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Stochastic simulation is a simulation where some variable or process is subject to random variations and is projected using Monte Carlo techniques using pseudo-random numbers. Thus replicated runs with the same boundary conditions will each produce different results within a specific confidence band.
Computer simulation is the running of a mathematical model on a computer, ... Techniques used for such simulations are Molecular dynamics, Molecular mechanics, ...
Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making.
Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one time, or once at many different times, and assigning values less than or equal to 0.50 as heads and greater than 0.50 as tails, is a Monte Carlo simulation of the behavior of repeatedly tossing a coin.
Simulation-based optimization (also known as simply simulation optimization) integrates optimization techniques into simulation modeling and analysis. Because of the complexity of the simulation, the objective function may become difficult and expensive to evaluate. Usually, the underlying simulation model is stochastic, so that the objective ...
A live simulation, by definition represents the highest fidelity, since it is reality. But a simulation quickly becomes more difficult when it is created from various live, virtual and constructive elements, or sets of simulations with various network protocols, where each simulation consists of a set of live, virtual and constructive elements.
This concern is addressed through verification and validation of the simulation model. Simulation models are approximate imitations of real-world systems and they never exactly imitate the real-world system. Due to that, a model should be verified and validated to the degree needed for the model's intended purpose or application. [3]
Simulation modeling is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world. Simulation modeling is used to help designers and engineers understand whether, under what conditions, and in which ways a part could fail and what loads it can withstand.
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