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| Title: | A new approach for convert multiply-connected trees in Bayesian networks |
| Authors: | Hussein, Baloochian
Alireza, Khantimoory
Saeed, Balochian |
| E-mail: | Hossein.baloochian@gmail.com |
| Keywords: | Bayesian networks
Neural networks (Computer science)
Bayesian statistical decision theory -- Data processing
Geometric function theory
Probability |
| Issue Date: | 11-Oct-2009 |
| Publisher: | Universiti Malaysia Perlis |
| Citation: | p.3A5 1 - 3A5 5 |
| Series/Report no.: | Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) |
| Abstract: | One 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. |
| Description: | Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. |
| URI: | http://hdl.handle.net/123456789/7309 |
| Appears in Collections: | Conference Papers
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