Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Agenttipohjainen mikrosimulaatio× | Diskreetti tapahtumasimulaatio (DES)× | |
|---|---|---|
| Tieteenala | Simulointi | Simulointi |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1957 (microsimulation); 2000s (hybrid ABMS) | 1960s (formalized); modern computational form from 1970s onward |
| Kehittäjä≠ | Orcutt, G. H. (microsimulation roots); Bonabeau, E. and others (ABM integration) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Tyyppi≠ | Hybrid simulation | Stochastic process simulation |
| Alkuperäislähde≠ | Birkin, M., & Clarke, M. (2012). The enhancement of spatial microsimulation models using geodemographics. Annals of Regional Science, 49(2), 515–532. DOI ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Rinnakkaisnimet≠ | ABMS, Agent-Based Micro-Simulation, Microsimulation with Agent-Based Modeling, Hybrid ABM-Microsimulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Liittyvät≠ | 5 | 4 |
| Tiivistelmä≠ | 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. | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. |
| ScholarGateAineisto ↗ |
|
|