পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| সেলুলার অটোমাটা× | নেটওয়ার্ক ডিফিউশন মডেল× | |
|---|---|---|
| ক্ষেত্র≠ | অনুকরণ | নেটওয়ার্ক বিশ্লেষণ |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1940s–1950s (formalized); 1970 (Conway's Game of Life); 2002 (Wolfram's systematic classification) | 1927 (epidemiological compartmental); 2003 (social influence cascade) |
| প্রবর্তক≠ | John von Neumann and Stanislaw Ulam (1940s–1950s); popularized by John Conway (1970) and Stephen Wolfram (1980s–2002) | Kermack & McKendrick (SIR/SIS, 1927); Kempe, Kleinberg & Tardos (Independent Cascade, 2003) |
| ধরন≠ | Grid-based computational simulation model | Stochastic / deterministic simulation on graphs |
| মৌলিক উৎস≠ | Wolfram, S. (2002). A New Kind of Science. Wolfram Media. ISBN: 978-1579550080 | 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 ↗ |
| অপর নাম | CA, Hücresel Otomat (Cellular Automata), lattice model, grid-based simulation | epidemic spreading models, compartmental models, influence propagation models, Ağ Yayılım Modelleri (SIR, SIS, Independent Cascade) |
| সম্পর্কিত | 5 | 5 |
| সারসংক্ষেপ≠ | Cellular automata (CA) is a grid-based computational simulation model, first formalized by John von Neumann and Stanislaw Ulam in the 1940s–1950s and brought to wide attention by John Conway's Game of Life (1970) and Stephen Wolfram's systematic classification (2002), in which a lattice of cells — each holding a finite discrete state — evolves in discrete time steps according to local neighborhood interaction rules, causing complex global patterns to emerge from simple local specifications. | 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. |
| ScholarGateডেটাসেট ↗ |
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