The Discrete Grey Power Model Based on Aging Accumulation and its Application

Abstract

Abstract Accumulation generation is one of the key methods to reduce the randomness of data series, which significantly enhances the predictive performance of the grey prediction model. By integrating a degenerate operator, a novel accumulating discrete grey power model is introduced, capable of substantially enhancing the accuracy of predictions. This method allows for the flexible adjustment of the accumulation coefficient in the modeling data, mitigating the fluctuations in model parameters due to data perturbations, and effectively minimizing the loss of differential information. The outcomes of practical numerical examples demonstrate that the proposed aging accumulation discrete grey power model exhibits superior performance.