Reconstruction and Prediction of Regional Population Migration Neural Network Model with Age Structure
The rationale for age-structured population migration system models lies in the significant impact of age patterns on migration dynamics, as age-specific migration rates exhibit distinct regularities and are influenced by life course transitions, socio-economic conditions, and demographic structures...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/5/755 |
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| Summary: | The rationale for age-structured population migration system models lies in the significant impact of age patterns on migration dynamics, as age-specific migration rates exhibit distinct regularities and are influenced by life course transitions, socio-economic conditions, and demographic structures. Based on artificial neural networks, this article proposes a class of population models with age structure described by partial differential equations to predict the future trends of regional population changes. The population migration rate, as a complex nonlinear feature, can be trained through artificial neural networks, providing a population approximation system. By employing semigroup theory, we establish the well-posedness of the proposed system. It is shown that the solution of the approximation system can converge to that of the original system in the sense of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>L</mi><mn>2</mn></msup></semantics></math></inline-formula>-norm. Finally, several simulation experiments are provided to verify the effectiveness of the population forecasting model. |
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| ISSN: | 2227-7390 |