পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| নেটওয়ার্ক ডিফিউশন মডেল× | নেটওয়ার্ক স্থিতিস্থাপকতা এবং দুর্বলতা বিশ্লেষণ× | |
|---|---|---|
| ক্ষেত্র | নেটওয়ার্ক বিশ্লেষণ | নেটওয়ার্ক বিশ্লেষণ |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1927 (epidemiological compartmental); 2003 (social influence cascade) | 2000 |
| প্রবর্তক≠ | Kermack & McKendrick (SIR/SIS, 1927); Kempe, Kleinberg & Tardos (Independent Cascade, 2003) | Albert, Jeong & Barabási |
| ধরন≠ | Stochastic / deterministic simulation on graphs | Network robustness / vulnerability framework |
| মৌলিক উৎস≠ | Kermack, W.O. & McKendrick, A.G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proceedings of the Royal Society of London. Series A, 115(772), 700-721. DOI ↗ | Albert, R., Jeong, H. & Barabási, A.L. (2000). Error and attack tolerance of complex networks. Nature, 406, 378–382. DOI ↗ |
| অপর নাম≠ | epidemic spreading models, compartmental models, influence propagation models, Ağ Yayılım Modelleri (SIR, SIS, Independent Cascade) | network vulnerability analysis, attack tolerance analysis, Ağ Dayanıklılığı ve Güvenlik Açığı Analizi |
| সম্পর্কিত | 5 | 5 |
| সারসংক্ষেপ≠ | Network diffusion models are a family of compartmental and probabilistic frameworks that simulate how information, disease, or innovation spreads across a connected system. Rooted in the mathematical epidemiology of Kermack and McKendrick (1927), the SIR and SIS models partition nodes into states and track transitions driven by contact rates and recovery probabilities. The Independent Cascade and Linear Threshold models, formalised by Kempe, Kleinberg, and Tardos (2003), extend this logic to social influence, modelling how activation propagates through a network one neighbour at a time. | 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. |
| ScholarGateডেটাসেট ↗ |
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