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Give an example for each type of model and state the one that leads to simulation.

Mumbai University > Information Technology > Sem 8 > Computer Simulation and Modelling

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Give an example for each type of model and state the one that leads to simulation.

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Explain types of model with examples.

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Discuss types of simulation models

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What is the model of a system? What are the things that you have to keep in mind while designing a model? Explain different types of model with suitable example.

1 Answer
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Models can be classified as being mathematical or physical.

A mathematical model uses symbolic notation and mathematical equations to represent a system. A simulation model is a particular type of mathematical model of a system.

A physical model is based on some analogy between systems such as mechanical and electrical, electrical and hydraulic.

Systems attributes are represented by measurements such as voltage or position of shaft. It is also called look a like model. Simulation models can further classified as follows:

  1. Static: It is sometimes called as Monte Carlo simulation, represents a system at a particular point of time. Example: Model of building.
  2. Dynamic: Dynamic simulation models represents systems as they change over time. Example: The simulation of a bank from 9:00 A.M. to 4:00 P.M. is an example dynamic model.
  3. Deterministic: Simulation models that contain no random variables are classified as deterministic. Deterministic have known sets of input which will result in a unique set of outputs. Example: Deterministic arrivals would occur at a dentist’s office if all patents arrived at the scheduled appointment time.
  4. Stochastic: A stochastic simulation model has one or more random variables as inputs. Random inputs leads to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of a model. Example: The simulation of bank would usually involve random inter-arrival times and random service times. Thus in a stochastic simulation, the output measures- the average number of people waiting, the average waiting time of a customer- must be treated as statistical estimates of the true characteristics of the system.
  5. Discrete: In discrete model the state variables change only at discrete set of points in time. Example: Arrival of customers in banks.
  6. Continuous: A continuous model is a model in which state variables changes continuously over time is called continuous model. Example: Flow of water. Another example is the level of water in dam.
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