Abstract
According to the poor adaptability and the poor effect of medium and long term prediction of the GM(1,1) model, combined with prediction theory of metabolism, applied the equal division function method to optimized the background value constantly, and established a model of GM(1,1) based on metabolism. At the same time, on the basis of sufficient consideration of the random interference and driving factors that entered the model successively, the model of GM(1,1) based on metabolism is further improved and optimized, and established a gradual progressive metabolic grey GM (1,1) which has the optimal dimension to achieve the best balance between the accuracy of prediction and the convergence of prediction. The results of simulation experiments indicate that the metabolic grey GM (1,1) is improved has better forecasting effect and stronger adaptability than the conventional and metabolic GM (1,1) model.
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Yuwen, L., Hongtu, C., Zhiyong, L., Shidong, F., Min, J. (2019). Prediction of Remaining Useful Life for Equipment Based on Improved Metabolic GM(1,1) Model. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_85
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DOI: https://doi.org/10.1007/978-3-030-02804-6_85
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