Russian Federation
This paper is to discuss the simulation process and stochastic modeling in depth. The step of the simulation process is to simulate the real system by establishing a system model and running it. Stochastic modeling is to solve and dispose of the uncertainty of the experiment, because uncertainty is an important factor that greatly affects the experimental results. Therefore, the probability and statistics method is used to model the stochastic process. In this paper, a series of problems and methods such as the concept and type of the two are expounded. In order to describe their advantages and characteristics in more detail, I will elaborate each feature in combination with examples.
Simulation process; Stochastic modeling; Uncertainty analysis; Decision support
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