Titlebook: Computer Simulation Validation; Fundamental Concepts Claus Beisbart,Nicole J. Saam Book 2019 Springer Nature Switzerland AG 2019 Computer S

APNEA

The Use of Experimental Data in Simulation Model Validationaic equations is discussed. Comparisons of model and target system data are considered using graphical methods and quantitative measures in the time and frequency domains. System identification and parameter estimation methods are emphasized, especially in terms of identifiability analysis which can

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Enteropathic

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Possible Principles of Justice,system. The goal of the testing process for a simulation model must always be to establish the extent to which a model has the quality and credibility required for the intended application. These model testing processes, involving both verification and validation, are inherently iterative.

BLUSH

Application and the Act of Reading,. Hermeneutic aims to demonstrate how simulation validation is historically situated, revealing the hidden prejudice (prejudgement)in validating, and distinguishing between legitimate prejudice and prejudice that has to be overcome. Understanding simulation validation is a dialogic, practical, situated activity.

Meager

https://doi.org/10.1007/978-1-349-00776-9l validation results is, inevitably, an iterative process, and experiments designed for model validation can never be truly optimal. A model of the pulmonary gas exchange processes in humans is used to illustrate some issues of identifiability, experiment design and test input selection for model validation.

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Detoxification

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Justice, Equality and Socialism,ional source of error and uncertainty. This chapter discusses these different sources of error and uncertainty as well as methods to characterize and treat them. Techniques for rolling up these different uncertainty sources into a total prediction uncertainty are briefly discussed.