विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मार्कोव मॉडल× | कतार अनुकरण× | |
|---|---|---|
| क्षेत्र | अनुकरण | अनुकरण |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1906 | 1909 |
| प्रवर्तक≠ | Andrei Markov | Agner Krarup Erlang |
| प्रकार≠ | Probabilistic state-transition model | Stochastic simulation / analytical modeling |
| मौलिक स्रोत≠ | Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963 | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 |
| उपनाम | Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| संबंधित≠ | 5 | 6 |
| सारांश≠ | A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling. | 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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