Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз мультиплексних мереж× | Аналіз поширення в мережі× | |
|---|---|---|
| Галузь | Мережевий аналіз | Мережевий аналіз |
| Родина | Machine learning | Machine learning |
| Рік появи≠ | 2014 | 1927 (epidemic roots); network formalization 1990s–2000s |
| Автор методу≠ | Kivela, M.; Boccaletti, S. et al. | Kermack, W. O. & McKendrick, A. G. |
| Тип≠ | Structural network model | Simulation / analytical model |
| Основоположне джерело≠ | Kivela, 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 ↗ |
| Інші назви | multiplex networks, multi-layer network analysis, multilayer network analysis, MNA | diffusion on networks, information diffusion, contagion spreading model, network propagation model |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | Multiplex 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. |
| ScholarGateНабір даних ↗ |
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