Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Simulare Bayesiană a Liniilor de Așteptare× | Simularea Cozilor× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1994 | 1909 |
| Autorul original≠ | Armero, C. & Bayarri, M. J. | Agner Krarup Erlang |
| Tip≠ | Bayesian inference + stochastic simulation | Stochastic simulation / analytical modeling |
| Sursa seminală≠ | Armero, C., & Bayarri, M. J. (1994). Bayesian prediction in M/M/1 queues. Queueing Systems, 15(1–4), 401–417. DOI ↗ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 |
| Denumiri alternative | BQS, Bayesian Queue Simulation, Bayesian Stochastic Queueing, Bayesian Queuing Analysis | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| Înrudite | 6 | 6 |
| Rezumat≠ | Bayesian Queueing Simulation combines Bayesian statistical inference with stochastic queueing simulation to model waiting-line systems under parameter uncertainty. Instead of treating arrival and service rates as fixed known values, it places prior distributions over them, updates these with observed data to obtain posteriors, and propagates the resulting parameter uncertainty through repeated simulation runs to produce probabilistic predictions of system performance metrics such as queue length, waiting time, and server utilisation. | Queueing Simulation combines classical queueing theory with discrete-event simulation to model systems where entities arrive, wait for service, and depart. It predicts performance metrics such as average waiting time, queue length, and server utilization, enabling capacity planning and bottleneck identification across service, manufacturing, healthcare, and network systems. |
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