A Bayesian learning approach to inconsistency identification in model-based systems engineering

A Bayesian learning approach to inconsistency identification in model-based systems engineering

Designing and developing complex engineering systems is a collaborative effort. In Model-Based Systems Engineering (MBSE), this collaboration is supported through the use of formal, computer-interpretable models, allowing stakeholders to address concerns using well-defined modeling languages. Howeve...

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Bibliographic Details
Main Author: Herzig, Sebastian J. I.
Other Authors: Paredis, Christiaan J. J.
Format: Others
Language:en_US
Published: Georgia Institute of Technology 2015
Subjects:
Interoperability
Bayesian learning
Bayesian reasoning
Graph queries
Pattern matching
Abductive reasoning
Incremental reasoning
Automated reasoning
Machine learning
RDF
SPARQL
Semantic web
MBSE
Model-based systems engineering
Inconsistency management
Inconsistency identification
Model integration
Online Access:http://hdl.handle.net/1853/53576

Internet

http://hdl.handle.net/1853/53576

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