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8.3.2 Uncertainty Quantification (UQ) in Complex System of Systems (SoS) Modeling and Simulation (M&S) Environments
Author(s) -
Marvin Joseph,
Morantz Brad,
Whalen Thomas,
Deiotte Ray,
Garrett Robert K.
Publication year - 2014
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2014.tb03185.x
Subject(s) - computer science , uncertainty quantification , complex system , parametric statistics , graph , theoretical computer science , artificial intelligence , machine learning , mathematics , statistics
Prevailing Modeling and Simulation (M&S) techniques have struggled to provide meaningful quantitative results in M&S of complex System of Systems (SoSs) in the face of an environment filled with complex interacting uncertainties. This paper reports on systems thinking applied to “how” M&S techniques should shift to allow a next generation of quantitative tools and techniques. The imperative is to provide quantitative performance results across the constituent interfaces in a modeled architecture. A five step statistical and parametric algorithm tool that addresses Uncertainty Quantification (UQ) is presented. [Improving the utility of UQ data evaluation] A quantitative approach to managing complex uncertainties across modeled interfaces using graph theory is proposed. A future vision for SoS Engineering (SoSE) that uses graph theory based modeling is suggested to improve the utility of tools such as UQ is suggested.