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Daudzslāņu tīklu analīze×Tīkla difūzijas analīze×
NozareTīklu analīzeTīklu analīze
SaimeMachine learningMachine learning
Izcelsmes gads20141927 (epidemic roots); network formalization 1990s–2000s
AutorsKivela, M.; Boccaletti, S. et al.Kermack, W. O. & McKendrick, A. G.
TipsStructural network modelSimulation / analytical model
PirmavotsKivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. 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 ↗
Citi nosaukumimultiplex networks, multi-layer network analysis, multilayer network analysis, MNAdiffusion on networks, information diffusion, contagion spreading model, network propagation model
Saistītās65
KopsavilkumsMultiplex network analysis studies systems where the same set of nodes is connected by multiple distinct types of relationships, each represented as a separate network layer. By analyzing layers simultaneously rather than in isolation, it reveals how different relation types interact, reinforce each other, or compensate for one another across the same actors or entities.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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ScholarGateSalīdzināt metodes: Multiplex Network Analysis · Network Diffusion Analysis. Izgūts 2026-06-15 no https://scholargate.app/lv/compare