A taxonomy of model abstraction techniques

Model abstraction is a method for reducing the complexity of a simulation model while maintaining the validity of the simulation results with respect to the question that the simulation is being used to address. Model developers have traditionally used a number of abstraction techniques, and simulat...

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Vydáno v:Proceedings of the 27th conference on Winter simulation s. 1413 - 1420
Hlavní autor: Frantz, Frederick K.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Washington, DC, USA IEEE Computer Society 01.12.1995
Edice:ACM Conferences
Témata:
Computing methodologies > Modeling and simulation > Model development and analysis
Computing methodologies > Modeling and simulation > Model development and analysis > Model verification and validation
Mathematics of computing > Mathematical analysis > Functional analysis > Approximation
Mathematics of computing > Mathematical analysis > Numerical analysis > Interpolation
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis
ISBN:0780330188, 9780780330184
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Shrnutí:Model abstraction is a method for reducing the complexity of a simulation model while maintaining the validity of the simulation results with respect to the question that the simulation is being used to address. Model developers have traditionally used a number of abstraction techniques, and simulation researchers have conducted formal research to build a theoretical foundation for model manipulation. More recently, researchers in the artificial intelligence (AI) subfield of qualitative simulation have also been developing techniques for simplifying models, determining whether models results are valid, and developing tools for automatic model selection and manipulation. Metamodeling can also be considered as an abstraction technique. The purpose of the paper is to provide a taxonomy of abstraction techniques drawn from these fields. This taxonomy provides a framework for comparing and contrasting various abstraction techniques.
Bibliografie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:0780330188
9780780330184
DOI:10.1145/224401.224834