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dc.contributor.authorHussein, Baloochian
dc.contributor.authorAlireza, Khantimoory
dc.contributor.authorSaeed, Balochian
dc.date.accessioned2009-11-17T07:36:06Z
dc.date.available2009-11-17T07:36:06Z
dc.date.issued2009-10-11
dc.identifier.citationp.3A5 1 - 3A5 5en_US
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/7309
dc.descriptionOrganized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.en_US
dc.description.abstractOne of the purposes of the Bayesian networks is inference. There have different algorithms for this purpose. Message passing algorithms us one of the inference approaches on the junction trees. However all of the Bayesian networks are not singly-connected tree, but solution was presented for making junction tree from multiply-connected tree. This article presents a new approach for converting multiply-connected tree to junction tree by moor and meely machine concepts. This approach is based on edge labeling by conditional probability, then moral and triangulation steps transact based on five-step design.en_US
dc.description.sponsorshipTechnical sponsored by IEEE Malaysia Sectionen_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlisen_US
dc.relation.ispartofseriesProceedings of the International Conference on Man-Machine Systems (ICoMMS 2009)en_US
dc.subjectBayesian networksen_US
dc.subjectNeural networks (Computer science)en_US
dc.subjectBayesian statistical decision theory -- Data processingen_US
dc.subjectGeometric function theoryen_US
dc.subjectProbabilityen_US
dc.titleA new approach for convert multiply-connected trees in Bayesian networksen_US
dc.typeWorking Paperen_US
dc.contributor.urlHossein.baloochian@gmail.comen_US


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