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| Analiza difuzije na višeslojnim mrežama× | Analiza mrežne difuzije× | |
|---|---|---|
| Područje | Analiza mreža | Analiza mreža |
| Obitelj | Machine learning | Machine learning |
| Godina nastanka≠ | 2013–2014 | 1927 (epidemic roots); network formalization 1990s–2000s |
| Tvorac≠ | Gomez, S. et al.; Boccaletti, S. et al. | Kermack, W. O. & McKendrick, A. G. |
| Vrsta≠ | Network diffusion model | Simulation / analytical model |
| Temeljni izvor≠ | Gomez, S., Diaz-Guilera, A., Gomez-Gardenes, J., Perez-Vicente, C. J., Moreno, Y., & Arenas, A. (2013). Diffusion dynamics on multiplex networks. Physical Review Letters, 110(2), 028701. DOI ↗ | Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721. DOI ↗ |
| Drugi nazivi | multiplex diffusion analysis, multilayer spreading analysis, cross-layer contagion analysis, diffusion on multiplex networks | diffusion on networks, information diffusion, contagion spreading model, network propagation model |
| Srodne≠ | 6 | 5 |
| Sažetak≠ | Multilayer Network Diffusion Analysis models how information, disease, or influence spreads across a system composed of multiple, interconnected network layers. By coupling diffusion processes across layers — for instance social ties, transport routes, and online channels simultaneously — it reveals how cross-layer interactions accelerate or dampen spreading and lowers epidemic thresholds compared to single-layer models. | Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally. |
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