Abstract
To accurately predict the aging population in China, a novel grey prediction model (CFODGMW(1,1, alpha ) model) is established in this study. The CFODGMW(1,1, alpha ) model has all the advantages of the weighted least square method, combined fractional-order accumulation generation operation and grey prediction model with time power term, which makes it have excellent prediction performance. Compared with the traditional grey prediction model based on the least square method and the first-order accumulation operation, the CFODGMW(1,1, alpha ) model has stronger adaptability. The proposed model and its competing models are used to analyze the aging population in five regions of China. The results show that the prediction performance of the CFODGMW(1,1, alpha ) model is better than other models. Based on this, the CFODGMW(1,1, alpha ) model is used to predict the aging population in China in the next 4 years, and some suggestions are given based on the development trend of the aging population.
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