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Application hybrid grey dynamic model to forecasting compensatory control

机译:混合灰色动态模型在预测补偿控制中的应用。

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Purpose - This paper aims to increase the manufacturing accuracy and quality of product by improving the prediction accuracy of forecasting compensatory control (FCC). Design/methodology/approach - The dynamic analysis model, which combines grey dynamic model with time series autoregressive integrated moving average (ARIMA) model is proposed. In addition, the Markov chain from stochastic process theory is applied to improve the prediction accuracy.rnFindings - The proposed model is more accurate than ARIMA model and grey dynamic model. Originality/value - The paper provides a viewpoint on FCC by using the combined methodology, which takes advantage of high predictable power of grey dynamic model and at the same time takes advantage of the prediction powers of ARIMA model and Markov chain.
机译:目的-本文旨在通过提高预测补偿控制(FCC)的预测准确性来提高制造精度和产品质量。设计/方法/方法-提出了将灰色动态模型与时间序列自回归综合移动平均值(ARIMA)模型相结合的动态分析模型。此外,还采用了随机过程理论的马尔可夫链来提高预测的准确性。rn发现-所提出的模型比ARIMA模型和灰色动态模型更准确。原创性/价值-本文通过使用组合方法提供了有关FCC的观点,该方法利用了灰色动态模型的高预测能力,同时利用了ARIMA模型和马尔可夫链的预测能力。

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