Application hybrid grey dynamic model to forecasting compensatory control

Abstract

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.

Findings

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.

Citation

Li, G., Yamaguchi, D. and Nagai, M. (2007), "Application hybrid grey dynamic model to forecasting compensatory control", Engineering Computations, Vol. 24 No. 7, pp. 699-711. https://doi.org/10.1108/02644400710817943