Model validation is defined to mean "substantiation that a computerized model within its domain of applicability possesses a satisfactory range of accuracy consistent with the intended application of the model". Including, but not limited to, have the model checked by an expert, making logic flow diagrams that include each logically possible action, examining the model output for reasonableness under a variety of settings of the input parameters, and using an interactive debugger. For example, the number of servers in a fast food drive through lane and if there is more than one how are they utilized? A typical error is assuming an inappropriate statistical distribution for the data. Validation of model assumptions[ edit ] Assumptions made about a model generally fall into two categories: Do the servers work in parallel where a customer completes a transaction by visiting a single server or does one server take orders and handle payment while the other prepares and serves the order. The validation test consists of comparing outputs from the system under consideration to model outputs for the same set of input conditions. Compare the model input-output transformations to corresponding input-output transformations for the real system. There are many techniques that can be utilized to verify a model. The approaches range from subjective reviews to objective statistical tests. Build a model that has high face validity.

# Validating input output transformation. Verification and validation of computer simulation models.

Model validation is defined to mean "substantiation that a computerized model within its domain of applicability possesses a satisfactory range of accuracy consistent with the intended application of the model". Including, but not limited to, have the model checked by an expert, making logic flow diagrams that include each logically possible action, examining the model output for reasonableness under a variety of settings of the input parameters, and using an interactive debugger. For example, the number of servers in a fast food drive through lane and if there is more than one how are they utilized? A typical error is assuming an inappropriate statistical distribution for the data. Validation of model assumptions[ edit ] Assumptions made about a model generally fall into two categories: Do the servers work in parallel where a customer completes a transaction by visiting a single server or does one server take orders and handle payment while the other prepares and serves the order. The validation test consists of comparing outputs from the system under consideration to model outputs for the same set of input conditions. Compare the model input-output transformations to corresponding input-output transformations for the real system. There are many techniques that can be utilized to verify a model. The approaches range from subjective reviews to objective statistical tests. Build a model that has high face validity.

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