| dc.creator | GUSTAVO ARROYO FIGUEROA | |
| dc.creator | LUIS ENRIQUE SUCAR SUCCAR | |
| dc.date | 2013-06-23 | |
| dc.date.accessioned | 2022-10-12T20:15:59Z | |
| dc.date.available | 2022-10-12T20:15:59Z | |
| dc.identifier | http://repositorio.ineel.mx/jspui/handle/123456789/311 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4130735 | |
| dc.description | Diagnosis and prediction m some
domains, like medical and industrial
diagnosis, require a representation that
combines uncertainty management and
temporal reasoning. Based on the fact
that in many cases there are few state
changes in the temporal range of
interest, we propose a novel representation
called Temporal Nodes Bayesian
Network (TNBN). In a TNBN each node
represents an event or state change of a
variable, and an arc corresponds to a
causal-temporal relation. The temporal
intervals can differ in number and size
for each temporal node, so this allows
multiple granularity. Our approach is
contrasted with a dynamic Bayesian
network for a simple medical example.
An empirical evaluation is presented for
a more complex problem, a subsystem of
a fossil power plant, in which this
approach is used for fault diagnosis and
event prediction with good results. | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by-nc/4.0 | |
| dc.subject | info:eu-repo/classification/cti/7 | |
| dc.subject | info:eu-repo/classification/cti/33 | |
| dc.subject | info:eu-repo/classification/cti/3304 | |
| dc.subject | info:eu-repo/classification/cti/120307 | |
| dc.title | A temporal bayesian network for diagnosis and prediction | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
