Show simple item record

dc.contributor.authorFernández, Antonio
dc.contributor.authorRumí, Rafael
dc.contributor.authorSalmerón Cerdán, Antonio
dc.date.accessioned2017-07-07T07:17:32Z
dc.date.available2017-07-07T07:17:32Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10835/4895
dc.description.abstractIn this paper we propose an algorithm for answering queries in hybrid Bayesian networks where the underlying probability distribution is of class MTE (mixture of truncated exponentials). The algorithm is based on importance sampling simulation. We show how, like existing importance sampling algorithms for discrete networks, it is able to provide answers to multiple queries simultaneously using a single sample. The behaviour of the new algorithm is experimentally tested and compared with previous methods existing in the literature.es_ES
dc.language.isoenes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBayesian networkses_ES
dc.subjectProbabilistic reasoninges_ES
dc.subjectImportance samplinges_ES
dc.subjectMixtures of truncated exponentialses_ES
dc.titleAnswering queries in hybrid Bayesian networks using importance samplinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doihttps://doi.org/10.1016/j.dss.2012.03.007


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional