Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Jiang, Jianming | Ban, Yandong; * | Li, Jiayi | Zhou, Yane
Affiliations: School of Public Health and Management, Youjiang Medical University for Nationalities, Baise, China
Correspondence: [*] Corresponding author. Yandong Ban, School of Public Health and Management, Youjiang Medical University for Nationalities, Baise 533000, China. Email: 13707768141@163.com.
Abstract: Accurate prediction of the aging population can provide valuable reference and corresponding theoretical support for the adjustment of national population development policy and economic development strategy. To explore the future development trend of China’s aging population, this paper establishes a novel fractional grey prediction model with the time power term (abbreviated as FGM (1, 1, t α) model) to study China’s aging population. FGM (1, 1, t α) has the properties of fractional order accumulation operation and GM (1, 1, t α) model, which makes it good at capturing nonlinear features in time series. Furthermore, the quantum genetic algorithm is used to search for unknown parameters in the model to facilitate the solving task of the model. Data on China’s aging population from 2000 to 2009 are used to train the prediction models, and data from 2010 to 2019 are used to evaluate the models’ prediction performance. The results show that the FGM (1, 1, t α) model outperforms the other competing models, which means that it has good generalization. Finally, the FGM (1, 1, t α) model is used to forecast China’s aging population from 2020 to 2029.
Keywords: Grey system theory, grey prediction model, china’s elderly population, simpson formula, fractional order accumulation
DOI: 10.3233/JIFS-234205
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2929-2939, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl