Probabilistic diagnostics with P-graphs

Authors:
Balázs Polgár;Endre Selényi
Affiliations:
Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar Tudósok krt. 2, Budapest, Hungary, H-1117;Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar Tudósok krt. 2, Budapest, Hungary, H-1117
Venue:
Acta Cybernetica
Year:
2003

Citing 3
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Abstract

This paper presents a novel approach for solving the probabilistic diagnosis problem in multiprocessor systems. The main idea of the algorithm is based on the reformulation of the diagnostic procedure as a P-graph model. The same, well-elaborated mathematical paxadigm--originally used to model material flow--can be applied in our approach to model information flow. This idea is illustrated by deriving a maximum likelihood diagnostic decision procedure. The diagnostic accuracy of the solution is considered on the basis of simulation measurements, and a method of constructing a general framework for different aspects of a complex problem is demonstrated with the use of P-graph models.