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Academic Journal of Business & Management, 2020, 2(2); doi: 10.25236/AJBM.2020.020214.

Prediction of Aging Degree Based on Holt Linear Trend and BP Neural Network


Yang Yang1, Wang Jing2

Corresponding Author:
Yang Yang

1 School of Finance, Anhui University of Finance and Economics; Bengbu, 233030, China
2 School of Finance and public management, Anhui University of Finance and economics, Bengbu, China, 233030


The change of population age structure is related to all aspects of the development of social production in China. It is beneficial to the adjustment of industrial structure and the construction of social security system by predicting the development of aging population in China. In order to predict the change of aging degree in China, based on the data of population aging in China from 1990 to 2018, using SPSS, MATLAB, Excel and other software, the paper forecasts the population aging degree from 2019 to 2023 by constructing Holt linear trend and BP neural network model. The model established by the model is tested, and the error analysis of the prediction results shows that the reliability of the prediction is high. Finally, according to the prediction of aging changes, the paper puts forward corresponding suggestions for the adjustment of industrial structure and the construction of social security system.


Holt linear trend; BP neural network; Population aging; Age structure

Cite This Paper

Yang Yang, Wang Jing. Prediction of Aging Degree Based on Holt Linear Trend and BP Neural Network. Academic Journal of Business & Management (2020) Vol. 2, Issue 2: 129-139. https://doi.org/10.25236/AJBM.2020.020214.


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