Research on Approximate Reference Algorithm of SVDBN based on Sliding Window

doi:10.16182/j.issn1004731x.joss.18-0042

Abstract

Abstract: Structure-variable dynamic Bayesian networks (SVDBN) have the special advantage in dealing with the uncertainty of the unstable processes. In order to overcome the disadvantage that the inference algorithms of the SVDBN are unable to apply online, introducing the concepts of SVDBN sliding window and the window width, the online approximate inference mechanism of structure-variable dynamic Bayesian networks based on sliding window is explained, and two online algorithms are proposed, that is the recursive inference algorithm of structure-variable discrete dynamic Bayesian networks (SVDDBN) based on sliding window and the fast inference algorithm of SVDDBN based on sliding window. Experimental simulations show the effectiveness of the two inference algorithms and compare their complexity, application, updated time and so on.

Key words: structure-variable discrete dynamic Bayesian networks, approximate inference, information dissemination, sliding window

CLC Number:

TP181

Chen Haiyang, Chai Bing, Wang Ruilan, Cao Lu. Research on Approximate Reference Algorithm of SVDBN based on Sliding Window[J]. Journal of System Simulation, 2020, 32(2): 217-228.

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