Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Αυτόματα Κυτταρικά Ντετερμινιστικά× | Δυναμική Συστημάτων× | |
|---|---|---|
| Πεδίο | Προσομοίωση | Προσομοίωση |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 1940s–1950s | 1961 |
| Δημιουργός≠ | John von Neumann and Stanislaw Ulam | Jay W. Forrester |
| Τύπος≠ | Discrete deterministic grid simulation | Continuous simulation / feedback modelling |
| Θεμελιώδης πηγή≠ | von Neumann, J. (1966). Theory of Self-Reproducing Automata. University of Illinois Press, Urbana, IL. (Edited and completed by A. W. Burks.) link ↗ | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| Εναλλακτικές ονομασίες | Deterministic CA, Classical Cellular Automata, Rule-based CA, Finite Automata Grid Model | stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation |
| Συναφείς≠ | 6 | 3 |
| Σύνοψη≠ | Deterministic Cellular Automata (DCA) is a simulation method that models the evolution of complex systems through a regular grid of cells, each holding a discrete state, updated synchronously at each time step according to a fixed, deterministic rule applied to the cell and its neighbors. The outcome is fully reproducible given the same initial conditions and rule set. | System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|