quality forecasting
    • Residual

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