Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Makadirio ya Idadi ya Watu kwa Njia ya Vikundi-Vijenzi× | Mifumo ya Mionzi ya Uhamaji na Usafiri× | |
|---|---|---|
| Nyanja≠ | Demografia | Uchanganuzi wa Kimaeneo |
| Familia≠ | Process / pipeline | Regression model |
| Mwaka wa asili≠ | 2001 | 2012 |
| Mwanzilishi≠ | Preston, Heuveline & Guillot | Filippo Simini et al. |
| Aina≠ | Demographic projection pipeline | Parameter-free spatial interaction model |
| Chanzo asilia≠ | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2 | Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100. DOI ↗ |
| Majina mbadala | Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonu | Radiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeli |
| Zinazohusiana | 3 | 3 |
| Muhtasari≠ | Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (2001), the method builds on foundational actuarial and demographic work dating to the early twentieth century and remains the workhorse technique used by national statistical offices and international organizations worldwide. | The Radiation Model, introduced by Simini et al. in 2012, is a parameter-free model for predicting human mobility and migration flows between geographic locations. Drawing an analogy from radiation physics, it predicts trip volumes based solely on population sizes at origin and destination, and the intervening population within the circle connecting them. It has been widely applied to commuting flows, migration, and epidemic spreading. |
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