Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model
Zhu, Y. G.; D. Y. Liu; Y. Li and X. H. Wang
刊名Journal of Intelligent & Fuzzy Systems
2015
卷号29期号:6页码:2397-2403
英文摘要Active and dynamic fusion for fuzzy and uncertain data have key challenges such as high complexity and difficult to guarantee accuracy, etc. In order to resolve the challenging issues, in this article a selective and incremental data fusion approach based on probabilistic graphical model is proposed. General Bayesian networks are adopted to represent the relationship among the data and fusion result. It purposively selects the most informative and decision-relevant data for fusion based on Markov Blanket in probabilistic graphical model. Meanwhile we present a special incremental learning method for updating the fusion model to reflect the temporal changes of environment. Theoretical analysis and experimental results all demonstrate the proposed method has higher accuracy and lower time complexity than existing state-of-the-art methods.
收录类别SCI ; EI
内容类型期刊论文
源URL[http://ir.ciomp.ac.cn/handle/181722/55544]  
专题长春光学精密机械与物理研究所_中科院长春光机所知识产出
推荐引用方式
GB/T 7714
Zhu, Y. G.,D. Y. Liu,Y. Li and X. H. Wang. Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model[J]. Journal of Intelligent & Fuzzy Systems,2015,29(6):2397-2403.
APA Zhu, Y. G.,D. Y. Liu,&Y. Li and X. H. Wang.(2015).Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model.Journal of Intelligent & Fuzzy Systems,29(6),2397-2403.
MLA Zhu, Y. G.,et al."Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model".Journal of Intelligent & Fuzzy Systems 29.6(2015):2397-2403.
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