Constrained abductive reasoning with fuzzy parameters in Bayesian networks
| dc.citation.epage | 105 | en_US |
| dc.citation.issue | 1 | en_US |
| dc.citation.spage | 87 | en_US |
| dc.citation.volume | 32 | en_US |
| dc.citation.woscount | 12 | |
| dc.contributor.author | Li, HL | en_US |
| dc.contributor.author | Kao, HY | en_US |
| dc.contributor.department | 資訊管理與財務金融系 註：原資管所+財金所 | zh_TW |
| dc.contributor.department | Department of Information Management and Finance | en_US |
| dc.date.accessioned | 2014-12-08T15:36:45Z | |
| dc.date.available | 2014-12-08T15:36:45Z | |
| dc.date.issued | 2005-01-01 | en_US |
| dc.description.abstract | This work proposes a novel approach for solving abductive reasoning problems in Bayesian networks involving fuzzy parameters and extra constraints. The proposed method formulates abduction problems using nonlinear programming. To maximize the sum of the fuzzy membership functions subjected to various constraints, such as boundary, dependency and disjunctive conditions, unknown node belief propagation is completed. The model developed here can be built on any exact propagation methods, including clustering, joint tree decomposition, etc. (C) 2003 Elsevier Ltd. All rights reserved. | en_US |
| dc.identifier.doi | 10.1016/S0305-0548(03)00204-1 | en_US |
| dc.identifier.issn | 0305-0548 | en_US |
| dc.identifier.journal | COMPUTERS & OPERATIONS RESEARCH | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1016/S0305-0548(03)00204-1 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/25110 | |
| dc.identifier.wosnumber | WOS:000223971300005 | |
| dc.language.iso | en_US | en_US |
| dc.subject | abductive reasoning | en_US |
| dc.subject | Bayesian networks | en_US |
| dc.subject | fuzzy parameters | en_US |
| dc.subject | optimization | en_US |
| dc.subject | constraints | en_US |
| dc.title | Constrained abductive reasoning with fuzzy parameters in Bayesian networks | en_US |
| dc.type | Article | en_US |