Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Aģentu bāzēta mikrosimulācija× | Sistēmdinamika× | |
|---|---|---|
| Nozare | Simulācija | Simulācija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1957 (microsimulation); 2000s (hybrid ABMS) | 1961 |
| Autors≠ | Orcutt, G. H. (microsimulation roots); Bonabeau, E. and others (ABM integration) | Jay W. Forrester |
| Tips≠ | Hybrid simulation | Continuous simulation / feedback modelling |
| Pirmavots≠ | Birkin, M., & Clarke, M. (2012). The enhancement of spatial microsimulation models using geodemographics. Annals of Regional Science, 49(2), 515–532. DOI ↗ | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| Citi nosaukumi | ABMS, Agent-Based Micro-Simulation, Microsimulation with Agent-Based Modeling, Hybrid ABM-Microsimulation | stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation |
| Saistītās≠ | 5 | 3 |
| Kopsavilkums≠ | Agent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanisms. It creates virtual populations of heterogeneous agents who evolve over time according to transition probabilities, adaptive behaviors, and social interactions, producing emergent system-level outcomes from micro-level dynamics. | 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. |
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