Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model

	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
	2015
发表期刊	Journal of Intelligent & Fuzzy Systems
卷号	29 期号:6 页码:2397-2403
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
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/55544
专题	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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