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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Pruning Procedure For Incomplete-Observation Diagnostic Model
Simplification |
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Authors: |
Ivan Havel |
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Published in:
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ECMS
2007 Proceedings Edited
by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni ISBN:
978-0-9553018-2-7 Doi: 10.7148/2007 21st European
Conference on Modelling and Simulation, Prague, June
4-6, 2007 |
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Citation
format: |
Havel, I. (2007). Pruning
Procedure For Incomplete-Observation Diagnostic Model Simplification. ECMS
2007 Proceedings edited by: I. Zelinka, Z. Oplatkova, A. Orsoni
(pp. 515-520). European Council for Modeling and Simulation. doi:10.7148/2007-0515. |
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DOI: |
http://dx.doi.org/10.7148/2007-0515 |
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Abstract: |
Model-based
diagnostics deals with diagnosing systems, it means determining health of
system com- ponents based on a system description
and an obser- vation of
system variables. This paper focuses on sys- tems
that can be described in propositional logic, par- ticularly
on simplification of their diagnostic models for some given conditions of
observation. It is known that performing diagnostics on the entire model of a
system when only few variables are expected to be observed
is not efficient. If we knew the limited set of variables
which may appear in the observation then they would be used to
simplify the diagnostic model before the diag- nosis inference takes place. A pruning procedure
which systematically removes segments of a model that do not contribute to
the overall system diagnosis is proposed. The procedure employs an
algorithm deciding compo- nent diagnosability which is
based on directional resolu- tion.
Diagnoses retrieved using the simplified model are equivalent to those
retrieved using the original model. |
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