Título
Comparison of two types of event Bayesian networks: a case study
Autor
GUSTAVO ARROYO FIGUEROA
LUIS ENRIQUE SUCAR SUCCAR
Nivel de Acceso
Acceso Abierto
Materias
Bayesian networks - (BAYESIAN NETWORKS) Temporal reasoning - (TEMPORAL REASONING) Fault diagnosis and prediction - (FAULT DIAGNOSIS AND PREDICTION) Evaluation - (EVALUATION) Case study - (CASE STUDY) CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA - (CTI) MATEMÁTICAS - (CTI) CIENCIA DE LOS ORDENADORES - (CTI)
Resumen o descripción
Temporal Nodes Bayesian Networks (TNBNs) and Networks of Probabilistic Events in Discrete Time (NPEDTs) are two different types of Event Bayesian Networks (EBNs). Both are based on the representation of uncertain events, alternatively to Dynamic Bayesian Networks, which deal with real-world dynamic properties. In a previous work, Arroyo-Figueroa and Sucar applied TNBNs to the diagnosis and prediction of the temporal faults that may occur in the steam generator of a fossil power plant. We present an NPEDT for the same domain, along with a comparative evaluation of the two networks. We examine different methods suggested in the literature for the evaluation of Bayesian networks, analyze their limitations when applied to this temporal domain, and suggest a new evaluation method appropriate for EBNs. In general, the results show that, in this domain, NPEDTs perform better than TNBNs, possibly due to be the finer time granularity used in the NPEDT.
Editor
Applied Artificial Intelligence
Fecha de publicación
2007
Tipo de publicación
Artículo
Versión de la publicación
Versión publicada
Recurso de información
Formato
application/pdf
Idioma
Inglés
Audiencia
Estudiantes
Investigadores
Público en general
Sugerencia de citación
Galán, S.F., et al., (2007). Comparison of two types of event Bayesian networks: a case study, Applied Artificial Intelligence, 21(3):185-209
Repositorio Orígen
Repositorio Institucional del INAOE
Descargas
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