Abstract

Modeling processes and model testing processes are discussed as parts of the model life cycle, and the tasks of these processes and their relations are highlighted. Of particular interest is the model validation process, which ensures that the model closely simulates what the real system does. A collection of validation techniques is presented to facilitate a systematic check of model performance from various perspectives. Under the qualitative category, a few graphical techniques are presented to help a visual examination of the differences between the simulation and the observation. Under the quantitative category, several statistical measures are discussed to quantify the goodness of fit; to achieve a higher level of confidence about model performance, a simultaneous statistical inference technique is proposed that tests both model accuracy and precision. As an illustrative example, these validation techniques are comprehensively applied to test an enhanced macroscopic simulation model, KWaves, in a systematic manner.

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