Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Anàlisi de la Resiliència i Vulnerabilitat de Xarxes× | Anàlisi de Xarxes Temporals× | |
|---|---|---|
| Camp | Anàlisi de xarxes | Anàlisi de xarxes |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2000 | 2012 |
| Autor original≠ | Albert, Jeong & Barabási | Holme & Saramäki (2012) — seminal framework |
| Tipus≠ | Network robustness / vulnerability framework | Dynamic graph analysis |
| Font seminal≠ | Albert, R., Jeong, H. & Barabási, A.L. (2000). Error and attack tolerance of complex networks. Nature, 406, 378–382. DOI ↗ | Holme, P. & Saramäki, J. (2012). Temporal Networks. Physics Reports, 519(3), 97-125. DOI ↗ |
| Àlies | network vulnerability analysis, attack tolerance analysis, Ağ Dayanıklılığı ve Güvenlik Açığı Analizi | dynamic network analysis, time-varying network analysis, Zamansal Ağ Analizi (Temporal / Dynamic Networks) |
| Relacionats≠ | 5 | 3 |
| Resum≠ | Network resilience and vulnerability analysis is an analytical framework, formalised by Albert, Jeong, and Barabási (2000), that measures how a network degrades functionally as nodes or edges are progressively removed. By running targeted-attack simulations — removing the highest-centrality nodes first — and random-failure simulations — removing nodes at uniform probability — the framework identifies which structural elements are critical to network integrity and where infrastructure is most exposed. | Temporal network analysis, formalised by Holme and Saramäki in their landmark 2012 Physics Reports survey, is the study of networks in which edges appear and disappear over time. Rather than collapsing all contacts into a single static graph, the approach preserves the precise timing of interactions — whether as contact sequences, time-stamped event lists, or windowed snapshots — and uses that timing to track how influence, disease, or information can actually propagate through the system. |
| ScholarGateConjunt de dades ↗ |
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