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	Probabilistic SDG model and approach to inference for fault analysis
	Yang Fan ; Xiao De-yun
	2010-05-06 ; 2010-05-06
关键词	Theoretical or Mathematical/ Bayes methods cause-effect analysis directed graphs fault diagnosis large-scale systems probability/ fault analysis probabilistic signed directed graph cause-effect relationships large-scale complex systems Bayesian inference junction tree algorithm/ A0210 Algebra, set theory, and graph theory A0250 Probability theory, stochastic processes, and statistics B0250 Combinatorial mathematics B0240Z Other topics in statistics C1160 Combinatorial mathematics C1140Z Other topics in statistics
中文摘要	Signed directed graph (SDG) model is a significant tool to express cause-effect relationships between variables in large-scale complex systems, but it also has some disadvantages that are difficult to overcome. A new kind of model, probabilistic SDG model, is proposed to describe the dependence relationships with conditional probabilities. In the framework of probabilistic SDG model, inference approach is presented, which implements Bayesian inference with elimination algorithm and junction tree algorithm to calculate the fault probability. Finally, a probabilistic SDG model is established for a typical instance of 65 t/h boiler system, which proves the validation of the model and inference approach.
语种	中文 ; 中文
出版者	Northeastern Univ ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9021]
专题	清华大学
推荐引用方式 GB/T 7714	Yang Fan,Xiao De-yun. Probabilistic SDG model and approach to inference for fault analysis[J],2010, 2010.
APA	Yang Fan,&Xiao De-yun.(2010).Probabilistic SDG model and approach to inference for fault analysis..
MLA	Yang Fan,et al."Probabilistic SDG model and approach to inference for fault analysis".(2010).

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