关键词: 高龄人口死亡率, AE-LSTM改进模型, CBD模型, 死亡率预测

Abstract: Prediction of mortality of the elderly population is the basis of longevity risk measurement and management, assessment of pension cost and debt. Based on the characteristics of mortality data of the elderly population, an improved AE-LSTM model is proposed to predict the mortality of the elderly population. Firstly, the AE model is used to extract the potential time factor from the mortality data of the elderly population. Then, the potential time factor is used as the input variable of the LSTM model. The mortality prediction value of the elderly population is obtained by decoding the AE model. At the same time, the mortality rate of the elderly aged 60-89 in China mainland from 1994 to 2018 is selected as the sample data for empirical analysis. The results show that the prediction accuracy of the improved AE-LSTM model is significantly higher than that of the traditional CBD model, and the prediction results show strong robustness.

Key words: Mortality rate of elderly population, Improved AE-LSTM model, CBD model, Prediction of mortality