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dc.contributor.authorLI, HLen_US
dc.contributor.authorYANG, CCen_US
dc.date.accessioned2014-12-08T15:05:15Z-
dc.date.available2014-12-08T15:05:15Z-
dc.date.issued1991-05-01en_US
dc.identifier.issn0167-9236en_US
dc.identifier.urihttp://hdl.handle.net/11536/3800-
dc.description.abstractAn algorithm is proposed for finding optimal solutions of the diagnosis problem by using deduction graphs (DG) to accomplish abductions of multiple causes and multiple symptoms. The relationship among causes, symptoms, and possible intermediaries is represented by a causal network. The algorithm accomplishes the abduction by constructing a deduction graph DG(C,S) from the cause set C to the symptom set S representing the subnetwork such that the product of the prior probability, P(C), of C and the conditional probability, P(SC), of DG(C,S) is maximized. An optimal solution is achieved by solving a 0/1 linear integer programming problem. Based on some assumptions, the algorithm can deal with a causal network involving various mutually independent deduction graphs.en_US
dc.language.isoen_USen_US
dc.subjectABDUCTIONen_US
dc.subjectCAUSAL NETWORKen_US
dc.subjectDEDUCTIONen_US
dc.subjectDEDUCTION GRAPHen_US
dc.subjectDIAGNOSISen_US
dc.subjectEXPERT SYSTEMen_US
dc.subjectINTEGER PROGRAMMINGen_US
dc.subjectMUTUALLY INDEPENDENT OR EXCLUSIVEen_US
dc.subjectOPTIMIZATIONen_US
dc.subjectPROBABILISTIC REASONINGen_US
dc.titleABDUCTIVE REASONING BY CONSTRUCTING PROBABILISTIC DEDUCTION GRAPHS FOR SOLVING THE DIAGNOSIS PROBLEMen_US
dc.typeArticleen_US
dc.identifier.journalDECISION SUPPORT SYSTEMSen_US
dc.citation.volume7en_US
dc.citation.issue2en_US
dc.citation.spage121en_US
dc.citation.epage131en_US
dc.contributor.department交大名義發表zh_TW
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.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:A1991FP61600004-
dc.citation.woscount2-
Appears in Collections:Articles