Dynamic Uncertain Causality Graph for Knowledge Representation and Probabilistic Reasoning: Directed Cyclic Graph and Joint Probability Distribution

IEEE Transactions on Neural Networks and Learning Systems
Qin Zhang

Abstract

Probabilistic graphical models (PGMs) such as Bayesian network (BN) have been widely applied in uncertain causality representation and probabilistic reasoning. Dynamic uncertain causality graph (DUCG) is a newly presented model of PGMs, which can be applied to fault diagnosis of large and complex industrial systems, disease diagnosis, and so on. The basic methodology of DUCG has been previously presented, in which only the directed acyclic graph (DAG) was addressed. However, the mathematical meaning of DUCG was not discussed. In this paper, the DUCG with directed cyclic graphs (DCGs) is addressed. In contrast, BN does not allow DCGs, as otherwise the conditional independence will not be satisfied. The inference algorithm for the DUCG with DCGs is presented, which not only extends the capabilities of DUCG from DAGs to DCGs but also enables users to decompose a large and complex DUCG into a set of small, simple sub-DUCGs, so that a large and complex knowledge base can be easily constructed, understood, and maintained. The basic mathematical definition of a complete DUCG with or without DCGs is proved to be a joint probability distribution (JPD) over a set of random variables. The incomplete DUCG as a part of a complete DUCG may r...Continue Reading

References

Jun 5, 2002·Journal of Attention Disorders·Patricia Murphy
Oct 29, 2005·IEEE Transactions on Neural Networks·Irina RishKarina Hernandez
Dec 31, 2009·IEEE Transactions on Neural Networks·Derrick T Mirikitani, Nikolay Nikolaev
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Nov 2, 2013·Computer Methods and Programs in Biomedicine·Chunling DongNingyu Wang
May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Qin ZhangZhihui Yang

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Citations

Mar 6, 2016·Neural Networks : the Official Journal of the International Neural Network Society·Yong HeMin Wu
Apr 22, 2016·IEEE Transactions on Neural Networks and Learning Systems·Chunling DongQin Zhang
May 5, 2017·Journal of Zhejiang University. Science. B·Shao-Rui HaoLan-Juan Li
May 16, 2020·Computational and Mathematical Methods in Medicine·Chunling DongNingyu Wang

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