Deriving Stochastic Properties from Behavior Models Defined by Monterey Phoenix
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Stochastic properties of behavior models are of interest to the developer of a System of Systems (SoS) in order to gain insight to the likelihood of potential outcomes of the system. Constraints added to the system introduce changes to the inherent dependencies within a representative Bayesian belief network; thereby impacting the system. This paper defines a probability process model that may be used to identify the probability of outcomes compliant with behavior models defined in Monterey Phoenix (MP), with constraints added to the model.
The article of record as published may be found a http://doi.org/10.1109/SYSOSE.2017.7994961Published in: 2017 12th System of Systems Engineering Conference (SoSE); Date of Conference: 18-21 June 2017
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