Verifying and validating simulation models
Robert G. Sargent
- pp 55-64
TLDR
A graphical paradigm that relates verification and validation to the model development process is presented and explained and a recommended procedure for model validation is presented.Abstract:
This paper discusses verification and validation of simulation models. The different approaches to deciding model validity am presented; how model verification and validation relate to the model development process are discussed; various validation techniques are defined, conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; and a recommended procedure is presented.read more
Citations
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Journal ArticleDOI
Verification and validation of simulation models
TL;DR: Three approaches to deciding model validity are described, two paradigms that relate verification and validation to the model development process are presented, and various validation techniques are defined.
Journal ArticleDOI
Verification and Validation in Computational Fluid Dynamics
TL;DR: An extensive review of the literature in V&V in computational fluid dynamics (CFD) is presented, methods and procedures for assessing V &V are discussed, and a relatively new procedure for estimating experimental uncertainty is given that has proven more effective at estimating random and correlated bias errors in wind-tunnel experiments than traditional methods.
Proceedings ArticleDOI
Validation and verification of simulation models
TL;DR: Four different approaches to deciding model validity are described, and a recommended procedure for model validation is presented, as well as various validation techniques defined.
Proceedings ArticleDOI
Verification and validation of simulation models
TL;DR: In this article, verification and validation of simulation models are discussed, and four different approaches to deciding model validity are described; various validation techniques are defined; conceptual model validity, model verification, operational validity and data validity are discussed; a way to document results is given; a recommended procedure for model validation is presented; and accreditation is briefly discussed.
Journal ArticleDOI
A Methodology for Fitting and Validating Metamodels in Simulation
TL;DR: In this article, the authors propose a methodology for validation of a metamodel with respect to both the underlying simulation model and the problem entity, based on the classic design of experiments (DOE) and measuring fit through standard measures such as R-square and crossvalidation statistics.
References
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Book
Simulation Modeling and Analysis
Averill M. Law,W. David Kelton +1 more
TL;DR: The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.
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Discrete-Event System Simulation
TL;DR: Beleska o autorima: str. XV-XVI. as mentioned in this paper - Bibliografija uz svako poglavlje. - Registar.
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Probability and Statistics for Engineers and Scientists
TL;DR: In this paper, the authors present a survey of statistical and data analysis methods for probability distributions and their application to statistical quality control problems, including one and two Sided Tests of Hypotheses.
Book
Theory of modeling and simulation
TL;DR: In this paper, the authors present a rigorous mathematical foundation for modeling and simulation and provide a comprehensive framework for integrating the various simulation approaches employed in practice, including cellular automata, chaotic systems, hierarchical block diagrams, and Petri nets.
Posted Content
Verification and validation of simulation models
TL;DR: In this article, the authors present a survey of verification and validation of simulation models in operations research, focusing on good programming practice (such as modular programming), checking intermediate simulation outputs through tracing and statistical testing per module, statistical testing of final simulation outputs against analytical results, and animation.