DocumentCode :
3276235
Title :
Simulation validation using Causal Inference Theory with morphological constraints
Author :
Reynolds, William N. ; Wimberly, Frank
Author_Institution :
Least Squares Software, Inc., Albuquerque, NM, USA
fYear :
2011
fDate :
11-14 Dec. 2011
Firstpage :
3636
Lastpage :
3648
Abstract :
We present an approach for the validation of complex simulation based on the structured elicitation of expert knowledge. Knowledge capture is based on the technique of Morphological Analysis, which is used to capture expert information on causal linkages and constraints in a systems and its simulation representation. This information is combined with Causal Inference Theory arguments to develop assertions about statistical dependency relations that should exist in both system and simulation. Causal Techniques for conducting these tests, which include the elicited constraint information are described. Overviews of Morphological Analysis, Causal Inference Theory and Statistical Testing Approaches are provided in the context of a Bayesian simulation of an example problem.
Keywords :
Bayes methods; inference mechanisms; simulation; Bayesian simulation; causal inference theory; causal linkage; causal technique; complex simulation; expert information; expert knowledge; knowledge capture; morphological analysis; morphological constraint; simulation validation; statistical dependency; statistical testing; Analytical models; Computational modeling; Data models; Face; Joints; Markov processes; Rivers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2011 Winter
Conference_Location :
Phoenix, AZ
ISSN :
0891-7736
Print_ISBN :
978-1-4577-2108-3
Electronic_ISBN :
0891-7736
Type :
conf
DOI :
10.1109/WSC.2011.6148057
Filename :
6148057
Link To Document :
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