標題: ABDUCTIVE REASONING BY CONSTRUCTING PROBABILISTIC DEDUCTION GRAPHS FOR SOLVING THE DIAGNOSIS PROBLEM
作者: LI, HL
YANG, CC
交大名義發表
資訊管理與財務金融系 註:原資管所+財金所
National Chiao Tung University
Department of Information Management and Finance
關鍵字: ABDUCTION;CAUSAL NETWORK;DEDUCTION;DEDUCTION GRAPH;DIAGNOSIS;EXPERT SYSTEM;INTEGER PROGRAMMING;MUTUALLY INDEPENDENT OR EXCLUSIVE;OPTIMIZATION;PROBABILISTIC REASONING
公開日期: 1-May-1991
摘要: An 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.
URI: http://hdl.handle.net/11536/3800
ISSN: 0167-9236
期刊: DECISION SUPPORT SYSTEMS
Volume: 7
Issue: 2
起始頁: 121
結束頁: 131
Appears in Collections:Articles