Computer simulation tools are defined by four sets of characteristics, including stochastic and deterministic models, stationary or terminating output goals, continuous or discrete models, and local or distributed models. These characteristics define the tool and allow for a wide variety of choices. The method of data input determines the connection to the real world, and the final output is defined by what is being simulated. The method used to handle information and organize the simulation also affects the nature of the model.
Computer simulation tools are defined by four sets of characteristics. In most cases, there are two options to choose from, and a choice in one area has no impact on choices made in other areas. This means that simulation tool types don’t have a set name, but rather a hodgepodge of assigned characteristics. The definitions of these various options define the tool itself, making a wide variety of choices possible.
The types of computer simulation tools are defined by several characteristics and each of them has two main descriptors. The stochastic and deterministic models define the method of data input in the simulation. The ultimate output goal of the model is defined by whether it is stationary or terminating. The difference between a continuous and a discrete model is how information is processed by the simulation as a whole. Finally, local and distributed models define the method used to organize and run the simulation.
How data is fed into simulation tools often determines its connection to the real world. If the simulation uses a stochastic model, it usually attempts to simulate real-world factors. It does this by using a random generator to constantly feed the simulation with unexpected information. In a deterministic simulation, specific information is fed into the model to see the results under specific circumstances.
The final output of simulation tools is usually defined by what is being simulated. In a steady state model, the simulation can run indefinitely without stopping. These are used to monitor processes without natural stopping points, such as flowing water in a river. A final simulation has a natural beginning and end. A closing simulation could model the number of people entering a store on a given day, starting when the store opens and ending when the store closes.
The method a simulation tool uses to handle the information it assigns is another connection to the nature of the model. In a continuous model, the simulation is always learning new information and producing results. A flight simulator is a good example of this; flight information is constantly entering the system, which requires constant interaction. In a discrete model, all the information is entered, then done either at once or at predetermined intervals. These models are often used for defects in product and system testing.
The last option of the simulation tools determines how the simulation is organized. In a local simulation, the model runs in one place, often on a single computer. Distributed models run on a large number of machines, usually on a network or even on the Internet. The reasons for running a simulation over such a large area usually have to do with the power of the computer: the more machines running the simulation, the more information it can gather.
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