Predicting of elderly population structure and density by a novel grey fractional-order model with theta residual optimization: a case study of Shanghai City, China.

Guo, Xiaojun; Li, Jiaxin; Zhu, Xinyao; Yang, Yingjie; Jin, Jingliang

Guo, Xiaojun; Li, Jiaxin; Zhu, Xinyao; Yang, Yingjie; Jin, Jingliang.

Afiliación

Guo X; School of Science, Nantong University, Nantong, 226019, China. guoxj159@163.com.
Li J; School of Science, Nantong University, Nantong, 226019, China.
Zhu X; School of Science, Nantong University, Nantong, 226019, China.
Yang Y; Institute of Artificial Intelligence, De Montfort University, Leicester, LE1 9BH, UK.
Jin J; School of Science, Nantong University, Nantong, 226019, China. Chinajjl@ntu.edu.cn.

BMC Geriatr ; 23(1): 568, 2023 09 16.

Article en En | MEDLINE | ID: mdl-37716937

Asunto(s)

Envejecimiento; Pensiones; Humanos; Anciano; China/epidemiología; Modelos Logísticos

Palabras clave

Elderly population prediction; Fractional order accumulation; Grey prediction model; Population aging; Theta residual optimization

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pensiones / Envejecimiento Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Aged / Humans País/Región como asunto: Asia Idioma: En Revista: BMC Geriatr Asunto de la revista: GERIATRIA Año: 2023 Tipo del documento: Article País de afiliación: China

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