It is of practical significance to clarify the influencing factors of population aging to effectively respond to the challenges of aging and promote the development of China's economy and society. This paper takes population aging influencing factors as the research object, and on the basis of reasonable assumptions The three single models of quadratic exponential smoothing prediction, modified gray prediction and BP neural network prediction are constructed, and then the error sum of squares of in-sample prediction is derived separately, and then the weights are determined according to the inverse of the error sum of squares method to construct a combined prediction model of population aging, and the conclusion that the prediction of combined prediction model is more effective regardless of in-sample prediction or out-of-sample prediction is drawn; and then the model is used to predict the prediction results show that the problem of population aging in China will remain increasingly serious in the future.

Linlin Su, Yaxin Zhou, Qi Fang.Analysis of Domestic Population Aging Forecast Based on Combined Forecast Model. International Journal of New Developments in Engineering and Society (2022) Vol.6, Issue 3: 43-49. https://doi.org/10.25236/IJNDES.2022.060308.

[1] Chen, T. Xu, L., Chen, X.J., Huang, L. S.. Analysis and forecast of population aging in China[C].// Proceedings of the 13th Annual Academic Conference on Management Science in China. [publisher unknown], 2011:717-722.

[2] Zhang Boqin, Gao Xiaocheng, and Mao Huanmin. Analysis and prediction of population aging in China[J]. Journal of Natural Sciences, Harbin Normal University, 2009, 25(03):23-24.

[3] Xu Yi. Analysis on the influencing factors of population aging in China [J]. Contemporary Tourism(Golf Travel), 2018(10):247-248.